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First Impression: November 2018

© Agro Environmental Development Society (AEDS), Majhra Ghat, Rampur, (UP), India

International Conference on Emerging Issues in Agricultural, Environmental and Applied Sciences for Sustainable Development (EIAEASSD-2018)

ISBN: 978-93-88237-24-6

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AcknowledgementThe proceedings of the International Conference on “Emerging Issues in Agricultural, Environmental & Applied Sciences for Sustainable Development” is the outcome of long dedicated efforts of many individuals who directly or indirectly supported us during its compilation and upbringing of this valuable book; many of whom deserve special mention.

Editors are thankful to all the contributing authors for their valuable submissions, cooperation and providing most up-to-date information on the diverse aspects of the subject regardless of their busy schedules; Dr. Vineet Kumar, Department of Environmental Microbiology, Dr. Shakuntala Misra National Rehabilitation University, Lucknow; and Mr. Gaurav Saxena, Department of Environmental Microbiology (DEM), Babasaheb Bhimrao Ambedkar (Central) University, Vidya Vihar, Raebareli Road, Lucknow, Uttar Pradesh, India for helping us in various ways during the book project.

We are extremely thankful to our Publishing Editors for the support and valuable advice and skillful organization and management of entire publishing process of book proceedings of the conference in an efficient and professional manner. We are also heartily thankful to the Almighty God for helping us through the entire journey and making the experience enjoyable. We hope that this proceedings book might be helpful for relevant researchers in the field.

EditorsNovember 27–29, 2018

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Contents

1. Heavy Metals in Contaminated Soils and Vegetables of Jagdalpur, ChhattisgarhTarence Thomas, P. Smriti Rao Ashish David and Ashima Thoma 1

2. Identifying the Risk Factors of Extra Pulmonary Tuberculosis: An OverviewTalluri Rameshwari K.R. and Ajay Kumar Singh 7

3. Screeningof Rhizobacteria from Tomato Crop to Control Bacterial Wilt Pathogen A Research Based on Antibiosis

Akash Mishra, Shraddha P. Mishra, Anfal Arshi, Merwyn S. and Madhu Bala 15

4. Frontline Demonstrations: An Effective Tool for Transfer of Wheat (Wh-1105) Production Technology in Hanumangarh District of Rajasthan

Akshaya Ghintala, Bheiru Singh, Mukesh Kumar Verma and Manohar Lal Sain 20

5. Isolation and Identification of A Cholesterol Oxidase Producing StrainAmreen Khan and C.K.M. Tripathi 25

6. Modeling of Rainfall—Runoff Processes using HBV Model in The Upper Betwa River BasinAshish David, D.M. Denis and Shakti Suryavanshi 35

7. Frontier Aspects in Agricultural Waste Management for Environmental SustainabilityB.S. Sagar, B.R. Sahithya 47

8. Assessment of Noise Level during Dusseharaat Ghoorpur, Bara Tehsil, Prayagraj, Uttar Pradeshy

Mohd Nafees, Satyendra Nath, and R. P. Singh 54

9. Application of Breadfruit in Food ProductsBhopal Singh, Rekha Rani and Chetan N. Dharaiya 58

10. Modern Techniques to Evaluate the Quality of Food ProductsChetan Dharaiya, Atanu Jana and Rekha Rani 62

11. Occurrence of Black Point Disease Complex of Wheat in Eastern Uttar PradeshD.N. Shukla, J.P. Shrivastava and Manish Kumar Yadav 76

12. A Detailed Review of Biomass Energy and its Challenges and Impact on the EnvironmentDevanshu Agnihotri and Mamta Sagar 83

13. Poly Low Tunnel Technology for off Season Tomato Cultivation with Drip Irrigation and Fertigation for Crop Diversification in Bundelkhand, UP

Shweta Soni, Govind Vishwakarma and Pintu Meena Pahadi 91

14. Biofertilizers: A Boon for AgricultureGovind Vishwakarma and Shweta Soni 94

15. Application of Sen’s Multi-Objective Programming Approach: Analysis of Farmers’ Livelihood Strategies by Optimizing Resource Use in Farming Area of Adamawa State, Nigeria

Gwandi O., V. Kamalvanshi, Saidu Buba and Saket Kushuwaha 100

16. Assessment of Heavy Metal Contamination in Leafy Vegetables Near Sewage Treatment Plants of Allahabad City, Uttar Pradesh, India

Harshita Baranwal, Dr. Satyendra Nath, Tarence Thomas and P. Smrity Rao 109

17. Front Line Demonstrations: An Effective Way of Productivity Enhancement of Pearlmillet in Hanumangarh District of Rajasthan

Bheiru Singh, Akshaya Ghintala, Mukesh Kumar Verma and Manohar Lal Sain 113

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Contents xix

18. Effect of Fly Ash on Soil Physical Properties under Sunflower-Spinach-Sunflower Crop Rotation System

Nouraldin Almadi Ibrahim Basha, Abhishek James, Ram Bharose and Smriti Rao 117

19. Impact of Thermal Effluent by Some Selected Physiochemical Properties on Total Bacterial Counts in Kota Barrage Lake, Kota, Rajasthan, India

Parveen Kumar, Manju Rawat Ranjan, Ashutosh Tripathi and S. Balachandaran 131

20. Piper nigrum: An Ecofriendly Source for Finish Application on Base Fabric for Museum Showcases

Pooja Singh and Alka Goel 137

21. Strategy for Doubling Farmers Income—A Case of Organic Turmeric Growers of Kandhamal District of Odisha

Prangya Paramita Sahoo, K.K. Sarangi, Suvangi Rath 143

22. Review on: Response of Nitrogen, Sulphur and Foliar Application of Zinc on Growth, Yield, Quality and Economics of Green Gram (Vigna radiata L.)

Prasad Mithare, R.S. Muniswamy, Rachana and Vikram Singh 153

23. Effect of Different Levels of N P K and Rhizobium on Soil Physico-Chemical Properties and Yield Attribute of Black Gram (Vigna Mungo L.) VAR. SHEKHAR–2

Raghu Nandan Singh Khatana, Tarence Thomas and P. Smriti Rao 165

24. Economics of Mustard (Brassica juncea L.) Cultivation through Integrated Nutrient Management Practices

Rama Kant Singh, Pankaj Kumar, S.K. Singh, S.B. Singh and R.N. Singh 169

25. Economic Impact of Free-Ranging Wildlife on Major Agricultural Crops in Eastern Uttar Pradesh, India

Ramchandra and Tarence Thomas 177

26. Significant of Anaerobic Treatment of High Sulphate Content Tannery Effluent at Jajmau, Kanpur, Uttar Pradesh

Richa Gupta, Tanu Jindal, Prateek Srivastava, Ambrina Sardar Khan and Ajay Kanauji 187

27. Morphometric Analysis and Bioefficacy of Trichogramma cordubensis Vargas & Cabello Against Teak Defoliator, Hyblaea puera

Salman Khan and Mohd. Yousuf 193

28. Selecting Sites to Save Maximum SpeciesShri Niwas Singh 199

29. Geospatial Scrutiny of Soil Samples Collected Nearby National Mineral Development Corporation, Nagarnar, District Bastar, Chhattisgarh, India

P. Smriti Rao, Tarence Thomas, Ashish David, and Ashima Thomas 209

30. Terminal Heat Stress Effects on Morpho-Physiological Characters of Indian Mustard (Brassica juncea L.) Genotypes

Suman Yadav 221

31. Speciation of Klebsiella Isolates from Various Clinical Samples and their Antibiotic Susceptibility Pattern

Talluri Rameshwari K.R., Deepa S., Anuradha K. and Sumana K. 226

32. Bihar Higher Education ChallengesAbha Mishra 239

33. Degradation and Decolourisation of Anaerobically Treated Distillery Effluent in Two-Stage Sequential Treatment by Bacteria and Constructed Wetland

Vineet Kumar, Gaurav Saxena, Chhatarpal Singh and Ram Chandra 241

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xx Contents

34. Effect of Different Planting Pattern and Nitrogen Management on Growth and Yield in Pearlmillet (Pennisetum Glaucum L.)+Greengram (Vigna Radiata L.) Intercropping System

Virpal Kaur, Rachana Prasad Mithare and Rajesh Singh 249

35. Ergonomic Evaluation in Weeding Operation Conducted by Hand Hoe (Khurpa) and Wheel Hoe of Wheat Crop for Female Respondents

Vishnu Ji Awasthi, Ashok Tripathi, Rahul Chaudhary and Mirtunjay Pandey 260

36. Synthesis of Iron Oxide Nanoparticles using Leaf Extract of Ocimum sanctum for Wastewater Treatment

Surya Pratap Goutam Diptarka Roy and Gaurav Saxena 272

37. Isolation and Characterization of Bacteria Capable for COD Removal from Tannery Wastewater: A Bioremediation Study

Gaurav Saxena, Chhatarpal Singh, Vineet Kumar and Ram Naresh Bharagava 278

38. Agro-industrial Waste as Source of Nutraceuticals and Health Promoting MoleculesMamta Shukla and R.L. Singh 283

AUTHOR INDEX 290

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ISBN: 978-93-88237-24-6

Heavy Metals in Contaminated Soils and Vegetables of Jagdalpur, Chhattisgarh

Tarence Thomas1, P. Smriti Rao1, Ashish David2,3 and Ashima Thoma3

1Department of Soil Science, Sam Higginbottom University of Agriculture Technology & Sciences,

Allahabad–211007, U.P.2Department of Soil Water and Land Conservation,

Sam Higginbottom University of Agriculture Technology & Sciences, Allahabad–211007, U.P.

3Naini Agricultural Institute, Sam Higginbottom University of Agriculture Technology and Sciences,

Allahabad–211007, U.P., India

ABSTRACT

This study has been conducted to determine the concentration of heavy metals Lead (Pb), Cadmium(Cd), Copper (Cu) and Iron (Fe) in soil and some grown vegetables of Jagdalpur. (Bastar) Comparing the results of heavy metals in soil and vegetables by using Atomic Absorption Spectrometer, (Perkin Elmer A Analyst 400) double beam with their respective natural level. Fe concentration varied considerably in tomato and chili are crossed permissible limits. Copper, Lead and Cadmium concentration is below than the safe limit. Overall, this study indicates that the soil and vegetable sample is contaminated by toxic heavy metals.

Keywords: Heavy Metals, Soil, Vegetables

INTRODUCTION

Vegetables are widely used for the culinary purpose and are very important in the human diet because of the presence of vitamins and minerals salts. They contain water, calcium, iron, sulfur, and potash (Sobukola et al. 2010). They also act as neutralizing agents for acidic substances forming during digestion (Thompson and Kelly 1990). Therefore fruits and vegetables are very useful for the maintenance of health as a preventive treatment of various diseases (D’ Mello, 2003). The presence of heavy metals may have a negative influence on the quality of vegetables and fruits causing changes to their taste and smell.

The term “heavy metals” to any metallic elements that have a relative density greater than 4gcm-3. In the group of heavy metals, one can distinguish both the element necessary for living organism and elements whose physiological role is unknown and those that are “neutral” for plants, animals, and humans. Accumulation of heavy metals by vegetables may depend on plant species as well as temperature, moisture, organic matter, Ph, nutrient availability and concentration of heavy metals. The total concentration of heavy metals in soil and water, however, varies from local to regional and further to the continental level. The uptake and

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2 Emerging Issues in Agricultural, Environmental and Applied Sciences for Sustainable Development

ISBN: 978-93-88237-24-6

accumulation of Cd, Cr, Fe were higher during the summer due to high transpiration rate as compared to winters whereas Cu, Ni, Pb accumulated more in winter. Heavy metals exert a toxic effect on soil. Metals are industrious natural contaminants, have long biological half-lives and potential for accumulation in different body organs leading to an unwanted side effect. Metal toxicity in plants is aggravated at a higher temperature and low ph as it facilitates the mobility from roots to shoots hence results in the change of the diverse population size and over all activity of soil microbial communities. In Indian food tomato and chili is the main ingredient for all diet. Heavy metals concentration may inhibit some vital plant processes.e. photosynthesis, mitosis, and H2O absorption. The consumption of heavy metal contaminated food can seriously deplete some essential nutrients in the body that are further responsible for decreasing immunological defenses, growth retardation disabilities associated with malnutrition and high prevalence of upper gastrointestinal cancer rates.

EXPERIMENTAL METHODOLOGY

Study AreA

The study was conducted around Jagdalpur city of Bastar district Chhattisgarh during March 2017. This is one of the tribal districts of the state. Location of the city is between 19.107 degree north latitudes and 81.953 degrees east longitude. The district is located in the southern part of Chhattisgarh situated at the height of 2000 m above plateau MSL Various small-scale industries situated in this town. A large area around industries have less access to clean water resources, so farmer use treated and untreated wastewater for irrigation. The hypothesis behind the present study is that the irrigation with wastewater contaminates soil and environment and the produce may elevate the levels of heavy metals in vegetable through surface deposition.

SAmpling

Study SiteFig. 1: Map Showing the Sampling Area

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Economics of Mustard (Brassica juncea L.) Cultivation through Integrated Nutrient Management Practices 3

ISBN: 978-93-88237-24-6

The soil sample and the edible portions of vegetables i.e. tomato and chili were collected from Jagdalpur area. Randomly soils were collected from 6 fields of which 3 fields having the produce of tomato and 3 having chili production. Soil samples were collected from two depths of 0-15 and 15-30 cm. The soil samples were oven dried at 40ᵒC for 48 hours and then crushed with a hammer and sieved by 2mm size.

The vegetables were classified according to their common name and scientific name:

Table 1: Scientific Names of Vegetables

Common name

Vegetable commodity Scientific name

Tomato Solanum Lycopersicon

Chilli Capsicum annum L.

SAmple prepArAtion And digeStion

Vegetable samples were brought back to the laboratory and washed under clean tap water followed by double distilled water to eliminate soil and air-borne pollutants. After removing the extra water from the surface of vegetables with the help of blotting papers, samples were cut into pieces packed in separate bags and kept in the oven until a constant weight was achieved. The dried samples were ground and passed through a sieved of 2mm size and then kept at room temp for further analysis.

1.0 gram of dried sample was taken and then 5 ml of conc. HNO3was added and kept overnight. Next day 12 ml of a di-acid mixture of conc. HNO3and HClO4 in 3:1 ratio was added and digested on hot plate oven till the white reddish brown fumes come out of the sample and the sample was evaporated till 2 ml was left in the flask. The resulting solution was cooled and filtered with Whatman filter paper 42. Finally, the volume of the extract was made up to 50 ml using double distilled water.

1.0-gram oven dried soil samples were transferred in 100 ml beaker to which 30 ml of 3:1 ratio of conc HNO3: HClO4 was added. The mixture was kept in a hot plate for 105ᵒC for few hours till reddish brown fumes come out and the sample was evaporated till 2 ml was left in the flask. The resulting solution was cooled and filtered with Whatman filter paper 42. Finally, the volume of the extract was made up to 50 ml using double distilled water.

Table 2: Concentration of Heavy Metals (Mg/Kg or ppm) in Vegetables

Commodity Cu Cd Fe Pb

Tomato (Site 1) 0.32 0.27 16.32 0.26

Tomato (Site 2) 0.41 0.77 8.427 0.2

Tomato (Site 3) 0.47 0.94 0.042 0.19

Chilli (Site 4) 0.14 0.02 11.4 0.32

Chilli (Site 5) 1.19 0.51 0.03 0.51

Chilli (Site 6) 0.6 0.2 9.65 0.92

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ISBN: 978-93-88237-24-6

AnAlySiS

The concentration of heavy metals was carried out by using Atomic Absorption Spectrophotometer, (Perkin Elmer A Analyst 400) Double Beam and deuterium background hollow cathode lamps of Fe, Pb, Cd, Cu were used at specific wavelengths. All samples were run in triplicates.

Fig. 2: Represents the Heavy Metal Concentration in the Edible Parts of Vegetables of Different Sites

Table 3: Concentration of Heavy Metals (Mg/Kg Or Ppm) in Soil

Sampling Site Cu Cd Fe Pb

Site 1 0.42 0.77 19.32 0.76

Site 2 1.09 0.97 15.47 0.82

Site 3 1.17 1.74 12.42 0.99

Site 4 0.94 0.82 14.4 0.82

Site 5 1.59 0.71 14.93 0.71

Site 6 1.36 0.52 15.65 1.12

Fig. 3: Represents the Heavy Metal Concentration in Different Soils of Jagdalpur

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The results of this study showed that the average concentration detected range from 0.2 to 5.75 mg/kg for given samples of vegetables and soil. The highest mean of Cd, Fe, Cu, and Pb respectively. The soil samples are contaminated by toxic heavy metals Fe concentration varied considerably in tomato and chili crossed permissible limits. Copper, Iron, and Lead concentrations are below than the safe limit. Overall, this study indicates that the vegetable sample is contaminated by toxic heavy metals. The level of these metals found in our study are compared with those reported for similar vegetables from some other part of the world.

CONCLUSION

From the given results it clears that Fe, Cu, Cd, Pb are present in the sample. These metals show toxic potential with an injury to human health. The results of the present study showed that consumers are at lesser risk of consuming fresh vegetables with this level of heavy metals beyond permissible limits as defined by the Indian Prevention of Food Adulteration Act 1954.

ACKNOWLEDGMENT

I would like to express my deepest appreciation to all those who provided me with the possibility to complete this research. A special gratitude to Dr. Tarence Thomas, HoD, Department of Soil Science and Agricultural Chemistry whose contribution in stimulating suggestion and encouragement helped me to coordinate my project.

REFERENCES

[1] Arora, M., Kiran, B., Rani, A., Kaur B. and Mittal, N. (2008) Heavy metal accumulation in vegetables irrigated with water from different sources. Food Chemistry, 111, 811-815. doi:10.1016/j.food chem. 2008.04.0 49

[2] Arora M. Wichelns, L.D., Raschid- sally P.G., Mc. Cornick, P.D., Bhari, A. and Minhas, P.S. “ The challenges of waste water irrigation in developing countries’’. Agriculture water management 2008, 97:561-568.

[3] Ashraf R. and Ali T. A.., Effect of heavy metals on soil microbial community and mung bean seed and germination. Pakistan Journals of botany,39(2), 629-636 (2007)

[4] Awasthi S K (2000). Prevention of food adulteration act No.37 of 1954. Central and state rule as amended of 1993. 3rd Edition. Ashoka Law House, New Delhi

[5] Divkli, U., Horzum, N., Soylak, M. and Elci, L. 2006. Trace heavy metal content of some spices and herbal plants from western Anatolia, Turkey. International Journal of food Science and Technology 41: 712- 716.

[6] D’ Mello, J.P.G. 2003. Food safety: contaminants and toxins, Scottish Agricultural college, Edinburgh, UK, 480 pages.

[7] D’ Mello, J.P.G., 2003. Food Safety: Contaminants and toxins. CABI Publishing, Wallinford, Oxon, UK, Cambridge, MA, p. 480

[8] Environmental Protection Agency, Toxicological review of trivalent chromium (CAS no. 16065-83-1) in support of summary information on the integrated risk information system (IRIS), US Environmental Protection Agency, Washington, DC, 1998.

[9] FAO/WHO, “Evaluation of certain food additives and Contaminants. Geneva, World Health Organization, Joint FAO/WHO Expert committee on Food Additives, World Health Organization Technical Report Series,“vol 859, pp.29-35, 1995

[10] Guala S.D., Vega F.A. AND Covelo E.F., The dynamics of heavy metals in plant soil interactions. Ecological Modelling, 221, 1148-1152 (2009)

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[11] M. A. Radwan, and A.K. Salama, “ Market basket survey for some heavy metals in Egyptian fruits and vegetables,’’ Food and Chemical Toxicology, vol. 44, no. 8, pp. 1273-1278, 2006.

[12] Najat k. Mohammed, fatma O. Khamis “ Assessment of heavy metal contamination in vegetables consumed in Zanzibar vol. 4 No. 8588-594 (2012).

[13] Perveen S., Ihsanullah I., Study of accumulation of heavy metals in vegetables Receiving Sewage Water J. Chem. Soc. Pak., Vol 33, No. 2, 2011 page 220-227.

[14] Ramesh H.L. and Yogananda Moorthy V.N. Assessment of Heavy Metal contamination in Green Leafy Vegetables Grown in Bangalore Urban District of Karnataka. Advances in Life Science and Technology Vol. 6, 2012

[15] Sobukola, O.P., Adeniran, O.M.,Odedairo, A.A. & Kajihausa, O.E. (2010). Heavy metal level of some fruits and leafy vegetables from selected,markets in Lagos, Nigeria. Afr.J. Food Sci., 4(2): 389-393.

[16] Thompson, H.C. and Kelly, W.C. 1990. Vegetable Crops. 5th Edn., McGraw Hill Publishing Company Ltd., New Delhi.

[17] Uwah E.I., Ndahi N.P. and Ogugbuaja V.O,2009. Study of the levels of some Agricultural Pollutants in Soils, and Water Leaf “(Talinum Triangulare) obtained in maiduguri, Nigeria. Journal of Applied Science in Environmental Sanitation.(221)

[18] WHO. 1992. Cadmium, Environmental Health Criteria, Geneva Vol. 134.[19] WHO. 1995. Lead. Environmental Health Criteria, Geneva, Vol. 165.

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Identifying the Risk Factors of Extra Pulmonary Tuberculosis: An Overview

Talluri Rameshwari K.R.1 and Ajay Kumar Singh2

1Division of Microbiology and Department of Water and Health, Faculty of Life Sciences, JSS Academy of Higher Education and Research,

Sri Shivarathreeshwara Nagar, Mysuru–5700152Department of Microbiology, Babasaheb Bhimrao Ambedkar University,

Raebareli Road, Vidya Vihar, Lucknow, Uttar Pradesh–226025E-mail: [email protected]

ABSTRACT

Tuberculosis (TB) is an infectious disease usually caused by the bacterium Mycobacterium tuberculosis (MTB). Tuberculosis generally affects the lungs, but can also affect other parts of the body. Most infections do not have symptoms, in which case it is known as latent tuberculosis. About 10% of latent infections progress to active disease which, if left untreated, kills about half of those infected. Disease patterns have changed, with a higher incidence of the disseminated and extrapulmonary disease now found. Extra pulmonary (25%) sites of infection commonly include lymph nodes, pleura, and osteoarticular areas, although any organ can be involved.

The diagnosis of extrapulmonary infectious disease will be elusive, necessitating a high index of suspicion. Physicians ought to acquire a radical history specializing in risk behaviors for human immunological disorder virus (HIV) infection and infectious disease. Antituberculous medical care will minimize morbidity and mortality, however, may have to be initiated by trial and error. A negative smear for acid-fast bacillus, a lack of granulomas on histopathology, and failure to culture Mycobacterium tuberculosis do not exclude the diagnosis. New diagnostic modalities like enzyme levels and enzyme chain reaction will be helpful in bound types of extrapulmonary infectious disease. In general, similar regimens square measure accustomed to treat pulmonary and extrapulmonary infectious disease, and responses to antituberculous medical care square measure similar in patients with HIV infection and in those while not. Treatment period may have to be extended for the central system and skeletal infectious disease, counting on drug resistance, and in patients WHO have a delayed or incomplete response. Adjunctive corticosteroids could also be useful in patients with tuberculous meningitis, tuberculous pericarditis, or miliary tuberculosis with refractory hypoxemia.

Keywords: Tuberculosis, Extra Pulmonary Tuberculosis, Miliary, Genitourinary, Meningitis, Peritonitis Pericarditis, Lymphadenitis, Cutaneous, Bones and Joints, Gastrointestinal, Liver and etc.

INTRODUCTION

The year 2015 is a watershed moment in the battle against Tuberculosis (TB). It marks the deadline for global TB targets set in the context of the Millennium Development Goals (MDGs) and is a year of transitions: from the MDGs to a new era of Sustainable Development Goals (SDGs), and from the Stop TB Strategy to the End TB Strategy. It is also two decades since

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WHO established a global TB monitoring system; since that time, 20 annual rounds of data collection have been completed. Using data from 205 countries and territories, which account for more than 99% of the world’s population, this global TB report documents advances in prevention, diagnosis, and treatment of the disease. It also identifies areas where efforts can be strengthened (NICE 2016).

Mycobacterium tuberculosis has been identified as the major cause of the Tuberculosis and risk factors of the Extra Pulmonary Tuberculosis. Globally Extra Pulmonary tuberculosis is the commonest diseases in the world. Epidemiology studies have proved that the TB is the re-emerging disease at the present. Despite all the effective vaccine and chemotherapy tuberculosis still sustains in many developing countries including India. New interventions are needed to interrupt the transmission of extra pulmonary tuberculosis and eradicate the agent, Mycobacterium tuberculosis,. The tubercle bacilli infect lungs causing pulmonary tuberculosis and also affect other organs viz., bronchus, lungs parenchyma, pleura, intrathoracic broncho pulmonary lymph nodes, bones, joints, CNS (usually meningitis, but can occur in brain or spine), larynx, pericardial cavity, abdominal sites, kidneys and genitourinary tract causing in extra pulmonary tuberculosis. The spectrum of the EPTB ranges in different proportions at different organs and remain dormant for years at a specific site before disease expression.

EPTB has remained a major public health problem since the dawn of civilization and continues to impose a major financial burden on the society. Despite the availability of modern techniques of diagnosis and effective drugs, Indian continues to host one-fourth of the world’s EPTB disease burden. It is estimated that every two minutes a person dies from TB in India. Keeping this in mind, the initiative was taken to carry out an extensive review of the current medical literature on the subject of diagnosis and treatment of various forms of extra-pulmonary tuberculosis. A large number of clinical specialists from different fields and experts from India and abroad have worked tirelessly for the past one and a half years to bring out an evidence-based, comprehensive guidelines on the management of all forms of extra-pulmonary tuberculosis.

Different types of Extra Pulmonary Tuberculosis (EPTB) include:

miliAry tB: Miliary TB was also known as generalized hematogenous TB, miliary TB occurs when a tuberculous lesion erodes into a blood vessel, disseminating millions of tubercle bacilli into the bloodstream and throughout the body. Uncontrolled massive dissemination can occur during primary infection or after reactivation of a latent focus. The lungs and bone marrow are most often affected, but any site may be involved (Garcia Rodriguez J F et al., 2011).

Miliary TB is most common among children < 4 yr and Immuno compromised people. The elderly symptoms include fever, chills, weakness, malaise, and often progressive dyspnea. Intermittent dissemination of tubercle bacilli may lead to a prolonged fever of unknown origin (FUO). Bone marrow involvement may cause anemia, thrombocytopenia, or a leukemoid reaction (Critchley JA et al., 2013)

genitourinAry tB: Infection of the kidneys may manifest as pyelonephritis (eg, fever, back pain, pyuria) without the usual urinary pathogens on routine culture (sterile pyuria). Infection commonly spreads to the bladder and, in men, to the prostate, seminal vesicles, or epididymis, causing an enlarging scrotal mass. Infection may spread to the perinephric space and down the psoas muscle, sometimes causing an abscess on the anterior thigh. Salpingo-oophoritis can

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Identifying the Risk Factors of Extra Pulmonary Tuberculosis: An Overview 9

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occur after menarche, when the fallopian tubes become vascular. Symptoms include chronic pelvic pain and sterility or ectopic pregnancy due to tubal scarring (Peto HM et al., 2006).

tB meningitiS: Meningitis often occurs in the absence of infection at other extrapulmonary sites. In the US, it is most common among the elderly and immuno compromised, but in areas where TB is common among children, TB meningitis usually occurs between birth and 5 yr. At any age, meningitis is the most serious form of TB and has high morbidity and mortality. It is the one form of TB believed to be prevented in childhood by vaccination with BCG (Espinosa et al., 2014).

Symptoms are low-grade fever, unremitting headache, nausea, and drowsiness, which may progress to stupor and coma. Kernig and Brudzinski signs may be positive (Thwaites GE et al., 2013). Stages are:

1. Clear sensorium with abnormal CSF

2. Drowsiness or stupor with focal neurologic signs

3. Coma

Stroke may result from thrombosis of a major cerebral vessel. Focal neurologic symptoms suggest a tuberculoma.

tB peritonitiS: Peritoneal infection represents seeding from abdominal lymph nodes or from salpingo-oophoritis. Peritonitis is particularly common among alcoholics with cirrhosis. Symptoms may be mild, with fatigue, abdominal pain, and tenderness, or severe enough to mimic an acute abdomen (Fisher D, et al., 2013).

A 24-year-old male patient with a fibrotic type of tubercular peritonitis.

Fig. A: Marked Ascites with Centrally Displaced Bowel Loops, Mimicking Peritoneal Carcinomatosis. Splenic Microabscesses (Curved Arrow) Also Noted

(Subhaschandraet Al., 2016)B: Peripherally Enhancing Central Hypodense Mesenteric Lymph Nodes (Arrow)

C: Smooth Peritoneal Thickening And Enhancement

tB pericArditiS: Pericardial infection may develop from foci in mediastinal lymph nodes or from pleural TB. In some high-incidence parts of the world, TB pericarditis is a common cause of heart failure. Patients may have a pericardial friction rub, pleuritic and positional chest pain, or fever. Pericardial tamponade may occur, causing dyspnea, neck vein distention, paradoxical

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pulse, muffled heart sounds, and possibly hypotension (Reuter H et al ., 2006). Granulomatous peritonitis in 25-year-old male patient.

TB Lymphadenitis: Tuberculous lymphadenitis (scrofula) typically involves the lymph nodes in the posterior cervical and supraclavicular chains. Infection in these areas is thought to be due to contiguous spread from intrathoracic lymphatics or from infection in the tonsils and adenoids. Mediastinal lymph nodes are also commonly enlarged as a part of primary pulmonary disease (Fontanilla JM et al.,2011).

Cervical tuberculous lymphadenitis is characterized by progressive swelling of the affected nodes. In advanced cases, nodes may become inflamed and tender; the overlying skin may break down, resulting in a draining fistula.

cutAneouS tuBerculoSiS: Cutaneous tuberculosis (scrofuloderma) results from the direct extension of an underlying TB focus (eg, a regional lymph node, an infected bone or joint) to the overlying skin, forming ulcers and sinus tracts. Lupus vulgaris results from hematogenous or lymphogenous dissemination to the skin from an extracutaneous focus in a sensitized patient. Tuberculosis verrucosa cutis (prosector’s wart) occurs after exogenous direct inoculation of the mycobacteria into the skin of a previously sensitized patient who has moderate to high immunity against the bacilli. Rarely, TB develops on the abraded skin in patients with cavitary pulmonary TB (Fisher D, et al., 2013)

Fig. D: Diffuse Small Bowel Wall Thickening with Engorged Mesenteric Vessels (Arrow) in Crohn’s Disease. Minimal Smooth Peritoneal Thickening

and Enhancement (Arrow Head) also seen (Subhaschandra et al., 2016).

Fig. E: Cutaneous Tuberculosis (Verrucosa Cuits)

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lAryngeAl tuBerculoSiS: Laryngeal tuberculosis usually entails the development of masses, ulcers or nodules in the larynx and vocal cords, which are usually mistaken as laryngeal neoplasms. The most common clinical manifestation is dysphonia but it can also produce coughing, stridor, and hemoptysis. It is usually associated with concomitant pulmonary TB, and it is thus a highly bacilliferous and contagious form of the disease (Gonzalez et al. 2010).

tB of BoneS And JointS: Weight-bearing joints are most commonly involved, but bones of the wrist, hand, and elbow may also be affected, especially after injury (Tappeiner G et al., 1999). Pott disease is a spinal infection, which begins in a vertebral body and often spreads to adjacent vertebrae, with narrowing of the disk space between them. Untreated, the vertebrae may collapse, possibly impinging on the spinal cord. Symptoms include progressive or constant pain in involved bones and chronic or sub-acute arthritis (usually monoarticular). In Pott disease, spinal cord compression produces neurologic deficits, including paraplegia; para vertebral swelling may result from an abscess (Barbagallo J et al., 2002).

gAStrointeStinAl tB: Because the entire GI mucosa resists TB invasion, infection requires prolonged exposure and enormous inocula. It is very unusual in developed countries where bovine TB is rare. Ulcers of the mouth and oropharynx may develop from eating M. Bovis–contaminated dairy products; primary lesions may also occur in the small bowel. Intestinal invasion generally causes hyperplasia and inflammatory bowel syndrome with pain, diarrhea, obstruction, and hematochezia. It may also mimic appendicitis. Ulceration and fistulas are possible.

tB of the liver: Liver infection is common in patients with advanced pulmonary TB and widely disseminated or miliary TB. However, the liver generally heals without sequelae when the principal infection is treated. TB in the liver occasionally spreads to the gallbladder, leading to obstructive jaundice. A necrotizing granuloma is most frequently obtained from liver samples (90-100%) rather than bone marrow (31-82%) or transbronchial biopsy (63-72%) (Fisher D, et al., 2013).

other SiteS of tuBerculoSiS: TB may infect the wall of a blood vessel and has even ruptured the aorta. Adrenal involvement, leading to Addison disease, formerly was common but now is rare. Tubercle bacilli may spread to tendon sheaths (tuberculous tenosynovitis) by direct extension from adjacent lesions in bone or hematogenously from any infected organ.

diAgnoSiS: Acid-fast staining, microscopic analysis, and mycobacterial culture of fluid and tissue samples, and, when available, nucleic acid-based testing, Chest x-ray, Tuberculin skin testing (TST) or interferon-gamma release assay (IGRA).

Testing is similar to that for pulmonary TB (see Tuberculosis (TB): Diagnosis), including chest x-ray, TST or IGRA, and microscopic analysis (with appropriate staining) and mycobacterial cultures of affected body fluids (CSF, urine, or pleural, pericardial, or joint fluid) and tissue for mycobacteria. Nucleic acid-based testing can be done on fresh fluid or biopsy samples and on the fixed tissue (eg, if TB was not suspected during a surgical procedure and cultures were not done). Blood culture results are positive in about 50% of patients with disseminated TB; such patients are often immunocompromised, often by HIV infection. However, cultures and smears

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of body fluids and tissues are often negative because few organisms are present; in such cases, nucleic acid amplification tests (NAAT) may be helpful (Almagro M, et al., 2005).

● Typically, lymphocytosis is present in body fluids. A very suggestive finding in the CSF is a glucose level < 50% of that in serum and an elevated protein level.

● If all tests are negative and miliary TB is still a concern, biopsies of the bone marrow and the liver are done. If TB is highly suspected based on other features (eg, granuloma is seen on biopsy, positive TST or IGRA plus unexplained lymphocytosis in pleural fluid or CSF), treatment should usually proceed despite the inability to demonstrate TB organisms.

● Chest x-ray and other imaging, TST, and IGRA can also provide helpful diagnostic information.

● A chest x-ray may show signs of primary or active TB; in miliary TB, it shows thousands of 2- to 3-mm interstitial nodules evenly distributed through both lungs.

● Other imaging tests are done based on clinical findings. Abdominal or GU involvement usually requires CT or ultrasonography; renal lesions are often visible. Bone and joint involvement require CT or MRI; MRI is preferable for spinal disease.

● TST and IGRA may initially be negative, but a repeat test in a few weeks is likely to be positive. If it is not, the diagnosis of TB should be questioned or causes of anergy sought.

treAtmentS: Although TB most commonly affects the lungs, any organ or tissue can be involved. In countries with comprehensive diagnostic and reporting systems, extrapulmonary TB accounts for 20–25% of reported cases. Globally, extrapulmonary cases (without concurrent pulmonary involvement) comprised 14% of notified cases (new and relapse) in 2007 (NICE 2016) of specific forms of EPTB, lymphatic, pleural, and bone or joint disease is the most common, while pericardial, meningeal and disseminated (miliary) forms are more likely to result in a fatal outcome.

Many TB patients have concomitant illnesses. At the start of TB treatment, all patients should be asked about medicines they are currently taking. The most important interactions with anti-TB drugs are due to rifampicin. Rifampicin induces pathways that metabolize other drugs, thereby reducing the concentration and effect of those drugs. To maintain a therapeutic effect, dosages of the other drug(s) may need to be increased. When rifampicin is discontinued, its metabolism-inducing effect resolves within about 2 weeks, and dosages of the other drug(s) will need to be reduced (American Thoracic Society; CDC 2003). A treatment includes:

● Antibiotics

● For pericarditis and meningitis, sometimes corticosteroids

● Sometimes surgery

Drug treatment is the most important modality and follows standard regimens and principles (see Tuberculosis (TB): First-line drugs). Six to 9 months of therapy is probably adequate for most sites except the meninges, which require treatment for 9 to 12 months.

Corticosteroids may help in pericarditis and meningitis.

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Drug resistance is a major concern; it is increased by poor adherence, use of too few drugs, and inadequate susceptibility testing (Marco A at al., 2014).

Surgery is required for the following:

● To drain empyema, cardiac tamponade, or CNS abscess

● To close bronchopleural fistulas

● To resects infected bowel

● To decompress spinal cord encroachment

Surgical debridement is sometimes needed in Pott disease to correct spinal deformities or to relieve cord compression if there are neurologic deficits or pain persists; fixation of the vertebral column by bone graft is required in only the most advanced cases. Surgery is usually not necessary for TB lymphadenitis except for diagnostic purposes.

CONCLUSION

The incidence of extrapulmonary tuberculosis has been increasing substantially on a worldwide basis over the past decade, but no tuberculosis-specific drugs have been discovered in 75 years. The EPTB burden includes not only difficulties in implementing EPTB control programs in many countries but also the recent increase in the number of HIV-infected individuals. Although current first-line anti-TB drug regimens can achieve more than 99% efficacy, this is often reduced because of drug resistance. The present work of identifying the risk factors will support the considerable management aspect in extrapulmonary tuberculosis and socioeconomic use.

ACKNOWLEDGMENT

I thank Dr. Anuradha K. Professor and Head of the Department, Mysore Medical College and Research Institute, K R Hospital Mysuru–570001 for her intensive support to the work.

REFERENCES

[1] Fisher D, Elwood K. Non-respiratory tuberculosis. In: Canadian Thoracic Society, Canadian Lung Association, and the Public Health Agency of Canada, editors. Canadian Tuberculosis Standards. 7th Edition. Ottawa: Canadian Thoracic Society; 2013. Indian J Med Res 122, October 2005, Page No: 330–337

[2] Critchley J A, Young F, Orton L, Garner P. Corticosteroids for the prevention of mortality in people with tuberculosis: a systematic review and meta-analysis. Lancet Infect Dis. 2013; 13: 223-37.

[3] García Rodríguez JF, Álvarez Díaz H, Lorenzo García MV, Mariño Callejo A, Fernández Rial A, Sesma Sánchez P. Extrapulmonary tuberculosis: epidemiology and risk factors. Enferm Infecc Microbiol Clin. 2011; 29(7): 502–9.

[4] Peto HM, Pratt RH, Harrington TA, LoBue PA, Armastrong L. Epidemiology of extrapulmonary tuberculosis in the United States, 1993-2006. Clin infects Dis. 2009; 49: 1350–7.

[5] Reuter H, Burgess L, Van Vuuren W, Doubell A. Diagnosing tuberculous pericarditis. QJM. 2006; 99(12): 827–39.

[6] González Martín J, García García JM, Anibarro L, Vidal R, Esteban J, Blanquer R, et al. Documentode consenso sobre diagnóstico, tratamientoy prevención de la tuberculosis. Enferm Infecc Microbiol clin. 2010; 28(5): 297.e20

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[7] Espinosa-Gimeno A, Martínez-Sanz J, Asong-Engonga L. Rodríguez-Zapata M. Protocolo diagnóstico y terapéutico de las tuberculosis extrapulmonares. Medicine. 2014; 11(52): 3091-7.

[8] Thwaites G E, Van Toorn R, Johan Schoeman J. Tuberculous meningitis: more questions, still too few answer. Lancet Neurol. 2013; 12: 999-1010.

[9] Fontanilla JM, Barnes A, Fordham von Reyn C. Current diagnosis and Management of Peripherals tuberculous lymphadenitis. Clin Infect Dis. 2011; 53(6): 555-62.

[10] Tappeiner G, Wolff K. Tuberculosis and other mycobacterial infections. In: Fitzpatrick TB, Eisen AZ, Wolff K, editors. Dermatology in general medicine. 5th ed. New York: McGraw Hill; 1999. p. 2274-92.

[11] Barbagallo J, Tager P, Ingleton R, Hirsch RJ, Weinberg JM. Cutaneous tuberculosis: diagnosis and treatment. Am J Clin Dermatol. 2002; 3(5):319-28.

[12] Subhaschandra Singh, Y. Sobita Devi, Shweta Bhalothia and Veeraraghavan Gunasekaran (2016). “Peritoneal Carcinomatosis: Pictorial Review of Computed Tomography Findings”. International Journal of Advanced Research. 4 (7): 735–748.

[13] Almagro M, Del Pozo J, Rodríguez-Lozano J, Silva JG, Yebra-Pimentel MT, Fonseca E. Metastatic tuberculous abscesses in an immunocompetent patient. Clin Exp Dermatol. 2005; 30(3): 247-9.

[14] Marco A, Solé R, Raguer E, Aranda M. Goma o absceso tuberculoso metastásico como diagnostic inicial de tuberculosis en un paciente inmunocompetente: una presentación inusual. Rev Esp Sanid Penit. 2014; 16: 59-62

[15] National Collaborating Centre for Chronic Conditions. Tuberculosis: clinical diagnosis and management of tuberculosis, and measures for its prevention and control. London: Royal College of Physicians, NICE (National Institute for Health and Clinical Excellence); 2006.

[16] American Thoracic Society; CDC; Infectious Diseases Society of America. Treatment of tuberculosis. Morbidity and Mortality Weekly Report: Recommendations and Reports. 2003; 52(RR-11):1–77.

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Screening of Rhizobacteria from Tomato Crop to Control Bacterial Wilt Pathogen:A Research-Based on Antibiosis

Akash Mishra*, Shraddha P. Mishra, Anfal Arshi, Merwyn S. and Madhu Bala

Defence Institute of Bio-Energy Research (DIBER), Defence Research and Development Organization (DRDO),

Ministry of Defence, Government of India, Haldwani, Uttarakhand (UK), India–263139

E-mail: *[email protected]

ABSTRACT

Bacterial wilt disease is one of the most destructive diseases caused by Ralstonia solanacearumthat affects more than 450 plant crops from 54 families including Solanaceae. Tomato and another related crop such as capsicum, potato, eggplant, and chilli are the most affected among all economically important crops. Therefore, the phytopathogen requires utmost attention in its control. However, no effective, as well as eco-friendly method, is available for the management of such disease. In the present study, the property of Plant growth Promoting Rhizobacteria (PGPR) to provide the first line of defence through induction of systemic resistance and serving as Biocontrol agent, have been considered for eco-friendly management of bacterial wilt disease. A Rhizobacterial species from Genus “Serratia” was isolated from tomato rhizosphere and screened for biocontrol potential (on the basis of Antagonism) against 5 strains of Ralstonia solanacearum by Agar well diffusion method. The isolate showed the potential of antagonism for almost all the strains of test pathogen and maximum measured zone of growth inhibition was 33mm in diameter. The isolate was further characterized and identified as a representative of family Enterobacteriaceae and Genus Serratia. Therefore, Present study shows the biocontrol potential of isolated Serratia sp. against phytopathogenRalstoniasolanacearum.However, the efficacy of the isolate has to be evaluated in field conditions to be used as a Biocontrol control agent for bacterial wilt disease management.

Keywords: Tomato, Rhizobacteria, Antibiosis, Bacterial Wilt, Serratia

INTRODUCTION

The zone of rhizosphere is a region of plant root system where the soil components are in much closer proximity with and has a direct influence on the living roots of the plant. This region has a maximum microbial activity as it serves as a hotspot for interaction between plant, soil, and microorganisms. The bacterial population living in the rhizosphere are called as the Rhizobacteria, which has a crucial role in neutral, beneficial and detrimental effect on plant growth by direct and indirect mechanisms, and therefore are known as Plant Growth Promoting Rhizobacteria (PGPR) (Juanda 2005). The direct mechanism of PGPR in plant growth is achieved by synthesis of various growth hormones essential for plants, fixation of atmospheric

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nitrogen, Siderophore production and solubilisation of minerals (Nelson 2004), whereas Indirect mechanism includes biocontrol of phytopathogens and other harmful microorganisms by the production of antibiotics, siderophore, lytic enzymes, hydrogen cyanide and/or due to competition for space and nutrient (Khan 2006). A number of bacterial species belonging to different genera have been considered as the PGPR, in which Bacillus, Pseudomonas, Serratia, Rhizobium, Agrobacterium, etc., (Kurabachew and Wydra 2013) are the major groups that have an important contribution in biocontrol of plant diseases, especially for tomato crop.

Bacterial wilt disease is one of the most destructive diseases caused by Ralstonia solanacearum (Yabuuchi et al. 1995)that affects more than 450 plant crops from 54 families including Solanaceae (Wicker et al. 2007). Tomato and another related crop such as capsicum, potato, eggplant, and chilli are the most affected (Denny 2006) among all economically important crops. Therefore, the phytopathogen requires utmost attention in its control. However, no effective, as well as eco-friendly methods, are available for the management of such disease. Meanwhile, the substantial property of PGPR to serve as a biocontrol agent and providing the first line of defence through the induction of systemic resistance (Mazzola 1998) is the solution to this problem.

Therefore, the present study has been conducted with an objective to isolate and screen out the rhizobacteria form tomato crop having the potential of biocontrol for various strains of Ralstonia solanacearum that causes bacterial wilt disease.

MATERIALS AND METHODS

iSolAtion of rhizoBActeriA And pure culture prepArAtion

Rhizospheric Soil from tomato crop plant was taken as a sample for the isolation of bacteria. 1 gram of soil from the sample was serially diluted up to 10th dilution as per standard microbiological methods for bacterial isolation. An amount of serially diluted sample from each dilution was transferred to sterile nutrient agar media plates and spread over with the help of sterile L-shaped spreader. Prepared plates were then allowed for the incubation at 30ºC for 24-48 hrs. After incubation, distinct bacterial colonies were observed, examined carefully and a loop full culture from each colony was transferred to a new media plates for preparation of pure culture, for which, Loop full culture was streaked over the media surface following the method of quadrate streaking and then inoculated plate was incubated at 30ºC for 24-48 hrs for development of colonies.

Screening of rhizoBActeriAl iSolAteS for AntAgoniSm potentiAl AgAinSt BActeriAl Wilt pAthogen

A pure culture of bacterial isolates with given code (AM 1–AM 5) was screened for their potential of antagonism against Ralstonia solanacearum strains DIBER- G1c2a, DIBER-G1b2b, DIBER-G1c1a, DIBER-G1b2a, DIBER-G1c2b (accession no. not provided) using Agar well diffusion method. Pathogenic strains were grown in 5 ml nutrient broth (NB) were swabbed onto the King’SB medium. A well was created in each test plate with the help of cork borer and filled with 100µl of the overnight grown culture of respective Rhizobacterial isolates in NB. Another well in each plate was created and filled with sterile NB which served as negative control. Plates

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were then incubated at 28ºC for 24-48 hrs. During incubation, a clear zone was formed around the wells for many of test pathogens indicating inhibition of growth. The formed zone was then examined and measured through “HI media antibiosis scale” specially designed to measure zone of growth inhibition in antibiosis test.

morphologicAl And BiochemicAl chArActerizAtion of iSolAte for itS identificAtion

Bacterial isolate showing antagonism potential was then characterized by standard microbiological tests. Several tests were performed for their identification such as examination of colony morphology (including size, shape, texture, appearance etc.) Gram’s staining, as well as motility test and capsule staining.

Metabolic activities of isolates were also determined with the help of various biochemical tests routinely used in microbiology for identification of an unknown bacteria. The tests employed for this purpose were Citrate Utilization, Indole, Urease and catalase production, Reduction of nitrate and Triple sugar Iron test.

Results from all the tests performed, were recorded and processed for identification of bacterial isolates with the help of “Bergey’s Manual of Systematic Bacteriology, volume 1” (Holt and Noel 1984) and “Identification Flow Charts Bergey’s Manual of Determinative Bacteriology”.

RESULTS AND DISCUSSION

iSolAtion of rhizoBActeriA And pure culture prepArAtion

During isolation of rhizobacteria from tomato crop, 5 different colonies were observed in the collected sample. All the colonies were morphologically diverse in terms of size, shape, texture, appearance etc.. Bacterial colonies were allotted a code individually as AM 1, AM 2, AM 3, AM 4, and AM 5.

Screening of rhizoBActeriAl iSolAteS for AntAgoniSm potentiAl AgAinSt BActeriAl Wilt pAthogen

Agar well diffusion method for antibiosis test showed the potential of bacterial isolates to control pathogenic strains of Ralstonia solanacearum. Among all the bacterial isolates, AM 3 inhibited almost all the test strains (Table 2). The maximum zone of growth inhibition was 33 mm in diameter. All other isolates also showed some inhibition of growth in few of test strains but the potential of them was very weak as the zones formed were cloudy in appearance.

morphologicAl And BiochemicAl chArActerizAtion of iSolAte for itS identificAtion

Bacterial isolate having the potential of antagonism showed a typical red colored colony on Nutrient agar media. The size of The colony was small (1-2 mm), with round shape and entire margin, convex and slightly raised at the center. It showed smooth texture and opaque appearance (Table 1). The cells were stained with Gram’s stain that showed slightly pink colored

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straight rod under a compound microscope. Motility test result reveals that the bacterium was motile and no capsule was present outside the cell when observed in capsule staining.

Metabolic activity of the bacterium was checked with different biochemical tests which showed that the isolate was oxidase negative but strongly positive for catalase and urease production. It did not produce indole but utilized citrate during growth (Table 3). The isolated bacteria metabolized glucose and produced acetoin as indicated in the MR-VP test. Nitrate was converted into nitrite which is the indication of its anaerobic metabolism. No acid or gas was produced in Triple sugar iron test.

All observations and the recorded result were compared with “Bergey’s Manual of Systematic Bacteriology, volume 1”(Holt 1984) which indicates that the bacterium secures its place for family Enterobacteriaceae. For further identification of its Genus, “Identification Flow Charts Bergey’s Manual of determinative bacteriology” was accessed that identifies this bacterium as a species of “Genus Serratia” as motility feature and typical red colored colony along with negative result for oxidase production is the main characteristic of Genus Serratia in family Enterobacteriaceae.

Table 1: Morphological Characteristics of Bacterial Isolates

Morphological Characterisation

IsolateColony Morphology

Gram Staining

Capsule Staining

Motility testShpae Size Margine Elevation Optical

Property Pigmentation

AM 3 Round Small Entire Umbonate Opaque Red pigmented Gram-ve -ve +ve

-ve: Negative; +ve: Positive

Table 2: Antibiosis Test Results Showing Antagonism Potential of The Isolate

Antibiosis Test (zone of growth inhibition)

IsolateRalstonia solanacearum strains

DIBER- G1c2a DIBER-G1b2b DIBER-G1c1a DIBER-G1b2a DIBER-G1c2b

AM 3 33 mm 26 mm 26 mm 25 mm

mm: millimeter;; All the values for the size of the zone of growth inhibition are for diameter in millimeter

Table 3: Biochemical Characteristics of Bacterial Isolates

Biochemical Characterisation

Isolate Oxidase test

Catalase test

MR-V-P test

Indole Production test

Citrate utilization test

Urease production test

Triple sugar iron test

Nitrate Reduction

Sucrose Test

AM 3 -ve +ve +ve -ve +ve +ve -ve +ve +ve

Foot Note: MR: Methyl Red; V-P: Voges-Proskauer; -ve: Negative; +ve: Positive;

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CONCLUSION

In the present study, bacteria residing in the surroundings of tomato crop root (Rhizosphere zone) were isolated and screened for antibiosis against different strains of Ralstonia solanacearum that causes bacterial wilt disease in a number of plant species from family Solanaceae, including tomato crop. The isolate which showed antagonism potential for many of test pathogen, was further characterized with the help of morphological and biochemical characteristics followed by its identification through “Bergey’s manual of Systematic Bacteriology, volume 1” (Holt and Noel 1984) and “Identification flow charts Bergey’s Manual of Determinative Bacteriology”. The isolated bacterium is a species of family “Enterobacteriaceae and Genus Serratia”.A typical red coloured pigmentation in bacterial colony is the characteristic of this genus which really helped in its easy identification. However, for identification for the name of species and efficacy of antagonism potential, molecular techniques and In-vivo study is further required respectively.

ACKNOWLEDGMENTS

Authors are extremely thankful to The Director, Defence Institute of Bio-Energy Research for providing all the facility to conduct this Research.

referenceS

[1] Denny, T.P., 2006.Plant pathogenic Ralstonia species. In: Gnanamanickam, S.S. (Ed.), Plant-Associated Bacteria. Springer Publishing, Dordrecht, The Netherlands, pp.573–644.

[2] Holt, J. G. (editor-in-chief) and Noel R. Krieg (editor, volume 1). (1984). Bergey’s Manual of Systematic Bacteriology, Volume 1. New York: Lippincott Williams & Wilkins.

[3] Juanda, J.I. H. 2005. Screening of soil bacteria for PlantGrowth Promoting Activities in Vitro. J. Agri. Sci. 4:27-31

[4] Khan, M. S. 2006. Screening of free-living rhizospheric bacteria for their multiple plant growth promoting activities.163:173-181.

[5] Kurabachew H., Wydra K. 2013.Characterization of plant growth promoting rhizobacteria and their potential as bioprotectant against tomato bacterial wilt caused by Ralstonia solanacearum. Biological Control 67:75–83

[6] Mazzola, M., 1998.The potential of natural and genetically engineered fluorescentPseudomonasspp.As biological control agent. In: Subba, R.N.S., Domesgyer, Y.R. (Eds.), Microbial Interaction in Agriculture and Forestry. Science publishers. Inc., USA, pp. 192 217.

[7] Nelson, L. M. 2004. Plant growth promoting rhizobacteria(PGPR): Prospect for new inoculants. Online.CropManagementdoi: 10. 1094/CM-2004-0301-05-RV.

[8] Wicker, E., Grassart, L., CoransonBeaudu, R., Mian, D., Guilbaud, C., Fegan, M., 2007. Ralstonia solanacearum strains from Martinique (French West Indies) Exhibiting a New Pathogenic Potential. Appl. Environ. Microbiol. 71, 6790–6801.

[9] Yabuuchi, E., Kosako, Y., Yano, I., Hotta, H., Nishiuchi, Y., 1995. Transfer of twoBurkholderia and an Alcaligenes species to Ralstonia gen. Nov.: Proposal of Ralstoniapic kettii (Ralston, Palleroni and Doudoroff1973) comb. Nov., Ralstonia solanacearum (Smith 1896) comb.Nov. and Ralstonia eutropha (Davis 1969) comb. Nov. Microbiol. Immunol. 39, 897–904.

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Frontline Demonstrations: An Effective Tool for Transfer of Wheat (Wh-1105) Production Technology in Hanumangarh District of Rajasthan

Akshaya Ghintala*, Bheiru Singh, Mukesh Kumar Verma and Manohar Lal Sain

Krishi Vigyan Kendra, Nohar, Hanumangarh-II (Raj.), India.


ABSTRACT

The frontline demonstrations were conducted by Krishi Vigyan Kendra from Rabi 2016-17 in the area of 4.0 hectare on 10 locations (farmers). Total 10 demonstrations were selected. The data collected from the reports of frontline demonstrations conducted by the Krishi Vigyan Kendra on the production technology of wheat crop were used. Production and economic data for frontline demonstrations and local practice were collected and analyzed. The results of the study showed that the average grain yield of wheat under demonstration plots was recorded 4,170 kg per ha when compared to local check 3,520 kg per ha. The percentage increase in the yield over local check was 18.47 %during the course of study. Technology gap and technology index values were 1,080 kg per hectare and 20.57 %, respectively. It is concluded that a wide gap existed in potential and demonstration yield in high yield wheat varieties due to technology and extension gap in Hanumangarh district of Rajasthan.

Keyword: FLDs, Technology Gap, Index, Wheat; & Production Technology

INTRODUCTION

Wheat (Triticum aestivam L.) is the world’s most widely cultivated food crop. It is eaten in various forms by more than one thousand million human beings in the world (Iftikhar et. al., 2002). Besides staple food for human beings, wheat straw also serves an as a good source of feed for animals (Sarwar et al., 2006). In India, wheat production was recorded as 95.91 million tonnes (mt) from an area of 30 m ha in 2013-14 (GoI, 2014). It supplies 21 percent of the per capita food energy and 18 percent of dietary protein in the country (Balasubramanian et. al., 2012).

Wheat is grown in all the states in India except Southern and North Eastern states. Uttar Pradesh, Haryana, Punjab, Rajasthan are the major wheat producing states and accounts for almost 80% of total production in India. Only 13% area is rain-fed. Major Rainfed wheat areas are in Madhya Pradesh, Gujarat, Maharashtra, West Bengal, and Karnataka. Central and Peninsular Zone accounts for total 1/3rd of wheat area in India. All India basis only 1/3 irrigated wheat receives desired irrigations and remaining is limited irrigation only. Breeding programmes are generally aimed for rain-fed and irrigated environments and there is a need to develop varieties which are responsive to limited irrigation conditions.

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The frontline demonstration may play a very important role in the proper transfer of technologies and changing the scientific temperament of the farmers. The frontline demonstration is the new concept of field demonstration evolved by the ICAR with the inception of the technology mission on oilseed crops during mid-eighties. The main objective of frontline demonstrations is to demonstrate newly released crop production and protection technologies and its management practices in the farmers filed under different agro-climatic regions and farming situations. Frontline demonstrations are conducted in a block of two or four-hectare land in order to have a better impact on the demonstrated technologies on the farmers and field level extension functionaries. The agricultural technology is not generally accepted by the farmers completely in all respects.

As such there always appears to be a gap between the recommended technology by the scientist and it’s modified from at the farmer’s level. The technology gap is thus the major problem in the efforts of increasing agricultural production in the country. A need of the day is to reduce the technological gap between the agricultural technology recommended by the scientist and its acceptance by the farmers on their field. In view of the above factors, frontline demonstrations were undertaken in a systematic manner on farmer’s field to show the worth of a new variety and convince the farmers to adopt improved cultivation practices of wheat for increasing productivity of wheat. Keeping in view the present investigation attempts to study the yield gap between frontline demonstration trails and farmers yield, extend of technology adoption and benefit-cost ratio.

RESEARCH METHODOLOGY

The study was carried out by Krishi Vigyan Kendra, Nohar, Hanumangarh-II (Rajasthan) during rabi 2016-17at farmer’s field. The data on the output of high yield variety of wheat crop and inputs used per hectare have been collected from the frontline demonstration trails conducted. All the participating farmers were trained on various aspects of wheat production technologies. Recommended agronomic practices and genuine seeds of wheat were used for frontline demonstrations in 0.4-hectare area per demonstration. A one-fifth area was also devoted to growing local standard check. The frontline demonstrations were conducted by Krishi Vigyan Kendra from Rabi 2016-17in area of 4.0 hectare on 10 locations (farmers). Thus, a total of 10 full package frontline demonstrations were selected. The data collected from the reports of frontline demonstrations conducted by the Krishi Vigyan Kendra on the production technology of wheat crop were used. These were compared with prevailing production technologies of wheat crop (which were taken in check plots). The performances of improved varieties with improved technologies evaluated closely by the organizing seasonal training, method of demonstrations, field days and by taking crop-cut experiments. Regular diagnostic visit by the scientists helped in the proper execution of demonstration as well as a collection of farmer’s opinion about the demonstration field. Production and economic data for frontline demonstrations and local practice were collected and analyzed.

In the present study, the technology index was operationally defined as the technical feasibility obtained due to the implementation of frontline demonstration in wheat. To estimate the technology gap, the extension gap, and technology index following formulae used by Samuel et al. (2000) have been used:

Extension Gap (kg per ha)=Demonstration yield - Farmer practices yield (Local check)

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Technology Gap (kg per ha) = Potential yield – Demonstration yield

TechnologyIndex = Potential yield – Demonstration yield/Potential yield X 100


performAnce of frontline demonStrAtion

A perusal of data indicated that the yield of wheat increased progressively over the years of study in demonstration plots as well as in control plots (Table-1).

Table 1: Productivity of Wheat Crop Under Demonstration and Farmer Practice

Year Name of varietyAverage yield (Kg/ha) % increase in

over the yieldDemonstration plot Farmer practice

2016-17 WH-1105 4,170 3,520 18.47

The results of average grain yield of wheat under demonstration plots were recorded4,170 kg per ha when compared to local check 3,520 kg per ha. The percentage increase in the yield over local check was 18.47%. More and less similar yield enhancement in different crops in frontline demonstration has amply been documented by Hirenmath et al. (2007), Patel et al. (2013)and Ghintala et al. (2018). From these results, it is evident that the performance of improved variety was found better than the local check under same environment conditions. Farmers were motivated by results of agro-technologies applied in the frontline demonstrations trails and it is expected that they would adopt these technologies in the coming years. The yield of the frontline demonstration trails and potential yield of the crop was compared to estimate the yield gaps which were further categorized into technology index.

extenSion gAp

The Extension gap shows (Table-2) the gap in the demonstration yield over farmer practices yield and it was 650 kg per ha. These findings are similar to the findings of Patel et al. (2013) and Ghintala et al. (2018).

technology gAp

The technology gap shows the gap in the demonstration yield over potential yield and it was 1080 kg per ha (Table-2). The frontline demonstrations were laid down under the supervision of scientists at the farmer’s field. There exists a gap between the potential yield and demonstration yield. This may be due to the weather conditions. Hence, location-specific recommendations are necessary to bridge the gap. These findings are similar to the findings of Ghintala et al. (2018).

technology index

Technology Index shows the feasibility of the variety at the farmer’s field. The lower the value of the technology index more is the feasibility. Results of the study depicted in Table-2 revealed

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that the technology index value was 20.57%. The results of the present study are in consonance with the findings of Singh et al. (2007) and Ghintala et al. (2018).

Table 2: Yield, Technology Gap, Technology Index and Extension Gap of Wheat Grown Under Demonstration and Local Check

Variables Yield (Kg/ha)

% Increase over local check

Extension Gap (Kg/ha)

Technology Gap (Kg/ha)

Technology Index (%)

Local check 3520 - - - -

Demonstration (WH-1105) 4170 18.47 650 1080 20.57

Potential yield: 5250 (Kg per ha)

economic of frontline dSemonStrAtion

The economics of wheat production under frontline demonstrations were estimated and the results of the study have been presented in Table-3.

Table 3: Economic Analysis of Demonstration Plot and Farmer Practice

VariablesAverage yield (Rs./ha.)

Gross Cost Gross Return Net Return B:C Ratio

Farmer plot 18000 57200 39200 3.18

Demonstration plot 18750 67762.50 49012.50 3.61

The results of the economic analysis of wheat production revealed that frontline demonstrations recorded the highest gross return of wheat under demonstration plots was Rs. 67,762.50 per ha and net return Rs. 49,012.50 per ha with the highest benefit-cost ratio(3.61) as compared to local checks. These results are in accordance with the finding of Hirenmath and Nagaraju (2009) and Ghintala et al. (2018). Further, the additional cost of Rs.750per ha in demonstration has increased additional net returns Rs.9,812.50per ha with an incremental benefit-cost ratio 13.08 suggesting it’s higher profitability and economic viability of the demonstration. More and less similar results were also reported by Dhaka et al. (2010), Patel et al. (2013) and Ghintala et al. (2018).

CONCLUSIONS

The results of the study showed that the average grain yield of wheat under demonstration plots was 4,170 kg per ha when compared to local check 3,520 kg per ha. The percentage increase in the yield over local check was 18.47% during the course of study. Technology gap and technology index values were 1080 kg per hectare and 20.57%, respectively.

The finding of the study revealed that a wide gap existed in potential and demonstration yield in high yield wheat varieties due to technology and extension gap in Hanumangarh district

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of Rajasthan. By conducting frontline demonstration was an effective tool for increasing the productivity of the wheat crop. Improved technologies in frontline demonstrations enhanced yield and increase percent over the farmer’s practice in local check plots. This will substantially increase the income as well as the livelihood of the farming community. This created greater curiosity and motivation among other farmers who do not adopt improved practices of wheat cultivation.

The demonstrations also built the relationship and confidence between farmers and scientist of Krishi Vigyan Kendra. The study emphasizes the needs to educate the farmers in the adoption of improved technology to narrow the extension gaps through various technology transfer centers. Therefore it is suggested that these factors may be taken for considered to increase the scientific temperament of the farmers.

REFERENCES

[1] Anonymous, (2016-17). Annual Progress Report, Krishi Vigyan Kendra, Nohar, Hanumangarh-II.[2] Anonymous (2014). Agricultural statistics at a glance. Ministry of Agriculture, Department of

Agriculture and cooperation, Directorate of Economics and Statistics, Government of India, pp. 68-69.

[3] Balasubramanian, V.; Adhya, T. K. and Ladha, J. K. (2012.) Enhancing eco-efficiency in the intensive cereal-based systems of the Indo-Gangetic Plains. Issues in Tropical Agriculture Eco efficiency From Vision to Reality. CIAT Publication, Cali, CO.

[4] Dhaka, B.L.; Meena, B. S. and Suwalka, R. L. (2010). Popularization of Improved Maize production technology through frontline demonstrations in south-eastern Rajasthan.Journal of Agri. Sci., 1(1):39-42.

[5] Ghintala, A.; Singh, B.; Verma, M.K. and Lal, M. (2018). Performance of Front Line Demonstration on the Yield of Wheat in Hanumangarh District of Rajasthan, India. Int. J. Curr. Microbiol. App. Sci. 7(09): 3477-3482.

[6] Hiremath, S. M. and Nagaraju, M. V. (2009). Evaluation of frontline demonstration trails on onion in Haveri district of Karnataka. Karnataka j. of agric. Sci., 22(5): 1092-1093.

[7] Hiremath, S. M.; Nagaraju, M. V. and Shashidhar, K. K. (2007). Impact of frontline demonstration on onion productivity in farmers field. Nation.Sem. Appropriate Extn.Strat.Manag.Rural Resources, Univ. agric. Sci. Dharward. December 18-20:100.

[8] Iftikhar, M.H.; Shamshad, H. S.; Hussain, S. and Iqbal, K. (2002). Growth, yield and quality response of three wheat (Triticum aestivum L.) varieties to different levels of N, P and K. International journal of Agricultural biology. 4: 362-364.

[9] Patel, M.M.; Jhajharia, A. K.; Khadda, B. S. and Patil, L. M. (2013). Frontline demonstration: An effective communication approach for dissemination of sustainable cotton production technology. Ind. J. Extn. Edu. & R.D., 21: 60-62.

[10] Samuel, S. K.; Miha, S.; Roy, D. K.; Mandal, A. K. and Saha, D. (2000).“Evaluation of Frontline demonstration on groundnut”.Journal of Indian Society Coastal Agril. Res., 18: 180-183.

[11] Sarwar, N.; Maqsood, M.; Mubeen, K.; Shehzad, M.; Bhullar, M. S.; Qamar, R., and Akbar, N. (2006). “Effect of different levels of irrigation on yield and yield components of wheat cultivars”. Pakistan Journal of Agricultural Science. 47: 371-734.

[12] Sharma, R. N. and Sharma, K. C. (2004). “Evaluation of frontline demonstration trails on oilseeds in Baran district of Rajasthan”. Madhya Pradesh Journal of Extn.Edu.,7: 94-95.

[13] Singh, D. K.; Gautam, U. S. and Singh R. K. (2007). “Study on yield gap and level of demonstrated crop production technology in Sagar district”. Ind. Res. J. Extn. Edu.,7(2&3): 94-95.

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Isolation and Identification of A Cholesterol Oxidase Producing Strain

Amreen Khan* and C.K.M. TripathiInstitute of Biosciences and Technology,

Shri Ram Swaroop Memorial University, Lucknow Deva Road, Barabanki


INTRODUCTION

The enzyme Cholesterol oxidase (COD) (cholesterol: oxygen oxidoreductase, EC1.1.3.6) catalyzes the oxidation of cholesterol to 4-cholesten-3-one in the presence of O [1]. COD has wide applications inclinical, pharmaceuticals, food and agricultural industries which has considerably increased the demand of this enzyme. Various microorganisms are reported to produce COD with specific properties. Cholesterol oxidases are used to determine cholesterol concentration in food and blood serum by coupling of the enzyme with peroxidase [2,3] in the production of precursors for chemical synthesis of steroid hormones, degradation of dietary cholesterol in foods [4] and as biological control agent[5].

COD is a monomeric bi-functional flavin adenine dinucleotide (FAD) containing an enzyme which belongs to the oxido reductases family and acts on the CH-OH group of donor with oxygen as an acceptor. COD catalyzes the oxidation of 3b-hydroxy steroids and the isomerization of Δ5-6-ene-3 β-ketosteroid (cholest-5-en-3-one) to produce 3-4-ene-3 β-ketosteroid (cholest- 4- en-3-one) (Figure 1)

Fig. 1: Breakdown of Cholesterol with the Help of Cholesterol Oxidase

SOURCES OF CHOLESTEROL OXIDASE

Cholesterol oxidase has been isolated and characterized from numerous microorganisms that are found in different environments (Figure 2). The first COD enzyme was isolated from Nocardia (later Rhodococcus) erythropolis and oxidant effect of cholesterol was explored [6]. Mycobacterium sp. and Streptomyces sp. are reported from soil for COD production. COD producing microorganisms have also been isolated from food stuffs like chicken fat, pork fat, butter and bacon eg. Rhodococcus strain [7]. COD has also been reported in many other

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microorganisms such as Arthrobacter sp. [8,9] Corynebacterium sp.[10] Nocardia erythropolis [11], Rhodococcus erythropolis [12,13], Mycobacterium sp.[14], Brevibacterium sterolicum, Streptoverticillium sp. [15], Streptomycesviolascens [16], Streptomyces sp. [17-19], and Enterobacter sp. [20].COD has also been isolated from some gram- negative bacteria such as Pseudomonas sp. [21], Chromobacteriumsp.[22]. COD from a eukaryotic microorganism Schizophyllum sp. (identified as basidiomycetes) has also been reported[23].

Table 2: Milestones of Discoveries Related to Cholesterol Oxidase Enzyme

Year Milestone Reference

1944–1967 Cholesterol and other sterols were oxidized by microorganism as their carbon source. [7]

1974 First cholesterol oxidase was isolated and crystallized from Brevibacterium sp.

[24]

1973 A method was developed to detect serum cholesterol level by cholesterol oxidase. [25]

1976 Cholesterol oxidase was found in Nocardia sp., Pseudomonas sp. and Rhodococcus sp. [26]

1989 Cholesterol oxidase was found in Streptomyces sp. [27]

1990 Immobilized cholesterol oxidase can be used as biosensor. [28]

1991 Cholesterol oxidase crystal structure was solved. [29]

1992 Membrane structure can be detected by using cholesterol oxidase as a probe. [30]

1993 Boll Weevil’s growth was inahibited by an enzyme which was reported as a cholesterol oxidase. [31]

1997 Cholesterol oxidase was discovered to be associated with the pathogenesis of Rhodococcus egtd. [32]

2005 Alzheimer disease beta-amyloid had similar mode of action as cholesterol oxidase. [33]

STRUCTURE OF CHOLESTEROL OXIDASE

There are two distinct types of COD that bind with FAD cofactor in two different ways: non- covalently and covalently. They also differ in terms of structure, folding, kinetic and thermodynamic properties. Two types of cholesterol oxidases are reported.

clASS-i choleSterol oxidASe

The class-I COD enzyme contains the FAD redox cofactor which is non-covalently bound to the enzyme.Itbelongstotheglucose-methanol- choline (GMC) oxidoreductase family and has been found mostly in actinomycetes such as Streptomyces sp. The structural and mutational analysis of Streptomyces sp. (class-I enzyme) has revealed that His447 and Glu361 residues are implicated in the activity for the oxidation and isomerization steps[34] and reported a comparison of amino acid sequences from class-I enzymes eg. Streptomyces sp., Rhodococcus sp. and Mycobacterium sp. These sequences contain a consensus sequence for FAD binding, Gly-X- Gly-X-X-Gly, in the N-terminal region of the COD[35].

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The class-I enzyme possesses the characteristic nucleotide-binding fold (Rossmann fold) consisting of a β-pleated sheet sandwiched between -helices and the motif needed for binding the cofactor. The diphosphate group of the cofactor is positioned closely to the N terminus of the first helix of the prote in where the conserved GXGXG glycine residues are located[29].

clASS-ii choleSterol oxidASe

In the class-II enzyme, the FAD cofactor covalently linked to the enzyme [36]. The class-II enzyme belongs to the (VAO) vanillyl-alcohol- oxidase family. This enzyme has been found in Brevibacterium sterolicum, Rhodococcus erythropolisandgram-negativebacteriasuchas Burkholderia sp., Chromobacterium sp. and Pseudomonas aeruginosa showing similarity (43% to 99%) to one another. The structure of COD (class-II enzyme) from the Brevibacterium sterolicum has been determined by X-ray crystallography and refined to high resolution. The structure suggested that the FAD was covalently bound to an active-site histidine (His121) via the C8group of the flavin isoalloxazine ring. This covalent bond is implicated in the redox potential and contributes to the stability of the enzyme[37].

In addition, Glu475 and Arg477, located at the active-site cavity, were suggested to constitute gate functioning in the control of oxygen access. In the covalent form of the enzyme, the diphosphate moiety is localized in the residues found between the third and fourth b-strands of a four-stranded β-pleated sheet.

COD has been known in a number of microorganisms and these flavoenzymes exhibit different sequences that suggest structural differences between the proteins. The comparison of sequence alignments is performed using CLUSTALW2 (http://www.expasy.ch.) for different types of CODs. Amino acids sequences are obtained using the protein search algorithm at The National Centre for Biotechnology Information (NCBI) [38]

SOIL SCREENING FOR ISOLATION OF NEW CHOLESTEROL OXIDASE PRODUCING MICROBIAL STRAIN

primAry Screening for choleSterol oxidASe producing microorgAniSmS

Soil samples collected from basin of Gomti river (Lucknow, 26°50’27”N, 80°56’48”E) and from the Himalayan Mountain region (Shimla, 31°37′N 77°06′E) were screened for potential cholesterol oxidase producing microorganisms. One gram of the soil sample was suspended in 10 ml of normal saline (NaCl, 0.85%) and vortexes vigorously for 2 min. The soil particles were allowed to settle and 1 ml of the supernatant was taken and serially diluted. The diluted samples were spread cholesterol enrichment medium plates containing (g/l) glucose, 20; yeast extract, 10; KH2PO4,0.05; KNO3, 1; MgSO4, 0.5; FeSO4, 0.01; NaCl, 0.5; cholesterol, 1 (dissolved in 0.5% Triton X-100); agar 15 and incubated at 30°C for 7 days. Colonies that formed halos were isolated by repeated single-colony isolation on the same medium. The colonies appearing on the incubated plates were subjected to secondary screening.

SecondAry Screening for choleSterol oxidASe producing microorgAniSmS cod indicAtor plAte ASSAy

The microorganisms isolated from the primary screening plates were sub cultured on cholesterol oxidase indicator plates (Cholesterol 0.1%, Triton X-100 0.1%, O-Dianisidine

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0.01%, Horseradish Peroxides 1 U/ml, Agar 1.5%) and further incubated for 7 days at 30°C. Cholesterol oxidase converts cholesterol into 4-cholesten-3-one and hydrogen peroxide. O-Dianisidine of the medium reacts with hydrogen peroxide (H2O2) to form azo compound (schiff’s base) which turns the color of medium into intense brown color. Colony showing intense brown color in surrounding was picked up as COD producer and used for further study.

moleculAr identificAtion of the iSolAteS

The bacterial isolate was characterized by 16S rRNA homology studies also Genetic relatedness provides more accurate identification of the strains as compared with the traditional phenotypic characterization methods . Genes coding for rRNA are highly conserved and their sequence analysis is used for inferring the evolution of taxa through billions of years has reported rRNA as the ultimate molecular chronometers to establish the phylogenetic relationship of microorganisms. Partial PCR amplification of bacterial rRNA gene by oligonucleotides primers complementary to the conserved regions resulted in 1368 bp PCR products. Gene sequencing and homology of the bacterial rRNA gene product revealed 99.7% homology with Streptomyces sp

RESULT

Fig. 2: Showing Growth and COD Production Kinetics of Strain R6

Fig. 3: Affinity Column Purification of COD and A Represent Active Fraction Eluted with Triton X100 Mixed Buffer

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Fig. 4: Isolated

Fig. 5: Cholesterol Oxidase Indicator Plate for Secondary Screening of K1

ApplicAtionS of choleSterol oxidASeS

COD of microbial origin are the enzymes of great interest in the present era. COD is widely used in clinical diagnosis and determining lipid disorders. It is used as an insecticide also[59]and plays a role in lysis of macrophages and leukocytes as well. The important applications of COD have been discussed below under separate categories.

clinicAl ApplicAtionS

COD is useful for the clinical determination of cholesterol levels in foods, serum (HDL and LDL) for the assessment of atherosclerotic diseases and other lipid disorders as well as the risk of thrombosis [60]. Analysis of serum cholesterol is generally accomplished by using a three-enzyme assay [2,25]. Because most of the cholesterol present in serum samples is esterified, the incubation of serum with cholesterol esterase (EC 3.1.1.13) is necessary to release free cholesterol. After that peroxidase enzyme(EC1.11.1.7)subsequently catalyzes the oxidative coupling reaction with hydrogen peroxide, 4-aminoantipyrine, and phenol to form a red quinoneimine dye. This red dye is easy to measure by spectrophotometric determination. In recent years various electrochemical biosensors using the immobilized CODs have been reported for the determination of cholesterol in serum and food.

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inSecticidAl Activity

Bacterial COD has potent insecticidal activity against the cotton boll weevil (Anthonomus grandis). Purcell et al. [31] discovered a highly efficient protein that killed boll weevil (Anthonomusgrandis grandis Boheman) larvae from Streptomyces culture filtrates and identified the protein as cholesterol oxidase. The COD is involved in the lysis of the mid gut epithelial cells of the larvae. Cholesterol or the related sterol at the membrane of the boll weevil mid gut epithelium seemed to be accessible to the enzyme and it is oxidized by cholesterol oxidase causing lysis of the mid gut epithelial cells resulting in larval death. Purified COD was active against boll weevil larvae at a concentration (LC50 of 20.9 ìg/ml), which is comparable to the bioactivity of Bacillus thuringiensis proteins against other insectpests. Corbin et al. [5] studied that enzyme also which exhibits insecticidal activity against lepidopteran cotton insect pests, tobacco budworm (Heliothisvirescens), corn earworm (Helicoverpazea) and pink bollworm (Pectinophora gossypiella). Recently, it was reported that Chromobacterium subtsugae has insecticidal properties [61]. Cholesterol oxidase might be involved in this insecticidal activity because it was recently found that Chromobacterium strains produce cholesterol oxidase [22] and also shows insecticidal activity. Some insecticide proteins are vital for pest control strategies employing transgenic crops. Corbin et al.[5]expressed the Streptomyces COD gene in tobacco protoplasts and Cho et al. [62] also have succeeded in the expression of the COD gene in tobacco cells.

trAnSformAtion of SterolS And non-SteroidAl compoundS And production of Steroid hormoneS precurSorS

Bioconversion of non-water-soluble compounds has been hindered because of their low solubility in an aqueous medium. Sterols including cholesterol are insoluble compounds so various reaction systems with COD have been developed. COD has been used for the transformation of cholesterol to cholest-4-en-3- one in the presence of different organic solvents in reverse micelles system[63]and in supercritical carbon dioxide. COD has a broad range of substrate specificity and can be used for the bioconversion of a number of 3-hydroxyster- oids which can be used for the synthesis of steroid hormones and other pharmaceutical steroids in the presence of organic solvents and in aqueous medium containing modified cyclodextrin [64]. Also cholesterol oxidase can be used for the optical resolution of non-steroidal compounds allylic alcohols in the presence of organic solvents [50].A wide range of microorganisms can metabolize cholesterol and use it as a sole carbon and energy source [65]. Cholesterol degradation is achieved through a complex metabolic pathway involving many enzymatics tepsstarting with theoxidation of the 3′-hydroxylgroup by COD followed by the Oxidation of the17-alkylsidechainandthe steroid ring system and ultimately degrading the entire molecule to CO2 and H2O. A number of Mycobacterium strains treated with mutagens have been reported to accumulate sterol biodegradation intermediates such as 4- androstene-3, 17-dione and 1,4-androstadiene- 3, 17-dione[66].These intermediates may be used as precursors for the production of steroid drugs and hormones.

A potentiAl tArget for neW AntiBioticS

Some pathogenic bacteria which possess cholesterol oxidases are thought to contribute to their pathogenicity. Navas et al. [34] observed that the COD is a major membrane damaging factor of Rhodococcus equi which is a primary pathogen of horses and an opportunistic pathogen in

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humans. The disruption of the COD gene was associated with a loss of cooperative (CAMP-like) hemolysis with sphingomyelinase producing bacteria. However the gene disruption analysis of the choE gene in R. equi performed by another groups how ed no difference between the mutant and parent strain in cytotoxic activity for macrophages or in intra macrophage multiplication. Mycobacterium tuberculosis is also a principal bacterial pathogen of humans and has been found to possess cholesterol oxidase. [67] It has been shown that the choD mutant

M. tuberculosis was attenuated in peritoneal macrophages. The mice infection experiments confirmed the significance of choD in the pathogenesis of M. tuberculosis. Thus, there seem to be opposite effects of the genes disruption in R. equi and in M. tuberculosis. S. natalensis cholesterol oxidase (PimE) has been described as a key enzyme in the biosynthesis of the polyene macrolide pimaricin [68]. Pimaricin is a macrolide antifungal antibiotic widely used in the food industry. The antifungal activity of pimaricin is involved in its interaction with membrane sterols, causing the alternation of membrane structure and leading to the leakage of cellular materials. The pimE gene is located in the center of the pimari cinbiosynthetic cluster. The gene disruption completely blocked the pimaricin production, whereas gene complementation recovered the antibiotic production. The addition of purified PimE or commercial cholesterol oxidases to the gene disruptant culture triggered pimaricin

production. These results suggested that cholesterol oxidases could act as signaling proteins for polyene biosynthesis. These new findings might be important for improving the productivity of the polyene from S. natalensis.

StudieS on memBrAne Structure

Cholesterol is the main constituent of the eukaryotic cell membrane. Cholesterol is expected to promote and stabilize the local bi- layer bending which is supposed to take place during membrane fusion since the curvature stress is towards the negative side [69]. Many researchers have studied the role of cholesterol in membrane organization that has used COD as a probe [68]. COD has been used as a probe to investigate the interaction of cholesterol with phospholipids [70] and the eukaryotic cell membrane structure i.e., lipid rafts. Pollegioni et al. [49] demonstrated the inaccessibility of COD for the outer-membrane surface of human erythrocytes and virus. The lipid rafts are the domainsin which cholesterol and saturate dlipids present in the membrane, such as sphingolipids, promote the formation of a highly ordered membrane structure [71]. Lipid rafts participate in numerous cellular processes including signal transduction, protein and lipid sorting, cellular entry by toxins and viruses, and viral budding. Therefore, the investigation of the lipid raft is important with regard to the study of eukaryotic membrane function.

choleSterol oxidASeS BioSenSorS

Cholesterol detection is important for clinical investigation and food analysis. For cholesterol detection different electrochemical biosensors have been proposed. Cholesterol biosensors based on immobilized cholesterol esterase and cholesterol oxidase have been studied to determine the total cholesterol content in food stuff and electrochemical measurements are performed in the cholesterol analysis of food samples. Different types of methods to use COD as biosensors, such as screen-printed electrode [72] hydrogel membranes, polymeric membrane, self-assembled mono layers, composite sol-gel membrane, liquid crystal cubic phase matrices,

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and films prepared by the layer-by-layer technique have been developed. Generally, in the electrochemical biosensor, the detection was monitored on the basis consumption of oxygen and H2O2. Novel amperometric biosensors have been formed by immobilizing COD insolgel layer on CNT-Pt modified electrodes. This biosensor was successfully used for serum cholesterol determination.

A new electrochemical biosensor was introduced in 2010, for determination of cholesterol that combined with Fourier transformation continuous cycle voltmeter [FFTCCV] technique in a flow injection analysis [73].A surface plasmaresonance based biosensor for simple, label-free, highly selective and sensitive detection of cholesterol employing the flavoenzyme COD as a sensing element has been proposed by Gehlot et al. [74]. A novel amperometric cholesterol biosensor immobilized with COD one lectrochemically polymerized poly-pyrole-polyvinlyulphonate (PPy-PVS) film entrapped on platinum electrode was developed by[75].Commonly cholesterol biosensors have been used in biochemical analysis owing to their good selectivity, low cost, small size, fastresponse and long term stability. The cited literature based on cholesterol biosensors have been mainly focused on diagnosingdisorders [76].

Recently a novel COD biosensor has been fabricated by co-immobilizing three enzymes COD, cholesterol esterase and HRP on nanoporous gold network directly grown on titanium substrate [77]. This biosensor possessed a wide line arrange upto 300mg/dlinaphysical condition (pH 7.4) for very effective clinical determination of cholesterol. The microchip capillary electrophoresis (MCE) was also used to demonstrate the rapiddetection of cholesterol in serum, using (MCE) fabricated from poly (dimethylsiloxane) (PDMS) microchip channel successfully applied to determine cholesterol levels. Also, this developed method was used to measure cholesterol in abovine serum standard solution. The developed polymer micro- fluid biochip has more advantages like,compact size, high sensitivity, and highselectivity,low cost and fast response that appeared to be beneficial to perform routine analysis in the clinical laboratory. Investigations pertaining with the isolation of novel COD producing microbial strains having commercial application will be welcomed in future.

CONCLUSON

1. Soil is a rich source of microbial diversity, but less than 1% of the bacterial cultures showing growth on complex media (Sabouraud’s dextrose agar and nutrient agar) were able to grow and form halo on cholesterol enriched medium (CIM) agar plates. One isolate, strain R6 (Identified as Streptomyces sp.by 16S rRNA gene homology), producer of COD was selected for further studies.

2. The characterization of isolates was performed on the basis of the morpho-physiological characters and rRNA gene homology studies provided accurate identification of the isolated microorganism by observing the percent similarity and phylogenetic relationship with Streptomyces sp.

REFERENCES

[1] MacLachlan J, Wotherspoon AT, Ansell RO, Brooks CJ. Cholesterol oxidase: sources, physical properties and analytical applications. J Steroid Biochem Mol Biol 2000; 72:169–195.

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[4] Watanabe K SH, Aihara H, Nakamura R, Suzuki KI, Momagata K. Isolation and identification of cholesterol degradation Rhodococcus strains food of animal origin and their cholesterol oxidase activities. J Gen Appl Microbiol 1986; 32: 137– 147.

[5] Corbin DR, Grebenok RJ, Ohnmeiss TE, Greenplate JT, Purcell JP. Expression and chloroplast targeting of cholesterol oxidase intransgenic tobacco plants. Plant Physiol 2001; 126:1116-1128.

[6] Turfitt GE. The microbiological degradation of steroids: 2.Oxidation of cholesterol by Proactinomyces sp. Biochem J 1944; 38:492-496.

[7] Watanabe K, Aihara H, Nakagawa Y, Nakamura R, Sasaki T. Properties of the purified extra cellular cholesterol oxidase from Rhodococcus equi No. 23. Agric Food Chem 1989; 37:1178-1182.

[8] Liu WH, Meng MH, Chen KS. Purification and some properties of cholesterol oxidases produced by an inducible and a constitutive mutant of x (Microbiology and Fermentation Industry). Agric Biol Chem 1988; 52: 413-418.

[9] Wilmanska D SL. The kinetics of biosynthesis and some properties of an extracellular cholesterol oxidase produced by Arthrobacter sp. IM 79. Acta Microbiol Polonica 1988; 37:45–51.

[10] Shirokane Y NK, Mizusawa K. Purification and some properties of an extracellular 3- hydroxysteroid oxidase produced by Corynebacterium cholesterolicum. J Fermen Technol 1977; 55:337–345.

[11] Cheetham PS, Dunnill P, Lilly MD. The characterization and interconversion of three forms of cholesterol oxidase extracted from Nocardia rhodochrous. Biochem J 1982; 201: 515- 521

[12] Kreit J, Lefebvre G, Elhichami A, Germain P,Saghi M.Acolorimetricassayformeasuringcell-freeand cell-bound cholesterol oxidase. Lipids 1992; 27: 458-465.

[13] Somkuti GA, Solaiman DK, Johnson TL, Steinberg DH. Transfer and expression of a Streptomyces cholesterol oxidase gene in Streptococcus thermophilus. Biotechnol Appl Biochem 1991; 13: 238-245

[14] Smith M, Zahnley J, Pfeifer D, Goff D. Growth and cholesterol oxidation by Mycobacterium species inTween80 medium. Appl Environ Microbiol 1993; 59:1425-1429

[15] Inouye Y, Taguchi K, Fuji A, Ishimaru K, Nakamura S, Nomi R. Purification and Characterization of Extracellular 3b-Hydroxysteroid Oxidase Produced by Streptoverticillium cholesterolicum. Chem Pharm Bull 1982; 30:951-958.

[16] Kamei T, Takiguchi Y, Suzuki H, Matsuzaki M, Nakamura S. Purification and Properties of Streptomyces violascens origin by affinity chromatography on cholesterol, Chem Pharm Bull 1978; 26:2799–2804.

[17] Lartillot S, Kedziora P., Production, purification and some properties of cholesterol oxidase from a Streptomyces sp. Prep Biochem 1990; 20:51-62.

[18] Niwas R, Singh V, Singh R, Tripathi D, Tripathi CKM. Production, purification and characterization of cholesterol oxidase from a newly isolated Streptomyces sp. World J Microbiol Biotechnol. 2013; 29:2077-2085.

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[20] Ye D, Lei J, Li W, Ge F, Wu K, Xu W, Yong B. Purification and characterization of extracellular cholesterol oxidase from Enterobacter sp. World J Microbiol Biotechnol 2008; 24:2227–2233.

[21] Lee SY, Rhee HI, Tae WC, Shin JC, Park BK. Purification and characterization of cholesterol oxidase from Pseudomonas sp. and taxonomic study of the strain. Appl Microbiol Biotechnol 1989; 31:542–546

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[22] Doukyu N, Shibata K, Ogino H, Sagermann M. Purificationand characterization of Chromobacterium sp. DS-1 cholesterol oxidase with thermal, organic solvent, and detergent tolerance. Appl Microbiol Biotechnol 2008; 80: 59–70.

[23] Fukuyama M, Miyake Y. Purification and some properties of cholesterol oxidase from Schizophyllum commune with covalently bound flavin. J Biochem 1979; 85:1183–1193

[24] Uwajima TYH, Nakamura S, Terada O. Properties of crystalline 3â-hydroxysteroid oxidase of Brevibacterium sterolicum. Agric Biolo Chem1974; 38: 1149–1156.

[25] Richmond W. Preparation and properties of a cholesterol oxidase from Nocardia sp. and itsapplication to the enzymatic assay of total cholesterol in serum. Clin Chem 1973; 19: 1350–1356.

[26] Smith AG and Brooks CJW. Cholesterol oxidases: Properties and applications. J Steroid Biochem 1976; 7:705–713

[27] Ishizaki T, Hirayama N, Shinkawa H, Nimi O, Murooka Y. Nucleotide sequence of the gene for cholesterol oxidase from a Streptomyces sp. J Bacteriol 1989; 171:596–601.

[28] Trettnak W and Wolfbeis OS. A fiberoptic cholesterol biosensor with an oxygen optrode as the transducer. Analyt Biochem 1990; 184: 124-127.

[29] Vrielink A, Lloyd LF, Blow DM. Crystal structure of cholesteroloxidas from Brevibacterium sterolicum refined at 1.8 a resolution. J Mol Biol 1991; 219:533–554

[30] Lange Y. Tracking cell cholesterol with cholesterol oxidase. J Lipid Res1992;33:315–321[31] Purcell JP, Greenplate JT, Jennings MG, Ryerse JS, Pershing JC, Sims SR, Prinsen, MJ, Corbin

D, Tran RM, Sammons RD. Cholesterol oxidase: A potent insecticidal protein active against boll weevil larvae. Biochem Bioph Res Comm; 1993; 196:1406–1413.

[32] Linder R and Bernheimer AW. Oxidation of macrophage membrane cholesterol by intracellular Rhodococcus equi. Vet Microbiol 1997; 56:269–276.

[33] Puglielli L, Friedlich AL, Setchell KD, Nagano S, Opazo C, Cherny RA, Barnham KJ, Wade JD, Melov S, Kovacs DM, Bush AI. Alzheimer disease beta-amyloid activity mimics cholesterol oxidase. J Clin Invest 2005; 115;2556–2563

[34] Navas J, Gonzalez-Zorn B, Ladron N, Garrido P, Vazquez-Boland JA. Identification and mutagenesis by allelic exchange of choE, encoding a cholesterol oxidase from the intracellular pathogen Rhodococcus equi. Journal of Bacteriology 2001; 183:4796–4805

[35] Ohta T, Fujishiro K, Yamaguchi K, Tamura Y, Aisaka K, Uwajima T, Hasegawa M. Sequence of gene choB encoding cholesteroloxidase of Brevibacterium sterolicum: comparison with choA of streptomyces sp. SA-COO. Gene 1991; 103: 93–96.

[36] Croteau N, Vrielink A. Crystallization and preliminary X-ray analysis of cholesterol oxidase from Brevibacterium sterolicum containing covalently bound FAD. J Stru Biol 1996; 116: 317–319.It

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Modeling of Rainfall—Runoff Processes using HBV Model in The Upper Betwa River Basin

Ashish David1, D.M. Denis2 and Shakti Suryavanshi3

1Department of Irrigation and Drainage Engineering, V.I.A.E.T, S.H.U.A.T.S., Allahabad, Uttar Pradesh

2Department of Civil Engineering, S.I.E.T, S.H.U.A.T.S., Allahabad, U.P.

ABSTRACT

In this study, new Hydrologiska Byrans Vattenbalansavdelning hydrological model (HBV), has been used to synthesize river discharge, monthly flow series for ten years in the sub-catchments of the Upper Betwa basin at Basoda. An attempt has been made to use HBV model, a semi-distributed conceptual model to obtain the discharge from the upper between river basin located in northern India, and a tributary of the Yamuna. It rises in the Vindhya Range just north of Hoshangabad in Madhya Pradesh (M.P) and flows north-east through Madhya Pradesh and Orchha to Uttar Pradesh (U.P), having drainage area of 3050.04 square kilometer and total length of betwa river basin is 590 kilometers, out of which 232 kilometers lies in Madhya Pradesh and the balance of 358 kilometers lies in Uttar Pradesh. The model uses monthly rainfall data from 1 station (Sagar) from 1980 to 1990, Ten years daily discharge data for 1 station (Basoda) from 1980 to 1990 and daily temperature data for 1 station (Sagar) from 1980 to 1990 has been used as input in the HBV Model. The Coefficient of determination of observed and simulated discharge at the Rajghat was found to be 0.73. In Upper Betwa River Basin hydrological modeling using the HBV model, PERC is the most sensitive parameter followed by KHQ and FC with their slopes values -0.0446, -0.0849 and -0.00006 and R2 values 0.8312,0.81 and 0.89.

Keywords: HBV Model, Sensitive Parameter, Monthly Discharge, Synthetic Discharge, Water Balance, Betwa River, M.P., U.P.

INTRODUCTION

About 60 percent of our body is water. An adequate and continuous supply of water is required to meet agricultural, industrial and domestic demand is a basic need for all societies. Both human and natural causes the water scarcity. Unfortunately, the demand for water is increasing which leads to scarce in many parts of the world. This has led to a scientific approach to water resources planning, development, and management. Continuous repetitive observations in space and time are needed to provide the necessary input data for hydrology models to. It will help to better used to analyze the river discharge. Regularly quantifying of runoff at the outlet of a watershed remains a challenge in spite of many existing models providing the solution for the same. An attempt has been made to use HBV model to obtain the discharge from the Betwa river basin located at in Northern India, having a drainage area of 7274.82 square kilometers. The model consists of several parameters out of which the most sensitive three parameters have been calibrated and validated.

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The following are the parameters and explanation how they are used in the model.

1. FC (Field capacity): This represents the maximum soil moisture storage (mm.) and has a range from 100mm–1500mm. It influences the total volume of runoff. At low soil moisture level, most of the precipitation is kept within the unsaturated zone. If FC is too high the soil water level increases during the spring flood.

2. LP: This is the limit for potential evaporation. And its values range from 1.0 or less than 0.9. It is a soil moisture value above which evapotranspiration reaches its potential value, the LP parameter is normally not calibrated but can be adjusted if required.

3. Beta: It is the exponent in the equation for the discharge from the soil water zone. The value of Beta ranges from 1–4. Beta as FC also influences the total value and is calibrated by observing the autumn discharge.

4. Khq and hq: Khq is the recession coefficient for the upper response box when the discharge is hq. hq is a high flow level at which the recession rate Khq is assumed. The value of khq ranges from 0.005 to 0.5 per day. The unit of hq is mm per day. It is the ratio of the mean of observed discharge over the whole period and the mean of annual peaks.

5. Perc: This is the percolation capacity of the upper response box when the discharge is hq. The water from upper reservoir percolates down according to the parameter perc. The unit is in mm per day. The range of perc is from 0.01–6 mm per day. This parameter influences the shape of the hydrograph but not the volume. The base flow is also adjusted with Perc. A low perc value will result in low base flow.

6. Alfa: It is a measure of the non-linearity, typically in the order of 1. The range of alfa is from 0.6 to 1.5 when the discharge peaks are simulated alfa can be adjusted. Alfa is generally not calibrated and is used to fit the higher peaks into the hydrograph. The higher the alfa, the higher the peaks and quicker recession.

MATERIALS AND METHOD

Study AreA

The Study area, Upper Betwa River basin is considered one of the oldest rivers basins which are located at a latitude of 25°55′03″N and longitude of 80012′45″E in Northern India, having a drainage area of 3050.04 square kilometers at basoda. The total length of the river from its origin to its confluence with the Yamuna is 590 kilometers, out of which 232 kilometers lie in Madhya Pradesh and the balance of 358 kilometers in Uttar Pradesh. The Betwa River traverses a long distance of 654 km from its source near Bhopal in M.P. up to its confluence with river Yamuna near Hamirpur in U.P. and benefits both the States. The basin is saucer-shaped with sandstone hills around its periphery and clays underlain by Deccan trap basalts (Pandey et al. 2008).

The Betwa River or Betravati originates from Barkhera in Raisen district of Madhya Pradesh State, India (Fig. 01). The Betwa river joins the Yamuna river near Hamirpur in Uttar Pradesh and flows north-east through Madhya Pradesh and Orchha to Uttar Pradesh State at an elevation of about 106 m. River Richhan, Nion, Kherkhedi, Bina, and Narayan join the Betwa

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Modeling of Rainfall—Runoff Processes using HBV Model in The Upper Betwa River Basin 37

ISBN: 978-93-88237-24-6

river on its right bank while Kerwan, Halali, Bah, Sagar, Naren, Kethan etc. join on its Left bank (Fig. 02).

Fig 1: Location Map of the Betwa River Basin Fig 2: Sub-catchment of the Betwa Basin upto Rajghat Dam

ABout hBv model

The HBV model is a conceptual hydrological model for continuous calculation of runoff. It was originally developed at the Swedish Meteorological and Hydrological Institute (SMHI) in the early 70’s to assist hydropower operation by providing hydrological forecasts. The aim was to create a conceptual hydrological model with reasonable demands on computer facilities and calibration data. The model was named after an abbreviation of Hydrologiska Byrans Vattenbalansavdelning (Hydrological Bureau of Water balance section). The HBV model is a conceptual, rainfall-runoff model and can be used as a semi-distributed or lumped model. The HBV models are set up using hourly hydro-meteorological data. In this model input data are required as rainfall, air temperature, land cover, and discharge are also needed for the validation and calibration.

Fig. 3: HBV Model

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HBV MODEL COMPONENTSoil routine

The standard snow melt routine of the HBV model is a degree-day approach, based on air temperature, with a water holding capacity of snow which delays runoff. Snow melt is the further distributed according to the temperature lapse rate and the model is different in the forest and the open land areas. A threshold temperature (TT) is used in the rainfall from snowfall. When temperature decreases below from the threshold temperature than water start refreezing and glaciers are melting only in the glacier zones.

Response Function and RoutineThe runoff generation routine is the response function which transforms excess water from the soil moisture zone to the runoff. It also includes the effect of direct precipitation and evaporation on the part which represents lakes, river and other wet areas. The function consists of the one upper, non-linear, linear and one lower reservoir. These are the quick origin (Superficial channels) and slow (base flow) runoff components of the hydrograph.

METHODOLOGYThis study involves identifying the most sensitive Response routine parameter in an agricultural watershed using HBV model. This research will be carried out in five main stages which are:

1. Warming of the model this is the first stage, in this stage, the model will be run with the assumed parameters and data.

2. Calibration of the modeling this stage model calibration is the process of adjustment of the model parameters and forcing within the margins of the uncertainties.

3. Parameterization is the process of deciding and defining the parameters necessary for a complete or relevant specification of a model or geometric object.

4. Sensitivity analysis is a technique used to determine how different values of an independent variable will impact a particular dependent variable under a given set of assumptions.

5. Validation to check’s the accuracy of the model’s representation of the real system. Model validation is defined to mean “substantiation that a computerized model within its domain of applicability possesses a satisfactory range of accuracy consistent with the intended application of model”.

hBV model cAliBrAtion

When the model was run with the initial input data than it was observed that the graph was simulated were not matching data should be observed discharge because of the hydrological model is the simplified representation in a complex hydrological system and may not reflect the real world with accuracy. A hydrological model to require the fine tuning of the model parameter to improve the reliability of the model. An important part of the hydrological modeling process is to establish that the results are simulated by the model with the physical system to be represented. Hydrological model is calibrated in order to get a good fit between the observed and simulated variables.

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HBV model vAlidAtion

Validation is a process of demonstrating that a given site-specific model is capable of making accurate predictions for periods outside a calibration period. Simple model structures, calibrated over a certain period, are influenced by the rainfall-runoff sequence specific to that period (Lee, McIntyre et al. 2005) therefore in order to prove the validity of a model, the model should be tested against a second, independent set of stress conditions. The data series are going to be divided into two sets. The first set of two years for warming the model and the second set of ten years for calibration and validation. The objective functions available in HBV model are going to be used for testing the validity of modeling the Betwa river basin with the HBV model. The objective functions used to measure the reliability of the model between calculated and the observed discharge and correlation coefficient R2.

SenSitivity AnAlySiS

‘Sensitivity analysis’ aims to describe how much model output values are affected by changes in model input values. It is the investigation of the importance of imprecision or uncertainty in model inputs in a decision-making or modeling process. The exact character of a sensitivity analysis depends upon the particular context and the questions of concern. Sensitivity studies can provide a general assessment of model precision when used to assess system performance for alternative scenarios.

oBJective function

r2

It is a statistical measure of how close the data are to the fitted regression line. It is also known as the coefficient of determinate, or the coefficient of multiple determinates for multiple regressions.

In statistics, the coefficient of determination is a number that indicates the proportion of the variance in dependent variables that is predictable from the independent variable.

Where Qabs,i and Qpred,i are the observed and predicted flow for each time step and n is the number of steps in the simulation period considered.

RESULTS & DISCUSSION

This chapter deals with the results and discussion obtained by adopting the methodology. If discuss the parameter influencing Discharge, which using a conceptual model HBV. The model is calibrated, parameter parameterized range of parameter identified. The objective function was used to find the acceptable range of each parameter influencing the Discharge, Finally the parameterized values more used to revalidate Discharge for the study area.

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Table 1: Table show Parameter used in Initialization and Calibration the Model

S. No Parameters Initialization Values Calibrated Values

1 Alfa 1 1

2 Athorn 0.5 0.5

3 Beta 1.340 2.5

4 Cevpl 1.15 1.15

5 Cflux 1.5 1.5

6 Critstep 1 1

7 Etf -1 -1

8 Fc 120 500

9 Hq 3 3

10 K0 0.00668 0.00668

11 K4 0.0054 0.0054

12 Khq 0.52 0.1

13 Lp 0.95 0.95

14 Pcalt 0.1 0.1

15 Pcaltl 800 800

16 Perc 0.1 0.1

17 Soilstep 3 3

18 Stf 1 1

19 resparea 1 1

20 rfcf 1 1

The model warm up was done by running the model for a period of 2 years then discharge was computed for the whole period of 01 January 1980 to 31 December 1990.

Fig. 4: Simulation of Discharge for Model Warming Period 1980–1981

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Fig 5: Relationship between Observed and Simulated Discharge by Calibrated Parameters for 1980–1981

SimulAtion reSultS of the cAliBrAtion period

The optimum values of the soil moisture routine parameter (FC) and response routine parameters (Khq and Perc) were determined by considering the coefficient of determining (R2) as high as possible. The R2 should be as high as possible. Selection of the best parameter set was made based on quantitative interpretation. Taking into account these two criteria, a sensitivity analysis for soil moisture routine parameter and response routine parameters routine was carried out. Low field capacity (50 mm) suggests a system, which is filled quickly. In this way, water is available for direct runoff. Moreover, a high value of FC is needed to capture the quick response of the system. All the parameters represent the characteristics of the catchment. During the calibration, it is seen that some parameters (ALFA, ATHORN, and BETA) were less sensitive and thus have not been changed during model calibration.The parameters calibrated are given in Table 1. These parameters were calibrated for the years 1980–1990. Results of discharge obtained are shown in the Fig. 6. Parameters shows in Table 1 are responsible for the Discharge.

Fig. 6: Observed Data of Discharge for Model of 10 years Period 1980–1990

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Fig. 7: Simulated Data of Discharge for Model of 10 years Period 1980–1990

SimulAtion reSultS of the vAlidAtion period

The HBV model is develop for Swedish conditions. However it does work when data input is provided. The process of the model uses is understood at the between river basin. All input parameters influencing the total discharge at the Betwa river basin is carefully parameterized. The model calibrates and validates it on a yearly timescale.

Fig. 8: Observed and Simulated Discharge for model of 10 years Period 1980–1990

Fig. 9: Relationship between Observed and Simulated Discharge for Model of 10 years Period 1980–1990

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SenSitivity AnAlySiS

The sensitivity analysis for all the seven parameters was done and are shown in Fig. 10 to Fig. 15. From these figures, we can see the range in which these parameters are sensitive. Since the model parameters did not have a uniform increase or decrease for the sensitivity analysis, they are shown here as individual graphs. The trend lines in these graphs show the range in which these parameters are sensitive and have their influence on the model. The slope of the graphs explains the most sensitive parameter and sensitive parameters from high to low along with their slopes values are shown below figures.

Fig. 10: Sensitivity Analysis for alfa Value

Fig. 11: Sensitivity Analysis for Beta Values

Fig. 12: Sensitivity Analysis for FC Values

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Fig. 13: Sensitivity Analysis for perc Values

Fig. 14: Sensitivity Analysis for khq Values

Fig 15: Sensitivity Analysis for hq Values

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DISCUSSION

The HBV model was used successfully to model discharge for the study area. Both calibration and validation results show a strong relationship between the simulated and observed discharge from the study area. The results from the model calibration and validation are shown in above Fig. Best results (with best R2=0.73) were attained during the calibration period than the validation period for the basin. These R2 values are shown in Fig 9. High correlation between observed and simulated discharge (R2 =0.72) during the calibration period and (R2 = 0.73) during the validation period. Figs. 10 to 15 shows the sensitivity analysis of the six parameters which influences the between river basin.

CONCLUSION

This study evaluated the effects of various parameter scale selections in the HBV model simulation. Comparison of hydrological simulation using average parameter values from short temporal calibration and using manual optimization was also conducted. We can obtain the following conclusions:

1. In Betwa river basin hydrological modeling using the HBV model, Perc are the most sensitive parameter for discharge in this basin.

2. In some parameters, R2 is the objective function values and their values will not change i.e., constant 0.73 respectively.

3. The most sensitive parameters from high to low along with their slopes values are perc: 0.0448, khq: 0.0849, FC: 0.00006 andR2values: 0.89, 0.83 and 0.81.

Simulation only reflects the model sensitivity to change in land and prediction can only be as accurate as the model structure and the data quality, however, an important consistency in the model results. The HBV model is originally a conceptually lumped model. Though a great deal of effort has been invested in accounting for spatial variability of precipitation and temperature in the “distributed” HBV model, it still falls short in its ability to account for full spatial variability due to its conceptual and lumped in nature. HBV simulations are more sensitive to potential evapotranspiration changes.

REFERENCES

[1] Abebe Nibret A., Ogden. Fred L. and Pradhan. Nawa R. (2010). Sensitivity and uncertainty analysis of the conceptual HBV rainfall-runoff model: Implications for parameter estimation. Journal of Hydrology 389, pp. 301–310.

[2] A.H. te Linde, J.C.J.H. Aerts, R.T.W.L. Hurkmans and M. Eberle (2008). Comparing model performance of two rainfall-runoff models in the Rhine basin using different atmospheric forcing data sets. Hydrol. Earth Syst. Sci., 12, pp. 943–957.

[3] ASCE Task Committee (1993). Criteria for evaluation of watershed models. Journal of Irrigation and Drainage Engineering. 119(3), pp. 429–442.

[4] Betwa River Board, Rajghat Dam Project, Project Report Vol. I—General Report and Cost Estimate (1979). Betwa River Board, Jhansi (U.P.).

[5] Betwa River Board, Rajghat Dam Project, Project Report Vol. II—Observational & Test Data & Drawings (1979). Betwa River Board, Jhansi (U.P.).

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[6] Bardossy A and Singh. S.K. (2008). Robust estimation of hydrological model parameters. Hydrol. Earth Syst. Sci., 12, pp. 1273–1283.

[7] Chaube U.C., Shakti Suryavanshi, Lukman Nurzaman and Ashish Pandey (2011). Synthesis of Flow Series of Tributaries In Upper Betwa Basin, International Journal of Environmental Sciences, Vol. 1, No. 7.

[8] Garg, H.K. (1987). Water Utilization Model Study of Rajghat Multipurpose Project and Betwa Basin. Unpublished: M.E. Dissertation Report University of Roorkee.

[9] Gitte. B., Jonas. G. and Hanna. G. (2009). The German Federal institute of hydrology calibrated HBV rainfall-runoff model for the river Rhine. Hydrol. Earth Syst. Sci., 12, pp. 1156–1162.

[10] Göran Lindström, Barbro Johansson, Magnus Persson, Marie Gardelin and Sten Bergström (1997). Development and test of the distributed HBV-96 hydrological model. Journal of Hydrology, 201, pp. 272-288.

[11] Hundecha. Yeshewatesfa and Bardossy Andra (2004). Modeling of the effect of land use changes on the runoff generation of a river basin through parameter regionalization of a watershed model. Journal of Hydrology 292, pp. 281–295.

[12] Jan. S. (1996). Estimation of parameter uncertainty in HBV model, Nordic Hydrology, 28(4/5), pp. 247–262.

[13] K. Mira and S. Kay (2006). Calibration techniques used for hbv hydrological model in savinja catchment.

[14] Kollat. J.B., Reed. P.M. and Wagener. T. (2012). Multi objective calibration trade-offs in hydrologic models meaningful. Water resources research, Vol. 48, w03520, doi: 10.1029/2011wr011534.

[15] Kolade M. Owolabi (2016). Numerical solution of diffusive HBV model in a fractional medium. Owolabi Springer Plus, 5: 1643 DOI 10.1186/s40064-016-3295-x.

[16] Lal. M.P and Martijnetal B.J (2009). Calibration of a semi-distributed hydrological model using discharge and remote sensing data. IAHS Publ. 333.

[17] M.G. Grillakis and I.K. Tsanis (2010). Application of the HBV hydrological model in a flash flood case in Slovenia. Nat. Hazards Earth Syst. Sci., 10, pp. 2713–2725.

[18] M. Mendeza and L. Calvo-Valverdeb (2016). Development of the HBV-TEC hydrological model, 12th International Conference on Hydro informatics, HIC 2016.

[19] Miha. P. and Mira. K. (2006). The implementation of the HBV model on the Sava river basin.[20] Pandey, R.P, S.K. Mishra, R. Singh and K.S, Ramasastri (2008a). Streamflow Drought Severity

Analysis of Betwa River System (India), Water Resources Management, 22, pp. 1127–1141.[21] Pandey, A, V.M., Chowdary, B.C. Mal and M. Billib (2008b). Runoff and sediment yield modelling

from a small agricultural watershed in India using the WEPP model. Journal of Hydrology 348, pp. 305–319.

[22] Seibert. J and Vis. M.J.P. (2012). Teaching hydrological modeling with a user-friendly catchment-runoff-model software package. Nat. Hazards Earth Syst. Sci., 10, pp. 2713–2725.

[23] Sten bergström (2006). Experience from applications of the HBV hydrological model from the perspective of prediction in ungauged basins. MOPEX. IAHS Publ. 307.

[24] Steven. R.R. and Doddi. Y. et al. (2015). Effects of temporal variability on HBV model calibration. Journal of Hydrology 295, pp. 153–160.

[25] Uhlenbrook. S. and Mmohamed. Y. (2010). Analyzing catchment behavior through catchment modeling in the Gilgel Abay, Upper Blue Nile River Basin, Ethiopia. Hydrol. Earth Syst. Sci., 14, pp. 2153–2165.

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Frontier Aspects in Agricultural Waste Management for Environmental Sustainability

B.S. Sagar*1, B.R. Sahithya2

1-2Department of Fruit Science, College of Horticulture Bagalkot,

University of Horticultural Sciences Bagalkot, 587-104 (Karnataka)


ABSTRACT

India stands second in population and India produces a huge quantity of agricultural waste. Agriculture is the backbone of India. Agricultural Wastes (AW) are wastes produced from agricultural activities in agricultural premises. Agricultural wastes are often managed poorly because of the limited access to disposal facilities, hence most of the agricultural wastes are burned or incinerated. Agricultural wastes are defined as the residues from the growing and processing of raw agricultural products such as fruits, vegetables, meat, poultry, dairy products, and crops. They are the non-product outputs of production and processing of agricultural products that may contain material that can benefit man but whose economic values are less than the cost of collection, transportation, and processing for beneficial use. Their composition will depend on the system and type of agricultural activities and they can be in the form of liquids, slurries, or solids. Agricultural waste otherwise called agro-waste is comprised of animal waste (manure, animal carcasses), food processing waste (only 20% of maize is canned and 80% is waste), crop waste (corn stalks, sugarcane bagasse, drops and culls from fruits and vegetables, prunings) and hazardous and toxic agricultural waste (pesticides, insecticides and herbicides, etc). Indian farmers are turning garbage into gold. The husks, weeds and other agricultural waste they thought were useless are being converted into sustainable, non-polluting and cheap energy that is lighting up villages and irrevocably changing lives.

Keywords: Agriculture, Sustainable, Waste

INTRODUCTION

There is likely to be a significant increase in agricultural wastes globally if developing countries continue to intensify farming systems. It is estimated that about 998 million tonnes of agricultural waste are produced yearly. Organic wastes can amount up to 80 percent of the total solid wastes generated in any farm of which manure production can amount up to 5.27 kg/day/1000 kg live weight, on a wet weight basis. Nowadays to get a maximum yield within shorter period, farmers are using chemical fertilizers. No doubt these fertilizers give better yield but their use causes permanent damage to the soil texture. Usually, farmers are adopting good old methods for solid waste management. Major part of the after harvest materials like straw, sugar canetrashes, plants, grass etc are used for livestock feeding. Remaining of these feedings, herbs, weeds are usually dried and burned in the field or otherwise farmers will leave the remaining in the field, watered continuously and allows as it is for several months.

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This may sometimes cause anaerobic condition and leads to bad smell, attracts flies and spread epidemic diseases. Therefore proper management of solid waste in the agricultural. the field is necessary. The agricultural waste contains biodegradable hemicellulose and cellulose materials, which on decomposition gives good nutrients to plants. Cowdung is an animal waste which comes under agricultural wastes commonly available in the rural area which rich in nutrients and microorganisms and can be used as good seeding material as it is available in the agricultural farm itself from livestock and also poultry manure piggery, ship manure can be used for compost making which is rich in nutrients.

The Green Revolution, or Third Agricultural Revolution, refers to a set of research and the development of technology transfer initiatives occurring between 1950 and the late 1960s, that increased agricultural production worldwide, particularly in the developing world, beginning most markedly in the late 1960s. The initiatives resulted in the adoption of new technologies, including high-yielding varieties (HYVs), in association with chemical fertilizers and pesticides. During green revolution, farmers used a huge quantity of chemical fertilizers and pesticides to double the yield which caused an adverse effect on the environment, human health and soil health. So now by utilizing agricultural wastes, soil health can be improved by organic farming and composting which is one of the wealth of agriculture and provide poisoned free foods.

clASSificAtion of AgriculturAl WASte

● Field waste: weeds, harvested crop residues like a vegetable, fruits, straws leaves etc.

● Animal wastes: animal excreta, urine, litter waste feed

● Agro-Industrial waste: sugarcane, molasses, wine industries, juice industries etc.

AgriculturAl WASte creAteS fieldS of gold in rurAl indiA By:

● Composting

● Organic farming

● Vermicompost

● Bio-fertilizer

● Biogas

Composting

Composting is a sustainable waste management practice that converts any volume of accumulated organic waste into a usable product. When organic wastes are broken down by microorganisms in a heat-generating environment, the waste volume is reduced, many harmful organisms are destroyed, and a useful, potentially marketable, the product is produced. Organic wastes may include manure from livestock operations, animal bedding, yard wastes, such as leaves and grass clippings, and even kitchen scraps. Agricultural waste can be converted to the wealth by utilizing them in compost production which is one of the important wealth of agriculture crop production. Raw organic materials such as crop residues, animal wastes, food garbage, some municipal wastes, and suitable industrial wastes, enhance their suitability for application to the soil as a fertilizing resource, after having undergone composting.

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Frontier Aspects in Agricultural Waste Management for Environmental Sustainability 49

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The compost made from farm waste like sugarcane trash, paddy straw, weeds, and other plants and other waste is called farm compost. The average nutrient contents of farm compost are 0.5 percent N, 0.15 percent P2O5and 0.5 percent K2O. The nutrient value of farm compost can be increased by application of superphosphate or rock phosphate at 10 to 15 kg/t of raw material at the initial stage of filling the compost pit. The compost made from town refuses like night soil, street sweepings and dustbin refuse are called town compost. It contains 1.4 percent N, 1.00 percent P2O5 and 1.4 percent K2O.

Organic Farming and Waste Recycling

It has been estimated that organic resources available in the country alone can produce not less than 20 million tonnes of plant nutrients (NPK). Vermicompost technology has promising potential to meet the organic manure requirement in both irrigated and rainfed areas. It has tremendous prospects in converting agro-wastes and city garbage into the valuable agricultural input. Vermi-wash can also be used as a spray on crops. Recycling of organic wastes such as crop residues, dung, and urine from domesticated animals, the biomass of weeds, organic wastes from fruit and vegetables production and household wastes, sugarcane trash, oilcakes, press mud and fly ash from thermal power plants. Material not suitable for the direct application can better apply by composting and vermicompost. The ultimate goal of sustainable agriculture is to develop a farming system that is production and profitable, conserve the natural resources base, protect the environment and enhance health and safety, and to do so over the long term. Two farming system has been proposed for ensuring sustainability. There are low input sustainable agriculture (LISA) and organic farming

Organic farming is the backbone of sustainable agriculture. Organic farming mainly depends on son Organic recycling: Industrial agriculture chemicals like fertilizer, pesticide, herbicide etc are not used or used to the minimum extent necessary in this kind of farming. Organic farming may result in comparable performance as conventional agriculture and crops growth with high organic manure application could tolerate the pest and disease attack better. Organic recyclable waste includes – crop residues, waste, farm industrial waste, multiple and sewage wastes. They are valuable sources of plant nutrient and humans in tropical and subtropical soils found in India, there is a general deficiency of organic carbon and plant nutrients due to rapid loss of this component by biodegradation. To make u for these losses, extensive utilization of organic residues in agriculture is essential. In addition, they also protect the soil from erosion.

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In India, there is a general potential for utilization of crop residues/ straw of major crops. Abort 141.2 MT. straws available and from that, contribute about 0.7, 0.84, and 2.1 MT .N.P.K respectively. If considering 50% crop residue utilized as animal feed, the rest can recycle.

Vermicomposting

Vermicompost is the process of turning organic debris into worm castings.compost. Earthworms consume biomass and excrete it in a digested form called worm casts. Worm casts are popularly called as Black gold. The casts are rich in nutrients, growth promoting substances, beneficial soil microflora and having properties of inhibiting pathogenic microbes. Vermicompost is stable, fine granular organic manure, which enriches soil quality by improving its physicochemical and biological properties. It is highly useful in raising seedlings and for crop production. Vermicompost is becoming popular as a major component of the organic farming system.

The worm castings are very important to the fertility of the soil. The castings contain high amounts of nitrogen, potassium, phosphorus, calcium, and magnesium. Castings contain 5 times the available nitrogen, 7 times the available potash, and 1½ time more calcium than found in good topsoil. Earthworm castings have excellent aeration, porosity, structure, drainage, and moisture-holding capacity. The content of the earthworm castings, along with the natural tillage by the worms burrowing action, enhances the permeability of water in the soil. Worm castings can hold close to nine times their weight in water. “Vermiconversion,” or using earthworms to convert waste into soil additives, has been done on a relatively small scale for some time. A recommended rate of vermicompost application is 15-20 percent. It is one of the easiest methods to recycle agricultural wastes and to produce quality. Decomposable organic wastes such as animal excreta, kitchen waste, farm residues, and forest litter are commonly used as composting materials. In general, animal dung mostly cow dung and dried chopped crop residues are the key raw materials. A mixture of leguminous and non-leguminous crop residues enriches the quality of vermicompost. There are different species of earthworms viz. Eiseniafoetida (Red earthworm), Eudriluseugeniae (night crawler), Perionyxexcavatus etc. Red earthworm is preferred because of its high multiplication rate and thereby converts the organic matter into vermicompost within 45-50 days. Since it is a surface feeder it converts organic materials into vermicompost from the top. These wastes could be converted into a potential renewable source of energy if managed sustainably and scientifically. In the last few decades, vermicomposting technology has been arising as a sustainable tool for the efficient utilization

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of the agro-industrial processing wastes and to convert them into value-added products for land restoration practices.

Bio-fertilizer

Bio-fertilizers are ready to use live formulates of such beneficial micro-organisms which on application to seed, root or soil mobilize the availability of nutrients and help build up the micro-flora and turn the soil health in general.

With the introduction of green revolution technologies, modern agriculture is getting more and more dependent upon the steady supply of synthetic inputs (mainly fertilizers), which are products of fossil fuel (coal+ petroleum). Adverse effects are being noticed due to the excessive and imbalanced use of these synthetic inputs. This situation has lead to identifying harmless inputs like bio-fertilizers.

Biogas

Biogas is produced after organic materials (plant and animal products) are broken down by bacteria in an oxygen-free environment, a process called anaerobic digestion. Biogas systems use anaerobic digestion to recycle these organic materials, turning them into biogas, which contains both energy (gas), and valuable soil products (liquids and solids). Anaerobic digestion already occurs in nature, landfills, and some livestock manure management systems, but can be optimized, controlled, and contained using an anaerobic digester. Biogas contains roughly 50-70 percent methane, 30-40 percent carbon dioxide, and trace amounts of other gases. The liquid and solid digested material, called digestate, is frequently used as a soil amendment. After biogas is captured, it can produce heat and electricity for use in engines, microturbines, and fuel cells. Biogas can also be upgraded into bio-methane, also called renewable natural gas or RNG, and injected into natural gas pipelines or used as a vehicle fuel.

The Benefits of Biogas Stored biogas can provide a clean, renewable, and reliable source of baseload power in place of coal or natural gas. Baseload power is consistently produced to meet minimum power demands; renewable baseload power can complement more intermittent renewables. Similar to natural gas, biogas can also be used as a source of peak power that can be rapidly ramped up. Using stored biogas limits the amount of methane released into the atmosphere and reduces dependence on fossil fuels.

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AdSorBentS in the eliminAtion of heAvy metAlS

Excessive release of heavy metals into the environment due to industrialization and urbanization has posed a great problem worldwide. Heavy metal ions such as copper, cadmium, mercury, zinc, chromium and lead ions do not degrade into harmless end products.

In recent years, agricultural wastes have proven to be a low-cost alternative for the treatment of effluents containing heavy metals through the adsorption process. The low-cost agricultural waste such as sugarcane bagasse, rice husk, sawdust, coconut husk, oil palm shell, neem bark etc., used for the elimination of heavy metals from wastewater

pyrolySiS

In pyrolysis systems, agricultural waste is heated up to a temperature of 400-600°C in the absence of oxygen to vaporize a portion of the material, leaving a char behind. This is considered to be a higher technology procedure for the utilization of agricultural wastes. Others are hydro-gasification and hydrolysis. They are used for the preparation of chemicals from agricultural waste as well as for energy recovery.

AnimAl feed

In most developing countries, the problem with animal feed is in the limited availability of protein sources although great efforts are being made to find alternative supplements. Crop residues have high fiber content and are low in protein, starch, and fat. Using paddy straw, vegetable, fruit waste, and crop generated waste can be used as a feed for animals.

Leaving crop residue (wastes) on the fields has many known beneficial effects. For one, the residues are used as a nutrition source for soil organisms which slowly break it down into smaller and finer particles which end up constituting soil organic matter. This, in turn, is broken down providing nutrition for crops and reducing fertilizer requirements.

Maintaining residue on the field, both above and underground is a well-known soil conservation or erosion control measure. Residue protects the soil from wind erosion, it slows down and prevents water from running off and acts as a wick allowing rainwater to infiltrate deep into the soil, recharging it with water. Furthermore, the residue acts as a continuum gap between water in the soil and water in the atmosphere, which basically means that evaporation of soil water, in a soil covered with residue, is diminished. Soil conservation and water conservation are the two sides of the same coin. Water harvesting can only be done if the soil is in a healthy state, physical, chemical and biological.

The positive impact of the organic waste application on the improvement of physical properties of the soils such as soil structure, water holding capacity, soil temperature, bulk density, total porosity, pore size distribution, soil resistance to penetration, aggregation, aggregate stability, hydraulic conductivity, base exchange capacity and resistance to soil erosion.

Advantages of Agricultural Waste Management:

● Reduce indiscriminate disposal or burning of waste which cause soil, water, and air pollution

● Conversion of all forms of vegetable and animal waste into organic matter

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● Utilization of agricultural waste maintains the soil health

● Keeps the environment clean and fresh

● Reduces environmental pollution

● Creates employment

● Reduce the dependence on chemicals and move towards more natural and healthier methods of food production

● By using agricultural waste the cost of production reduces

● Able to reduce the cost of animal feeding

● Conversion and utilization of agricultural waste can reduce the pest and disease attack and increases the yield of the crop.

CONCLUSION

A fundamental change in attitude is needed in the way wastes are managed. As the population keeps growing, more pressure is put on waste disposal of different kinds. In future, the need for the clean and safe environment will be among the most serious problems that need to be tackled. Preserving the environment is a major challenge that India and the world over are facing today. It is necessary for the environmentalists and women, to save the environment for better tomorrow for the next generation. Sensitization and mass awareness can contribute towards proper and safe disposal of waste. Composting, as a treatment of organic waste, had been proven to significantly reduce the volume of wastes in the country. In addition, composting can also provide nutrients that are suitable for agriculture and can be used as fertilizer to replace chemical fertilizer. Furthermore, compost can also be used as soil amendments as well as being eco-friendly, hygienic economical and toxic free. Vermicomposting is a faster system for breaking down organic waste than traditional composting approaches, allowing effective management of large organic waste burdens.

REFERENCES

[1] Zularisam, A.W., Zahir, Z. Siti., Zakaria, I., Syukri, M.M., Anwar, A. and Sakinah, M. 2010, Production of Biofertilizer from Vermicomposting Processes of Municipal Sewage Sludge. Journal of Applied Sciences. 10 (7): 580–584.

[2] Xing, Meiyan, JianYang, null; Wang, Yayi; Liu, Jing and Yu, Fen.2011,A comparative study of synchronous treatment of sewage and sludge by two vermifiltrations using an epigeicearthworm. Journal of Hazardous Materials. 185 (2–3): 881–888.

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Assessment of Noise Level during Dusseharaat Ghoorpur, Bara Tehsil, Prayagraj, Uttar Pradesh

Mohd Nafees1*, Satyendra Nath2, and R. P. Singh3

1,2Department of Environmental Sciences & NRM, College of Forestry,

SHUATS, Prayagraj, U.P., India.

3Department of Civil Engineering, MNNIT, Prayagraj,

U.P., IndiaE-mail: *[email protected]

ABSTRACT

Noise pollution and its effect on humans has been a recognized problem for decades. The urbanization and industrialization lead a serious problem. The present study explores the noise pollution during Dussehra at Ghoorpur, Bara Tehsil, Prayagraj. The L10 values were observed between 92.6–96.6 dB, L9073.0- 77.9 dB and Leq values between 89.6 – 93.9 dB at day time during 6:00 PM to 9:00 PM. During night time, L10 values between 103.7-117.2 dB, L9083.1- 99.7 dB and Leq values 100.5– 114.0 dB at Ghoorpur. The observed noise level during the period was higher than the prescribed limit laid by Central Pollution Control Board.

Keywords: Noise; Festival; Noise level

INTRODUCTION

Noise pollution is an environmental noise which is created by human and their daily activities that disrupts the activity of human life. Noise pollution can impact on physical as well as physiological health and higher exposure of noise level create the problem, annoyance, and irritation, damage to auditory mechanisms, psychological disorders, disturbances of daily activities and performances, hypertensions and schematic heart diseases (Singhand Davar, 2004:Kalshetty et al., 2010). Ganesh Utsav, Durga Puja, Dipawali, party, weeding ceremonies, and other religious festivals are celebrated in India that creates minimum noise level which gives happiness and avoids adverse effects on human health (Nafees and Nath, 2018). Indian festivals are celebrated with dance and song in a large group using musical instruments. Dussehra is the most famous and widely celebrated festival in India. During festival periods, loudspeakers and other musical instruments produce a lot of annoyance. During the festival, the level of noise was increased. The present study focused on monitoring of noise pollution during Dussehra at Ghoorpur, Bara Tehsil, Prayagraj.

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Study AreA

The study was performed in Ghoorpur market, situated on National Highway and approximate 16.8 km from city center.

monitoring time

Noise observation was performed on 15 October 2016 during 6:00 PM to 6:00 AM (12 hours) at Ghoorpur.

field meASurement

Noise monitoring was carried out to assess the noise produced during the festive day (Dussehra) at site Ghoorpur. Noise monitoring was performed using SLM (Sound Level Meter), during the observation of noise, the microphone of the sound level meter was pointed approximately 1m away from any reflective surfaces and 1.2 m to 1.5 m above the ground to reduce the effect of acoustic reflection. Noise monitoring was carried out during 6:00 PM - 6:00 AM in festive day. The noise level standards are given in table 1.

Table 1: Standards of noise level as laid by CPCB (January 2010)

Area Code Category of Area/Zone Limits in dB (A) Leq day time (6 a.m. and 9 p.m.)

Limits in dB (A) Leq night time (9 p.m. and 6 a.m.)

A Industrial Area 75 70

B Commercial Area 65 55

C Residential Area 55 45

D Silence Zone 50 40

RESULT AND DISCUSSION

The present study focused on noise pollution during the peak period of Dussehra in the selected place. The observed values plotted in fig 1. L10, L90and Leqshowed the level of noise. The variation of L10 values was 92.6 dB to 96.6 dB and L90values 73.0 dB to 77.9 dB with the Leq values of 89.6 dB to 93.9 dB during 6:00 PM to 9:00 PM at day time. Figure 1 shows that L10, L90 and Leq values are higher than the prescribed limit of Central Pollution Control Board

Fig. 1: Variation of noise level during day time

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(CPCB). The highest value was observed during 8:00 pm to 9:00 pm (96.6 dB) and minimum value during 6:00 pm to 7:00 pm (73.0 dB).

Vehicles, loudspeaker, drums, and other musical instruments were the main source of increasing noise (Nafees and Nath, 2018). The higher noise value varied with time, towards peak hour. The maximum movement of people and other factors influence the noise level.

Fig. 2: Variation of Noise level during night time

The L10 ranges from 103.7 dB to 117.2 dB, L90 ranges 83.1 dB to 99.7 dB and Leq ranges 100.5 dB to 114.0 dB at 9:00 pm to 6:00 AM during night time (Chien and Shih, 2007). The highest noise was observed at 12:00 PM to 1:00 AM (117.2 dB) and the minimum noise were observed at 9:00 PM to 10:00 PM (83.1 dB). Figure 2 showed that the observed noise levels during night time were higher than the standard limits of CPCB. The influencing factors were loudspeaker, jhanki, choukiand other musical instruments, increase the level of noise.

Fig. 3: Variation of noise level during the monitoring period

The level of noise varied with the time. Figure 3 showed that increasing trend of noise up to 1:00 AM and after that decreasing trend observed early morning 4:00 AM. After that increasing trends of noise were observed up to 6:00 AM.

CONCLUSION

The present study indicated the noise variations during the Dussehra time. The high noise level was observed both during day time and night time but the noise level during night time

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was more than the day time due to local people, shopkeepers, DJ, chouki. The crowed of local peoples, shopkeepers, and chouki during the evening to late night and they affected the level of noise in mela during Dussehra. The high noise level affects on human being and residents living around roadside and also disturbance the sleep and daily routine life. The study indicated that the variation of noise level cross the limit of CPCB standards and situation was alarming during mela/ Dussehra. The proper management and control the exceeding noise pollution during mela and people are aware about impact noise pollution on health. Current scenario public awareness on the impact of noise pollution on human health.

REFERENCES

[1] Chien, M. K., And Shih, L. H. (2007) An empirical study of the implementation of green supply chain management practices in the electrical and electronics industry and their relation to organizational performances.International journal of environment, science and technology, Vol. 4 (2): 383-394.

[2] Nafees, M. And Nath, S. (2018) Noise Levels in Dussehara at Mahewa, Allahabad, Uttar Pradesh.Universal Journal of Environmental Research and Technology, Vol. 7(1): 56-60.

[3] Singh, N. and Davar, S.C. (2004) Noise Pollution- Sources, Effects and Control.J. Hum. Ecol. Vol. 16(3): 181-187.

[4] Kalshetty, B. M., Sheth, R. C., Sanganavar, M. C. and Kalashetti, M. B. (2010) Physiological ill effect of environmental pollution due to industrial development. Current world environment, Vol.5 (1): 159-163.

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Application of Breadfruit in Food Products

Bhopal Singh1, Rekha Rani2* and Chetan N. Dharaiya3

1Faculty of Science in Dairy Technology, Dayalbagh Educational Institute, Agra, Utter Pradesh, India

2Warner College of Dairy Technology, Sam Higginbottom University of Agriculture,

Technology and Sciences, Allahabad, Utter Pradesh, India3Department of Dairy Technology,

SMC College of Dairy Science, AAU, Anand, Gujarat, IndiaE-mail: *[email protected]

ABSTRACT

Breadfruit (Artocarpusaltilis) is a tropical fruit of mulberry family which originated from New Guinea and possibly from Moluccas and Philippines. It possess high nutritional value and also useful in the prevention of many diseases. In comparison to other tropical crops, it is a traditional crop in Oceania with the potential to prevent hunger and mitigate diabetes. Cooked breadfruit helps to regulate blood sugar levels in humans. Urinary tract problems, injured eyes, mosquito repellent, headaches, urinary infections, hypertension and fewer can be treated by the leaves, roots, seed and the fruit. So many authors reported the importance of each and every part of it in value-added food products. It is an alternative source of starch for industrial and pharmaceutical purposes. Breadfruit contains a higher level of crude fiber, protein, starch, minerals, and vitamins, enhances its functional and nutraceutical value. The flour has been used in the preparation of stiff porridges, infant formulas, extruded products, bread, cake, fermented foods, pancakes, and biscuits.

Keywords: Breadfruit, Hunger, Blood Sugar, Hypertension, Starch

INTRODUCTIONBreadfruit (Artocarpusaltilis) belongs to the mulberry family of Moraceae and it is a tropical fruit (1). Zerega et al. (2004) used genetic markers and observed that Artocarpusaltilisspecies was derived from Artocarpuscamansi species, which is a species of a higher amount of large seeds and it was originated from New Guinea, Moluccas and the Philippines (2). Zerega et al. (2015) also reported that many cultivars in Vanuatu and other Western Oceania countries were showed greater genetic diversity than the Eastern Polynesia cultivars (3). Molecular marker techniques for breadfruit (4,5) provide valuable tools for the uniqueness of a genotype, tracing its origin and also indicating its propagation history. Perishable nature of the fruit is the biggest problem for large-scale production and international trade. At ambient temperature conditions, the fruit lost its freshness only in five days (6). The longer shelf life of 3-4 weeks can be obtained using controlled atmosphere storage (CAS) packaging at 16°C with 5% oxygen (O2), 5% carbon dioxide (CO2) (7). The fruit has good nutritional value and high calorific content such as 68% starch, 4% protein, 1% fat dry weight basis, vitamins and minerals (8). Due to a higher level of crude fiber present in the fruit, make it a good choice for diabetic people.

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NUTRITIONAL SIGNIFICANCE

Now a day it is used as an alternative source of starch for industrial and pharmaceutical purposes. The yield of seedless (dry matter basis) breadfruit which was cultivated in Venezuela was 18.5g/100g of starch (9). The starch contained higher water absorption, solubility, and swelling power than corn (Zea mays L.) or amaranth (Amaranthus cruentusL.) starch. Due to higher gelatinization temperature (73.3°C), it was stable during heating and cooling cycles. Adebowaleet al. (2005) reported that breadfruit starch can be modified using oxidation, acetylation and annealing treatments to alter functional properties (10). These modifications reduced gelling activity, solubility, pasting temperature, peak viscosity, hot paste viscosity and cold paste viscosity of the starch. Breadfruit starch was used as an alternative to corn starch in the pharmaceutical industry to bind tablets (11) and tablet disintegrant (12).

Breadfruit also contained higher amount of fiber than other commonly consumed staples in the Pacific Islands because 100 g of cooked breadfruit can contain up to 7.37 g crude fiber while cooked potato, rice, sweet potato, taro, and plantains it is 1.50, 0.30, 3.30, 5.10, and 2.30 g/100 g, respectively (13).

Liu et al. (2015) reported breadfruit as a source of high-quality protein for food security and novel food products (14). It contains an average of 3.9% protein (dry weight basis), which is 1.15% higher than cassava, 1.1% higher than a banana and 0.3% higher than sweet potato (15).

HEALTH BENEFITS

Different parts of the tree such as leaves, fruit, root have it s medicinal value. Whistler (2001) reported that urinary tract problems and injured eyes can be treated with the barks or roots and leaves of the plant, respectively (16). Mosquito repellent can be treated by male inflorescence of the plant (17). Headaches, urinary infections, hypertension (18) and fewer (19) cab be treated with the leaves of the plant. Breadfruit tree shoots in combination with Macarangadioica are useful for headaches and migraines treatment (19). Cooked breadfruit can regulate blood sugar in humans and useful for diabetic people. Turi et al. (2015) reported the breadfruit (Artocarpusaltilis and hybrids) as a traditional crop with the potential to prevent hunger and mitigate diabetes in Oceania (20).

APPLICATIONS OF BREADFRUIT

In Asian countries, breadfruit is consumed as a vegetable and picked before fully ripe to be used in the preparation of curry and similar products. The curry-like the dish is prepared by the cutting of flesh into chunks and parboiled them before mixing to coconut milk and other seasonings. It can also be used by cutting it into thin slices followed by deep frying and flavored with either salt, sugar syrup orchilli powder (1). It was also reported that cooked breadfruit was hardly noticeable from an excellent batter pudding. Omobuwajo (2003) prepared biscuits, prawn crackers and fried chips from breadfruit flour and reported that the textural quality of the products was optimum with the partial replacement of breadfruit flour. Full replacement lost the crispiness and organoleptic attributes of the products (21). Breadfruit flour had been used in so many food preparations like infant formulas (22), stiff porridges(23), biscuits(24), extruded products(25), fermented foods(26), breadfruit flour bar(27). Breadfruit sap mixed

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with coconut fiber is used for canoe caulking, glue feathers on masks (28). Dried breadfruit is obtained by drying the whole fruit in a special design oven and obtained non-perishable, easy-to-transport food can be kept safe for years. The dried fruit is consumed after pieces are dipped into tea or infusions of orange leaves. It is mostly consumed fresh as a starchy vegetable. The microencapsulation efficiency (MEE) of breadfruit and broken rice based maltodextrin was investigated as a coating material by using virgin coconut oil (VCO) as a model system (29). It was observed that all samples with dextrose equivalent (DE) value of 10-14 exhibited better microencapsulation properties than maltodextrins with DE value of 15-19.

CONCLUSION

Breadfruit is a tropical fruit which is mainly consumed as a vegetable for preparation of curry like dishes. Due to its higher nutritional value, it is a good source of energy. The high quality of starch makes it useful for the pharmaceutical industry for binding of tablets. High medicinal value makes it useful to treat hypertension, eye infection and urinary problems. It can also be used to regulate blood glucose level and prevent hunger. Thus it can be a good source for value addition in food products with good biological value.

CONFLICT OF INTEREST

The authors have declared that no conflict of interest exists.

REFERENCES

[1] Piper, J.M. (1989). Fruits of South-east Asia: Facts and folklore. Singapore: Oxford University Press, pp. 28. (Call no.: RSING 634.60959 PIP)

[2] Zerega, N.J., Ragone, D. and Motley, T.J.(2004). Complex origins of breadfruit (Artocarpusaltilis, Moraceae): implications for human migrations in Oceania. American Journal of Botany, 91(5):760-766.

[3] Zerega, N., Wiesner-Hanks, T., Ragone, D., Irish, B., Scheffler, B., Simpson, S. et al. (2015). Diversity in the breadfruit complex (Artocarpus, Moraceae): Genetic characterization of critical germplasm. Tree Genetics and Genomes, 11(1):4.

[4] Gardner, E.M., Laricchia, K.M., Murphy, M., Ragone, D., Scheffler, B.E., Simpson, S. et al. (2015). Chloroplast microsatellite markers for Artocarpus (Moraceae) developed from transcriptome sequences. Applications in Plant Sciences,3(9):1-6. (doi: 10.3732/apps.1500049)

[5] Witherup, C., Ragone, D., Wiesner-Hanks, T., Irish, B., Scheffler, B., Simpson, S. et al. (2013). Development of microsatellite loci in Artocarpusaltilis (Moraceae) and cross-amplification in congeneric species.Applications in Plant Sciences, 1(7):1-6.

[6] Sankat, C.K., and Maharaj, R.(2007). A review of postharvest storage technology of breadfruit. In I International Symposium on Breadfruit Research and Development 757:183-192.

[7] Loos, P.J., Hood, L.F. and Graham, H.D.(1981). Isolation and characterization of starch from breadfruit [Artocarpuscommunis]. Cereal Chemistry. (source: http://www.nal.usda.gov/)

[8] Worrell, D.B., Carrington, C.S. and Huber, D.J.(2002). The use of low temperature and coatings to maintain storage quality of breadfruit, Artocarpusaltilis (Parks.) Fosb. Postharvest Biology and Technology, 25(1):33-40.

[9] Rincón, A.M. and Padilla, F.C. (2004). Physicochemical properties of Venezuelan breadfruit (Artocarpusaltilis) starch. Archivoslatinoamericanos de nutricion, 54(4):449-456.

[10] Adebowale, K.O., Olu-Owolabi, B.I., kehinde-Olawumi, E. and Lawal, O.S.(2005). Functional properties of native, physically and chemically modified breadfruit (Artocarpusartilis) starch. Industrial Crops and Products, 21(3):343-351.

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[11] Adebayo, A.S. and Itiola, O.A. (2003). Effects of breadfruit and cocoyam starch mucilage binders on disintegration and dissolution behaviors of paracetamol tablet formulations. Pharmaceutical Technology, 27(3):78-90.

[12] Adebayo, S.A., Brown-Myrie, E. and Itiola, O.A.(2008). Comparative disintegrant activities of breadfruit starch and official corn starch. Powder Technology, 181(2):98-103.

[13] United States Department of Agriculture (USDA). USDA National Nutrient Database for Standard Reference (Available online: http://ndb.nal.usda.gov/) Accessed on 5October, 2015.

[14] Liu, Y., Ragone, D. and Murch, S.J. (2015). Breadfruit (Artocarpus altilis): a source of high-quality protein for food security and novel food products. Amino acids, 47(4):847-856.

[15] Jones, A.M.P., Ragone, D., Bernotas, D.W. and Murch, S.J. (2011). Beyond the Bounty: Breadfruit (Artocarpus altilis) for food security and novel foods in the 21st Century. Ethnobotany Research and Applications, 9:129-149.

[16] Whistler, W.A. (2001). Plants in Samoan Culture: The Ethnobotany of Samoa. The University of Hawaii Press, Honolulu, Hawaii.

[17] Navarro, M., Malres, S., Labouisse, J.P. and Roupsard, O. (2007) Vanuatu breadfruit project: survey on botanical diversity and traditional uses of Artocarpus altilis. In I International Symposium on Breadfruit Research and Development 757:81-88.

[18] Lans, C.A. (2006). Ethnomedicines used in Trinidad and Tobago for urinary problems and diabetes mellitus. Journal of ethnobiology and ethnomedicine, 2(1):45.

[19] Bipat, R., Toelsie, J., Joemmanbaks, R., Gummels, J., Klaverweide, J., Jhanjan, N.et al. (2008). Effects of plants popularly used against hypertension on norepinephrine-stimulated guinea pig atria. Pharmacognosy Magazine, 4(13):12.

[20] Turi, C.E., Liu, Y., Ragone, D. and Murch, S.J. (2015). Breadfruit (Artocarpus altilis and hybrids): A traditional crop with the potential to prevent hunger and mitigate diabetes in Oceania. Trends in Food Science and Technology, 45(2):264-272.

[21] Omobuwajo, T.O.(2003). Compositional characteristics and sensory quality of biscuits, prawn crackers and fried chips produced from breadfruit. Innovative Food Science & Emerging Technologies, 4(2):219-225.

[22] Esparagoza, R.S. and Tangonan, J.G.(1993). Instant baby food using banana and breadfruit flour as food base. USM CA [University of Southern Mindanao College of Agriculture] Research Journal (Philippines). (source:http://www.uplb.edu.ph)

[23] Mayaki, O.M., Akingbala, J.O., Baccus-Taylor, G.S. and Thomas, S. (2003). Evaluation of breadfruit (Artocarpus communis) in traditional stiff porridge foods. J. Food Agric. Environ, 1(2):54-59.

[24] Ayodele, M.S. and Oginni, E.O.(2002). Utilization of breadfruit (Artocarpusincisa) flour for confectionery products. Tropical science, 42(3):120-122.

[25] McHugh, T., Pan, Z., Apple E. and Films,T.A. (2007). Propertiesof Extruded Expandable Breadfruit Products. Presentedat CIGR Section VI (Postharvest Technology andProcess Engineering) 3rd International Symposium: Foodand Agricultural Products: Processing and Innovations,September 24-26, Naples, Italy.

[26] Adeniran A., H., Gbadamosi, S.O. and Omobuwajo, T.O. (2012). Microbiological and physico -chemical characteristics of fufu analogue from breadfruit (Altocarpusaltilis F). International journal of food science & technology, 47(2):332-340.

[27] Bradacs, G., Heilmann, J. and Weckerle, C.S. (2011). Medicinal plant use in Vanuatu: A comparative ethnobotanical study of three islands. Journal of ethnopharmacology, 137(1):434-448.

[28] Labouisse, J.P. (2016). Ethnobotany of breadfruit in Vanuatu: Review and prospects. Ethnobiology Letters, 7(1):14-23.

[29] Amin, Z.A., Koh, S. P., Hamid, N.S.A., Tan, C. P. and Long, K. (2017). New coating material for producing virgin coconut oil (VCO) microcapsules. Food Research 1 (1):15–22.

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Modern Techniques to Evaluate the Quality of Food Products

Chetan Dharaiya1*, Atanu Jana2 and Rekha Rani3

1Dept. of Dairy Technology, SMC College of Dairy Science, AAU, Anand 2Dept. of Dairy Processing & Operations, SMC College of Dairy Science, AAU, Anand

3Dept. of Dairy Technology, Warner College of Dairy Technology, SHUATS, AllahabadE-mail: *[email protected]

QUALITY

Food quality is the quality characteristics of food that is acceptable to the consumers. This includes external factors as appearance (size, shape, color, gloss, and consistency), texture and flavor as well as internal factors (chemical, physical, microbial) [1]. Various methods are used to ascertain the quality of food products such as sensory evaluation, determining chemical composition, evaluating the physicochemical characteristics, studying the structural and ultra-structural characteristics and assessing the microbial quality. There is bound to be developments and innovations in the methods for ascertaining food quality, with the developing pace of science and technology. International organizations like ISO also helps in assuring quality as well as reducing manufacturing cost. Good quality food products also lead to higher exports.

Methods Used to Ascertain the Food Quality

E-Sorting: Product safety is one of the most important issues facing the food processing industry. Food safety impacts consumer safety as well as brand protection. The human perception has proved very effective in the determination of quality in many foods and sorting by a human is still practiced. Electronic sorters have been developed with the advent of technology and their demand continues to increase owing to the escalating cost of manual sorting as well as higher quality requirements. There is also an increasing realization of the importance of sorting in the reduction of health hazards arising from contaminated food. A sorting machine generally consists of (i) a feed system, (ii) an inspection system, (iii) a signal processing system, and (iv) a separation system [1].

An electronic sorter is applicable in (i) removal of foreign material, (ii) separation of over- and under-ripe products, (iii) sorting on the basis of shape, (iv) separation of improperly processed food (i.e. roasted cashews), (v) separation of whole and cut grains, (vi) separation of food on the basis of size (i.e. potato)[2,3,4].

e-noSe

Electronic Neotronics Olfactory Sensing Equipment (NOSE) is an instrument which comprises of an array of electronic chemical sensors with partial specificity or broad-band chemical sensors and an appropriate pattern recognition system, capable of recognizing simple or complex odors. Foods maybe classified according to categories such as freshness and edibility. E-nose mimics the human olfactory sensory system [5].

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Instrumentation: E-Nose comprises of (i) sample delivery system, (ii) detection system, and (iii) computing system. The sample delivery system enables the generation of the headspace (volatile compounds) of a sample. The system then injects this headspace into the detection system of the e-nose. The detection system consists of a sensor set. When in contact with volatile compounds, the sensors react (i.e. experience a change of electrical properties). Each sensor is sensitive to all volatile molecules but each in their specific way. Most e-noses use sensor arrays that react to volatile compounds on contact: the adsorption of volatile compounds on the sensor surface causing a physical change of the sensor. A specific response is recorded by the electronic interface transforming the signal into a digital value. Recorded data are then computed based on statistical models. The computing system performs global fingerprint analysis and provides results and representations. A number of analysis techniques include a graphical representation of the individual sensor outputs with time; polar plots or spider plots; statistical techniques; offset polar or difference plots; neural networks [6]. The more commonly used sensors include metal oxide semiconductors (MOS), conducting polymers (CP), quartz crystal microbalance, surface acoustic wave (SAW), and field effect transistors (MOSFET)[5].

Application: E-nose is used for recognition and quality analysis of various food products such as wine [7], cola [8], meat [9], fish [10], coffee [11] and black tea [6]. It is used to monitor freshness of fish [5], identify coffee origin [12] and detect hazardous waste composition [13].

e-tongue

The electronic tongue is an analytical instrument comprising of an array of non-specific, low-selective, chemical sensors with high stability and cross-sensitivity to different species in solution, and an appropriate method of pattern recognition and/or multivariate calibration for data processing. The electronic tongue is capable of recognizing the qualitative and quantitative composition of multispecies solutions of different nature[14].

Sensors based on various sensing principles can be employed in electronic tongues, the most widespread being potentiometric, amperometric or optical sensors [15]. Chalcogenide and oxide glasses and crystalline materials have been used as membranes of potentiometric sensors [14, 16] and noble metals [17] have been used mostly for amperometric signal detection. Sensing materials based on plasticized organic polymers containing different active substances have been employed for both potentiometric [14, 15, 18] and optical sensors [19].

Applications: The applications of e-tongue includes: (i) determining the expiration date of foods [20], (ii) quantification of intensity of taste of black tea [21], green tea [22], milk [23], rice [24], pork [25] or table salt [26], and (iii) evaluation of taste of amino acids [27].

electronic eye

Colour is an important sensory attribute for acceptance of any food product. For maintaining uniform color and appearance of products, proper methods of color measurement are essential. Some of the instruments commonly used are colorimeters, spectrophotometers, comparator charts or color discs. However, objective color measurement methods have undergone significant changes in recent years with advancements in computer hardware and software and digitization technology [28, 29].

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Fundamentals of the Electronic Eye: Advancements in digital technology enabled the use of a scanner, camera, and software for color measurement. Following its origin in the 1960s, computer vision has experienced growth with its applications expanding in diverse fields not only for color measurements but also for process automation, remote sensing, robot guidance etc.[30].Computer vision and image analysis, are non-destructive and cost-effective techniques for sorting and grading of agricultural and food products during handling processes and commercial purposes [31].

Some of its applications includes: (a) visual inspection of muffins [32], (b) size, shape, colour of chocolate chip cookies [33], (c) colour of bread crust [34], (d) assess quality of meat and pork through colour [35, 36, 37, 38], (e) surface colour of apples [39], (f) track cold spots during sterilization of potatoes [40], (g) colour measurement of Kunda andKalakand[41, 42], (h) cheese browning and melting [43], (i) colour change in cheese curd during syneresis[44], (j) colour change in yoghurt during storage, prediction of shelf life [45,46], (k) determination of chocolate bloom [47], (l) quantification of colonies on petri plates [48], etc.

texture AnAlyzer

Texture analysis is primarily concerned with the measurement of the mechanical properties of a food product. The sensory properties of a food product have been related to the instrumental properties which can be calculated from the results of a two-cycle texture profile analysis test. Texture analyzers perform this test by applying controlled forces to the product and recording its response in the form of force, deformation and time [49].

The parameters analyzed by texture analyzer are hardness, apparent modulus, breaking point, bursting strength, chewiness, the coefficient of friction, cohesiveness, consistency, elasticity, fracture-force, gel strength, gumminess, pliability, relaxation, ripeness, spreadability, tackiness, adhesiveness and yield point.

In the dairy industry, texture analyzer is used to analyze texture of several indigenous dairy products (viz.,pedal, burfi, kalakand, Gulab Jamun, paneer, raosgolla, Sandesh) as well as western products (viz., cheese, butter, yogurt, tofu). It is also useful to check the ripeness of fruits like apple, carrot, guava [49, 50, 51,]; different mechanical and rheological parameters of bread crumb [52, 53]; elasticity of candy gums, viscoelasticity of gels [54]; determination of age of cheese [55], etc.

differentiAl ScAnning cAlorimetry

Differential scanning calorimetry (DSC) monitors heat effects associated with phase transitions and chemical reactions as a function of temperature. In a DSC, the difference in heat flow to the sample and a reference at the same temperature is recorded as a function of temperature. The reference is an inert material such as alumina, or just an empty aluminum pan. The temperature of both the sample and reference are increased at a constant rate. Since the DSC is at constant pressure, heat flow is equivalent to enthalpy changes [56].

In DSC, the sample and reference are connected by a low resistance heat flow path (a metal disc). The assembly is enclosed in a single furnace. Enthalpy or heat capacity changes in the sample cause a difference in its temperature relative to the reference; the resulting heat flow is

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small compared with that in the differential thermal analysis (DTA). The temperature difference is recorded and related to enthalpy change in the sample using calibration experiments [57].

The main assembly of the DSC cell is enclosed in a cylindrical, silver heating black, which dissipates heat to the specimens via a constantan disc which is attached to the silver block. The disc has two raised platforms on which the sample and reference pans are placed. The chromel-constantan thermocouples are used to determine the differential temperatures of interest. Alumel wires attached to the chromel discs provide the chromel-alumel junctions for independently measuring the sample and the reference temperature. A separate thermocouple embedded in the silver block serves as a temperature controller for the programmed heating cycle. An inert gas is passed through the cell at a constant flow rate ~ 40 ml/min)[58].

The application of DSC includes (a) measuring the melting and boiling points [59], (b) crystallisation time and temperature [60], (c) finding percent crystallinity [61], (d) specific heat capacity [62], (e) oxidative/thermal stability[63], (f) Purity of fat e.g. determination of adulteration in ghee [61]

x-rAy cryStAllogrAphy

X-rays have short wavelengths to ‘see’ the atoms and the molecular structure of molecules. Any structure can be visualized only if electromagnetic radiation of a wavelength comparable to its dimensions is used. For proteins, appropriate size is of the order of Å (10−10 m). The wavelength of X-rays approximates 1 to 100 Å. Use of X-ray crystallography (XRC) technique is useful for studying the structure of biological macromolecules [64].

XRC is the most widely used technique to obtain high-resolution protein structural information. It is the study of molecules using X-rays. Through the use of XRC, the detailed structure of molecules have been visualized and discovered by exposing a well-ordered crystal of a substance to X-rays and finally generating the structural information from the spots produced on a film due to this impact [64]. XRC relies on the dual nature (wave/particle) of X-rays to discover information about the structure of crystalline materials. The pattern produced by the diffraction of the X-rays through the closely spaced lattice of atoms in a crystal is recorded and then analyzed to reveal the nature of that lattice. This technique entails bombarding a molecule in crystalline form with a beam of X-rays. Most of these X-rays pass straight through the crystal but some are diffracted by it, resulting in a diffraction pattern recorded on a detector. The diffraction pattern is a reflection of the three-dimensional structure of a protein molecule present in the crystal. XRC can provide detailed atomic information, showing every atom in a protein or nucleic acid along with atomic details of ligands, inhibitors, ions, and other molecules that are incorporated into the crystal [65].

The application of XRC includes (a) analysis of milk stone[66], (b) chemical analysis of milk powder[66], (c) differentiation of sugars [66], (d) structure elucidation of milk proteins [67, 68, 69], and (e) polymorphism of milk fat utilizing X-Ray Diffraction and Infrared Spectroscopy [70].

nucleAr mAgnetic reSonAnce

Nuclear magnetic resonance (NMR) spectroscopy was first developed in 1946 by research groups at Stanford and M.I.T., in the USA. In the late 1940’s, physical chemists originally

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developed NMR spectroscopy to study different properties of atomic nuclei, but later found it to be useful in determining the molecular structure of organic compounds [71, 72].

Principle: The NMR phenomenon is based on the fact that nuclei of atoms have magnetic properties that can be utilized to yield chemical information. Quantum subatomic particles (protons, neutrons, and electrons) have spin. In some atoms (e.g. 12C, 16O, 32S) these spins are paired and cancel each other out so that the nucleus of the atom has no overall spin. However, in many atoms (1H,13C, 31P, 15N, 19F etc) the nucleus does possess an overall spin. If the number of neutrons and protons are even, the nucleus has no spin. If the number of neutrons plus the number of protons is odd, then the nucleus has a half-integer spin (i.e. 1/2, 3/2, 5/2); if the number of neutrons and protons are both odd, then the nucleus has an integer spin (i.e. 1, 2, 3) [73].

An NMR machine consists of (a) powerful, supercooled magnet (stable, with sensitive control, producing a precise magnetic field), (b) radio-frequency transmitter (emitting a precise frequency), (c) detector to measure the absorption of radiofrequency by the sample, and (d) recorder (to plot the output) [73].

ApplicAtion of nmr

NMR had been used for rapid analysis of fat, lactose and moisture in milk/cheese [74, 75];to differentiate cow milk and buffalo milk on the basis of capric acid content [76]; to differentiate homogenized from non-homogenized milk [74]; to investigate the structural organization of the milk fat globule membrane [77]. NMR has been used to investigate the freezing properties of ice cream with different fats incorporated [78]; to investigate the textural attributes of milk drinks [79]; to characterize fat and water in cheese [80]; to investigate the solid fat content(SFC) in anhydrous milk fat blends [81]; the diffusion of casein aggregates and casein behaviour in the renneting process [82, 83]; the properties of Mozzarella di bufalaCampana cheese [84]; stage of ripening in cheese [85]; microbial activity, lysine content, water activity and glass transition properties of milk powders [86]; and to quantitatively characterize the phospholipids from the milk fat globule membrane [87].

neAr infrA-red SpectroScopy

Near Infra Red (NIR) uses a small part of the spectrum of light between the visible and infra-red region. It is part of natural sunlight and is also produced by several light sources such as halogen car light. It is a rapid, non-destructive, less expensive and accurate method of analyzing food products [88].

NIR spectroscopy has been successfully applied to the analysis of qualitative and quantitative analysis of raw milk [88], compositional analysis of fat, protein and moisture of milk and milk products (i.e. cheese, butter milk powder) [89, 90], quantification of casein fractions in milk [91], determination of calcium content in milk and milk powder [92], determination of the fat and protein contents of lyophilized cheeses/Cheddar cheese[93, 94], estimation of free amino acids and soluble nitrogen during cheese ripening [95], to determine quality and authenticity of cheese [96], quality control during processing of Feta cheese [97], prediction of the shelf-life of Crescenza cheese [98], online monitoring of salt and moisture content of butter [99], determination of carbohydrate content in soy milk powder [100], determination of glycemic

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index of food using blood glucose sensor [101], and estimation of unfrozen liquid phase in ice cream[102].

fluoreScence SpectroScopy

Fluorescence spectroscopy, also known as Fluorometry or Spectrofluorometry is a type of electromagnetic spectroscopy which analyzes fluorescence from a sample. It involves using a beam of light, usually ultraviolet light, that excites the electrons in molecules of certain compounds and causes them to emit light; typically, but not necessarily, visible light. A complementary technique is Absorption Spectroscopy. The devices which measure fluorescence are called Fluorometers or Fluorimeters [103].

The applications of NIR spectroscopy include (a) evaluation of light-induced oxidation of dairy products during storage [104, 105]; determination of stage of ripening in cheese [106]; discrimination of raw, homogenized, pasteurized as well as homogenized and pasteurized milk; evaluation of lipid oxidation and rancidity of meat [107] and fish [108, 109]; adulteration of olive oil [110]; determination and aggregation of proteins in low-, medium- and high-heat skim milk powders [111]; determination of lactulose and furosine content in milk [112]; fluorescence properties of aromatic amino acids of proteins [113, 114], retinol [115]; and even freshness of egg [116].

SCANNING ELECTRON MICROSCOPY

Microscopy is increasingly used to study the influence of processing conditions and ingredients on food structure. Three-dimensional imaging, minimal sample intervention and in situ microscopies for dynamic studies, coupled with a greater appreciation of the power of image analysis to derive quantitative information from microscopic images are becoming more common. Scanning Electron Microscopy (SEM) is a very useful tool to visualize food structure. SEM combines the best features of light microscopy (LM) and transmission electron microscopy (TEM) [117].

In SEM, the image is formed step by step with scanning a focused electron beam across the specimen. The primary electrons penetrate the solid specimen and are deflected by a large number of elastic scattering processes. Various signals are generated as a result of the impact of the incident electrons which are collected to form an image or to analyze the sample surface. These are mainly secondary electrons, with energies of a few tens of eV, high-energy electrons back-scattered from the primary beam and characteristic X-rays [118].

The advantages of SEM include relatively simple sample preparation, a wide range of magnification, high depth of field and the fact that the image is a representation of electronic data allowing for image analysis and quantification. The disadvantages of conventional SEM techniques still exist, predominantly the difficulties associated with examining insulating specimens and the impossibility of examining hydrated samples without altering their state in some way (either drying or freezing). These sample preparation treatments introduce artifacts and, literally or figuratively, freeze the sample meaning that studies of dynamic processes must be interrupted for examination [119, 120].

SEM helps in the monitoring the effect of different processing conditions on the food product. Typical illustrative examples include the effect of temperature and air velocity on the drying

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kinetics and quality attributes of apple slices during the hot air drying [121], the effect of spray drying conditions (inlet air temperature and compressed air flow rate) and concentration of drying aids (maltodextrin and gum arabic) on the microstructure of spray dried black mulberry (Morusnigra) juice powders [122], the effect of drying conditions on mint leaves [123] and low-fat durian chips [124], the effect of freezing rate on the microstructure of strawberries [125], the effect of emulsifier on the structure of ice cream [126], the effect of emulsifying salts on the structure of processed cheese [127].

BioSenSor

A biosensor is any biological entity capable of being used to identify a response to some environmental change. It can quantitatively or qualitatively detect an analyte and generate a measurable signal. It can detect physicochemical parameters such as temperature, pH, redox potential, dissolved oxygen, carbon dioxide and certain ions [128].

Principle: A biosensor detects certain compounds through and electrical or optical signal. It consists of basically two components - a transducer and a biological element able to produce a specific reaction with the substance that is required to be measured, which should be able to generate a signal that can be detected by the transducer. Biological elements can be enzymes, antibodies, microorganisms, tissues, DNA, etc.[129].

The advantages of biosensors are high specificity, rapid measurement, simplicity, very low reagent usage, reusability of the biological element and possible online measurement [128].

The applications of Biosensors include (a) detection of the level of acid in yoghurt and soft drinks [130], (b) Ensuring food safety by detecting pathogens in milk, meat, poultry and fish [130], (c) detection of the level of alcohol in wine and beer industry [130], (d) detection of pesticides in dairy and food products [131], (e) BOD analyzers for wastewater [131].

petrifilm

A Petri film plate is an all-in-one plating system which is heavily used in many microbiology related industries and fields to culture various micro-organisms and is meant to be a more efficient method for detection and enumeration of microorganisms compared to conventional plating techniques. A majority of its use is for the testing of foodstuffs. Petri film plates are as accurate as conventional plating methods. Ingredients usually vary from plate to plate depending on the type of micro-organisms being cultured, but generally, a Petrifilm comprises of a cold-water-soluble gelling agent, nutrients, and indicators for activity and enumeration [132]. The petrifilm plates are available for performing Aerobic Plate Count, Aerobic Plate Count with Lactic Acid Bacteria, Coliform, Enterobacteriaceae, Staphylococci, Yeast & Mould and Listeria [133].

The size of a typical Petrifilm plate is 10 cm (H)×7.5 cm(W). The bottom film contains a foam barrier accommodating the plating surface. The plating surface consists of a circular area of about 20 cm2, and a top film which encloses the sample within the Petrifilm. A 1 cm × 1 cm yellow grid is printed on the back of the plate to assist enumeration. A plastic spreader is also used to spread the inoculums evenly [132, 133].

Petri film plates are cost-effective; possess simplicity, convenience, and ease of use. Petrifilm plates can be safely stacked and incubated just like Petri dishes. Since they are paper thin, more

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plates can be stacked together than Petri dishes. In some cases, Petrifilms were more sensitive in detection than standard microbiology methods, other than the case where higher sensitivity could possibly lead to an increased risk of false positive results [134].

CONCLUSION

There are numerous techniques to determine the quality of food products and there is a great scope for improvement also. The cost factor also needs consideration as the initial cost of installation is considerably high. Hence, more research is required to reduce the initial cost.

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Occurrence of Black Point Disease Complex of Wheat in Eastern Uttar Pradesh

D.N. Shukla1, J.P. Shrivastava2 and Manish Kumar Yadav3

1Department of Plant Pathology, Dr. Rajendra Prasad Central Agricultural University Pusa, Samastipur (Bihar)

2Department of Plant PathologyN. D. University of Agriculture and Technology Kumarganj, Faizabad (UP)

3Department of Entomology Dr. Rajendra Prasad Central Agricultural University Pusa, Samastipur (Bihar)

E-mail: [email protected]

ABSTRACT

Black point disease complex of wheat resulting from different types of field fungi common in different region of eastern Uttar Pradesh due to delayed sowing of farmers, intermittent rain, high relative humidity and relatively rise in temperature during anthesis stage. Therefore, an extensive survey was done in different district of Eastern Uttar Pradesh during 2012-13 to monitor wheat grain samples for black point incidence and severity. Total 26 wheat seed samples tested for knowing the seed infection percentage and range of infection in different district.During the detection maximum black point infection (3.15%) was found in the wheat variety K-9423 of Faizabad produced and minimum average infection (0.13%) was found in the variety HD-2733 of Ghazipur, Azamgarh and Siddarth Nagar produced. The fungi isolated from discolored grain was Bipolarissorokianiana, Alternaria alternata and the exceptionally the Curvularia lunata.

Keywords: Black Point, Seed Samples, Bipolaris, Alternaria, Curvularia

INTRODUCTION

Wheat (Triticum aestivum L.) belongs to family Gramineae. It is the staple food and major source of energy and nutrition of Indian diet. It is known for its remarkable adoption to a wide range of environment. Its importance derived from the properties of their gluten, cohesive network of tuft endosperm protein, starch with the expansion of fermentations dough. It is utilized for bread, cakes, cokies, noodles, pestri-products, chapatti & macaroni etc. Wheat grain contains 60-68% starch, 8.0 to 15% protein, 1.5 to 2.0% fat, 2.0-2.5% cellulose and 1.5 to 2.0% minerals [5].Wheat is infested by various seed-borne diseases in which black point is one of the most important seed-borne disease of wheat which induces qualitative loss. Black point, defined as the discolouration of the embryo end and surrounding areas of the wheat kernel, occurs any time from grain filling to near harvest. Various fungi that cause black point often occur on developing kernels that do not exhibit symptoms. Since the first report of black point of wheat in the United States in 1913, it has been reported in other wheat growing countries [2]. Wheat kernel discoloration is due to fungal invasion and termed as black point [1]. Black point disease of wheat was first time in reported in India by Dastur [2]. Black point caused mainly by Bipolaris sorokiniana, Alternaria alternata, Cladosporium cladosporioides,

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Occurrence of Black Point Disease Complex of Wheat in Eastern Uttar Pradesh 77

ISBN: 978-93-88237-24-6

Curvularia lunata and Fusarium spp. is one of them [3]. The disease occurs almost all over the world wherever wheat is grown. Black point infection becomes severe when prolonged wet weather prevails during grain filling period of the crop. Black point has an adverse effect on seed weight, germination, and seedling emergence [4,6].

MATERIAL AND METHOD

Narendra Deva University of Agriculture and Technology, Kumarganj, Faizabad has a well-equipped notified Seed Testing Laboratory under the Department of Seed Science & Technology. Samples of different release and notified varieties meant for quality seed production purposes i.e. nucleus, breeder, foundation and certified seed at different seed production farms/Krishi Vigyan Kendra of the University established at different location in eastern U.P. are collected and analyzed for testing against seed quality traits like germination, physical purity, genetic purity, seed vigor, seed health etc. Total 26 seeds samples comprising 11 released and notified varieties under university seed production chain were available in the seed testing lab from the produce of Rabi 2012-13. A part from the said seed samples was obtained and analyzed for black point complex. The black pointed seeds were categorized based on the symptoms on the grain. Thus collected samples were thoroughly mixed to form composite sample in Boerner type divider, to ensure homogeneity. Thereafter, a working sample of 250 g was drawn from each sample for conducting studies. Out of the working sample, 2000 seeds were drawn randomly and spread on purity board for the analysis of black point incidence. Percent infected samples, as well as percent infection, was calculated as follows: The percent disease incidence was calculated by using the formulae :( Number of samples having black point grains /Total No. of samples) X 100. The level of disease severity in each of the samples was calculated by the formulae: Severity= (Number of black point grains in a sample/2000) X 100.

RESULTS

Total 26 seed samples of newly released wheat varieties grown at different locations like Faizabad, Sultanpur, Bahraich, Basti, Barabanki, Sidharth Nagar, Mahrajganj, Ghazipur and Azamgarh under quality seed production programme and submitted to the Notified Seed Testing laboratory of the Department of Seed Science and Technology, N.D. University of Agriculture & Technology, Narendra Nagar (Kumarganj) Faizabad. A part of these samples was obtained from the set laboratory and analyzed for a black point of wheat. The black point infected seeds were categorized on the basis of conversion of the grain part. Besides, infected seeds were subjected to pathogenic association also.

Four samples of wheat varieties PBW 502 produced in Bahraich, Faizabad, Sultanpur, and Mahrajganj districts analyzed. Out of four samples, one samples from Mahrajganj were found infected (0.25%), from Bahraich(0.30%), Faizabad (0.35%) and Sultanpur (0.20%). Thus, the range of black point infection was 0.20 to 0.35 percent with an average infection of 0.27 percent. The fungi which were found associated with back point infected grain were Alternaria alternate and Bipolaris sorokiniana and Curvularia lunata (Table-1).

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Table 1: Incidence and Severity of Black Point in Wheat Varieties of Eastern Uttar Pradesh

S.N. Variety Production Site Percent Seed Infection (BP Average)

Pathogenic Associations (Fungi Isolated) Descending Order

1.a) PBW502 Bahraich 0.30 Alternaria alternata Bipolaris sorokiniana

b) PBW502 Faizabad 0.35 Curvularia lunata

c) PBW502 Sultanpur 0.20 Alternaria alternata

d) PBW502 Maharajganj 0.25 Alternaria alternata B. sorokiniana

Total/average 4 districts 1.10/0.27 A. alternata B.sorokiniana

2.a) PBW550 Bahraich 0.25 B.sorokiniana

b) PBW550 Faizabad 0.20 A.alternata

c) PBW550 Basti 0.30 B.sorokiniana

d) PBW550 Siddarth Nagar 0.25 B.sorokiniana, A.alternata

Total/average 4 districts 1.00/0.25 B.sorokiniana, A.alternata

3.a) Raj 3077 Barabanki 0.50 A.alternata, B.sorokiniana

b) Raj 3077 Faizabad 0.25 B.sorokiniana, A.alternata

c) Raj 3077 Sultanpur 0.25 B.sorokiniana, C. lunata

Total/average 3 districts 1.00/0.33

4.a) K-7903 Faizabad 0.30 B.sorokiniana, A.alternata

b) K-7903 Sultanpur 0.20 B.sorokiniana

c) K-7903 Barabanki 0.25 B.sorokiniana


5.a) HD2733 Ghazipur 0.10 B.sorokiniana

b) HD2733 Azamgarh 0.10 B.sorokiniana

c) HD2733 Siddarth Nagar 0.20 A.alternata


6.a) PBW 343 Faizabad 0.30 A.alternata

b) PBW 343 Sultanpur 0.30 B.sorokiniana

c) PBW 343 Faizabad 0.35 B.sorokiniana

Total/average 3districts 0.90/0.30

7.a) NW 1012 Faizabad 0.35 B.sorokiniana

b) NW 1012 Barabanki 0.30 B.sorokiniana


8.a) K 307 Faizabad 0.15 B.sorokiniana, A.alternata

9.a) K-9423 Faizabad 3.15 A.alternata, B.sorokiniana

10.a) DBW17 Faizabad 1.20 B.sorokiniana, A.alternata C. lunata

11.a) UP262 Barabanki 1.35 A.alternata

Total no. of seed samples = 26; Total no. of districts = 9; No. of infection range =0.10-3.15%

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Table 4: Effect of Sowing Dates and Variety on Test wt. and Karnal Bunt of Wheat

Date of sowing 1000 grain wt.(gm) KB infection

5-11 Nov. (D1) 35.19 0.01

12-18 Nov. (D2) 35.20 0.03

19-25 Nov. (D3) 35.33 0.00

SEm± 0.257 0.006

CD 5% 0.753 0.017

Variety

HD-2733 (V1) 36.16 0.00

PBW-343 (V2) 36.62 0.04

K-307 (V3) 31.40 0.00

PBW 39(V4) 36.78 0.01

SEm± 0.296 0.007

CD5% 0.513 0.020

Table 5 : Effect of Fertilizer doses and Varieties on the Incidence of Karnal Bunt of Wheat

Fertilizer doses 1000 grain wt. KB infection

40 kg N(N1) 41.54 0.00

60 kg N (N2) 41.92 0.00

80 kg N (N3) alongwith basal dose of P2O5 @ 30 kg/ha-1 42.43 0.00

SEm± 0.202 0.002

CD 5% 0.594 NS

Variety

HD-3070 41.89 0.00

C-306 41.88 0.00

K-8027 42.07 0.02

HD-2888 42.01 0.00

SEm± 0.234 0.003

CD5% 0.686 0.008

Table 6: Efficacy of Fungicides N. indica (Percent Inhibition to Radial Growth)

Percent Inhibition to Radial Growth

Fungicides Concentration (% a.i.)

0.1% 1.0% 2.5%

T1- Carboxin (Vitavax 75 WP) 15.10(22.87)**

24.23(29.49)

31.67(34.24)

T2- Carbendazim (Bavistin 50 WP) 17.17(24.48)

26.27(30.83)

33.11(35.07)

T3- Carbendazim-Subeej (Bavistin 25 SD) 12.09(20.34)

21.33(27.37)

28.38(32.19)

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Percent Inhibition to Radial Growth

Fungicides Concentration (% a.i.)

0.1% 1.0% 2.5%

T4- Propiconazole 20 EC (Tilt 20EC) 19.30(26.06)

27.72(31.77)

38.23(38.19)

T5- Vitavax Power (Crop Uni Royal) 14.20(22.14)

23.85(29.24)

32.53(34.78)

Control *

Factors CD at 5%Fungicides (F) 0.957Concentration (C) 0.256F x C 0.572* Radial growth in check 39.00 mm. check consisted of the medium without fungicides.** Values given in parenthesis are angular transformed values.

Four samples of wheat varieties PBW 550 produced in Bahraich, Faizabad, Basti, Siddarth Nagar districts analyzed. Out of four samples, one sample from Siddarth Nagar was found infected (0.25%) and the others from Bahraich(0.25%), Faizabad(0.20%) and Basti(0.30%) were found infected with black point infection. Thus the range of black point infection was 0.20 to 0.30 percent with average infection of 0.25 percent. The fungi which were isolated prominently from the infected grains were Alternaria alternate and Bipolaris sorokiniana.

Three samples of wheat variety Raj 3077 produced in Barabanki(0.50%), Faizabad(0.25%) and Sultanpur(0.25%) districts were analyses. All the three samples were found infected with black point ranging between 0.25 to 0.50 percent with average infection of 0.33 percent. The fungi which were isolated from the infected grains were Alternaria alternate, Bipolaris sorokiniana, and Curvularia lunata.

Three samples of wheat varieties K.7903 (Halna) produced in Faizabad, Sultanpur and Barabanki districts analyzed. Out of three samples, all samples were found infected one from Faizabad (0.30%) and the other from Barabanki (0.25%). The produce of Sultanpur(0.20%) was also found infected with black point infection. Thus, the range of black point seed infection was 0.20 % to 0.30% percent with an average infection of 0.25 percent. The fungi which were isolated prominently from the infected grain were Alternaria alternate and Bipolaris sorokiniana.

Three samples of the wheat variety HD 2733 produced in Ghazipur, Azamgarh and Siddarth Nagar districts analyzed. All the samples were found infected with a black point. Out of three samples, one sample was found infected with black point in Ghazipur(0.10%) and two samples were produced from Azamgarh and Siddarthnagar were also found infected with 0.10% and 0.20% respectively. All the three samples were found infected with black point ranging between 0.10 to 0.20 percent with average infection of 0.13 percent. The fungi isolated from infected grains were Biopolaris sorokiniana and Alternaria alternata.

Three samples of wheat variety PBW 343 produced in Faizabad and Sultanpur districts analyzed. Out of three samples, two sample from Faizabad were found infected (0.30%) and other 0.35% produce from Sultanpur(0.25%) was also infected with black point infection. All the three seed lots were found infected with black point ranging between 0.25 to 0.35

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percent with average infection of 0.30 percent. The fungi isolated from the infected grains were Alternaria alternate and Bipolaris sorokiniana.

Two samples of wheat varieties NW 1012 produced in Faizabad and Barabanki district was analyzed and found infected with black point (0.35%)and (0.30%) respectively All the two seed lots were found infected with black point ranging between 0.30 to 0.35 percent with average infection of 0.32 percent. The fungi isolated from the infected grains was Bipolaris sorokiniana.

One sample of wheat varieties K-307 produced in Faizabad district was analyzed and found infected with black point (0.15%). The fungi isolated from the infected grains were Bipolaris sorokiniana and Alternaria alternata.

One sample of wheat variety K-9423 produced in Faizabad district was analyzed found infected with black point which was 3.15 per cent. The fungi isolated from the infected grains were Alternaria alternata and Bipolaris sorokiniana.

One sample of wheat variety DBW-17 produced in Faizabad was analyzed and found infected with black point, which was 1.20 per cent. The fungi isolated from infected grains were Bipolaris sorokiniana, Alternaria alternata and Curvularia .One sample of wheat variety UP-262 produced in Barabanki was analyze and found infected with black point which was 1.35 per cent respectively. The fungi isolated prominently from the infected grain was Alternaria alternata.

DISCUSSION

Since the information of black point incidence in the districts surveyed was based on the variable number of wheat grain samples received seed samples in seed testing laboratory of N.D. University of Agriculture and Technology Kumarganj, Faizabad. Black point was widely distributed in various districts of eastern Uttar Pradesh. Present investigation showed that the wheat variety K-9423 was infected from black point with 3.15% seed infection followed by Raj-3007 with average infection 0.33 per cent, whereas the wheat verities NW 1012(0.32%), PBW 343(0.30%), PBW 502(0.27%), K-7903(0.25%) and PBW 550(0.25%) were found average seed infection. A trace level of average seed infection was found in the wheat variety HD-2733(0.13%) and in the variety K 307 showed the 0.15% seed infection. Based on the overall black point occurrence, it emerged that Black point incidence is common in the Eastern Uttar Pradesh and depend on the susceptible wheat varieties, time of sowing and weather condition.

CONCLUSION

Black point disease complex of wheat caused by Bipolaris sorokiniana is become alarming conditions in seed production areas of wheat in eastern Uttar Pradesh. As we know that,disease causes discolouration on the seeds which reduce the visible quality as well as reduce market price. Weather condition like intermittent rains, high relative humidity and particularly rise in temperature at the anthesis stage helped the pathogen to cause the disease in wheat verities because the pathogen is seed borne. Frequent rainfall from milk to soft dough stage, late season irrigation and lodging often trigger infection by these seed-inhabiting fungi.

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REFERENCES

[1] Bolley H.L. (1913) Wheat: soil troubles and seed deterioration, North Dakota Agriculture Experiment Station Bulletin, North Dakota, 107.

[2] Dastur F.J. (1932) Agriculture Livestock in India, 2, 275–282.[3] Fakir GA. Black point disease of wheat in Bangladesh. 2nd Edition. Seed Pathology Laboratory,

Bangladesh Agricultural University, Mymensingh. 1998, 81.[4] Khanum M, Nigar Y, Khanzada AK. Effect of black point disease on the germination of wheat

varieties. Pakistan J Agril. Res. 1987; 8 (4):467–473.[5] Rathore PS. Techniques & management of field crop production, 1st edn. Agrobios (India)

Jodhpur, 2001, 96120.[6] Rahman GMM, Islam MR. Effect of black point of wheat on some qualitative characters of its grain

and seed vigour. Bangladesh J Agril. Res. 1998; 23(2):283–287. [7] Watkins J.E. & Prentise L.J. (1997) Black point disease of wheat, Neb Guide, Publ. Institute of

Agriculture and Natural Resources, Lincoln Extension, University of Nebraska, U.S.A.

APPENDIX-I

Meteorological Data (Weekly average) During Investigation Period (2011–12).

Month Standard weeks

Temperature Average Relative Humidity (%)

Wind Speed (km/ha)

Sunshine (Hrs.)

Rainfall (mm)Min. Max.

January 3 7.9 21.0 77.2 3.2 3.3 001.4

4 5.5 22.2 71.5 3.7 7.0 000.0

February 5 5.0 23.0 72.3 3.5 7.3 000.0

6 6.6 22.9 74.7 4.1 5.9 015.2

7 8.6 24.3 67.7 3.1 5.0 000.0

8 11.0 27.5 64.8 3.5 8.3 000.0

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A Detailed Review of Biomass Energy and its Challenges and Impact on the Environment

Devanshu Agnihotri1 and Mamta Sagar2

1,2Department of Bioinformatics, UIET, Chhatrapati Shahu Ji Maharaj University, U.P., India

ABSTRACT

Plants utilize solar energy to synthesize food during photosynthesis as it provides biomaterials, needs for generation of bioenergy. A byproduct of natural and biological sources can be used as a source of bioenergetics, it can be a good replacement for carbon energy or fossil fuel. In this article, a variety of biomasses are discussed which include wood and agriculture products, solid waste, landfill gas, biogas. Biomass fuels are sustainable, efficient and viable. Biomass energy can be generated from waste material also which provide an efficient way of waste management. In the coming years will be a small but significant part of the energy.

Keywords: Biomass, Solar Energy, Biomaterials, Photsynthesis, Fossil Fuel

INTRODUCTION

Bio-energy

Some natural and biological sources are eligible for producing energy which can be classified as bio-energy which is a form of renewable energy. Byproducts of different ordinary sources such as plants, animals etc can be important in contributing in the processing bio-energy. Modern technology like abandon coal mine, dumping ground, pits creates by mines etc even makes landfills or waste zones potential bio-energy resources. These areas are suitable for the collection of biomass. Heat, fuel, and gas can be produced from such land which is also a sustainable power source. Energy production by plant occurs during photosynthesis with the help of sunlight which can be replenished and considered as an unlimited source. The greatest source of carbohydrate biomass is photosynthesis as it provides biomaterials used for bio-energy generation.

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Bio-energy can be a good replacement for carbon energy. There are many sources of bio-energy, but the most common are forests, agricultural farms, and waste. These contribute in large quantity and can use again. For the source of energy, farmers cultivate sugar and starch-rich crops which provide them with a sufficient amount of energy. These crops include sugarcane and corn which are a good source of starch and sugar. (16) Bio-energy is a good alternative for fossil-based fuel. Fossil-based fuel mainly consists of hydrocarbon which is highly toxic. Bio-energy has the potential to decrease carbon marks and improve the environment. The amount of carbon utilized by bio-energy and fossil fuel is more or less the same, but the impact by bio-energy can be decreased as long as the plants used are replaced. (16) Petrol and diesel which are extensively used as transportation fuels are overcome by bio-energy. Use of woods for generating energy is also decreasing as the use of bio-energy is becoming prominent and effective in urban as well as rural areas. Different developed countries are accepting this trend which can help in the development of domestic industries and can increase the scale of economic growth. Though this trend is popular in developed countries, it is still recessive in developing countries where traditional biomass is often dominant domestic fuel, especially in more rural areas. Table 1 describes the estimated trade of bThere are multiple challenges and opportunities which affect the sustainable development of bio-energy as a potential driver, given enough economic and technological support. (2)

Table 1- Estimated International Biomass Trade between 2004–2011

CLASSIFICATION AND SOURCE OF BIO-ENERGY

Collection of different resources constitutes to the source bio-energy and its usage varies from continent to continent and from country to country. However, the bio-energy is considered as a worldwide power in recent time because of increase in the trade of biomass for transport. Biomass can mainly be supplied through three different sources i.e. agriculture, forestry, and waste materials. Most of the countries utilize resources from these sources to develop a sector for modern bio-energy plant.

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A Detailed Review of Biomass Energy and its Challenges and Impact on the Environment 85

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BIOMASS

Any organic matter like woods, crops etc that is utilized as an alternate form of energy is known as biomass. It is also a renewable form of an energy source as its supplies are not limited. It is considered one of the ancient sources of energy after the sun. For years, people use the wood by burning it to prepare their food and warm their homes. Biomass gets its energy from the sun. All organic matter contains stored energy from the sun. During the photosynthesis process, sunlight gives energy as photons to plants which are used by them to produce oxygen and sugar by converting Co2 and water. Foods rich in carbohydrates are a good source of energy for the human body.

Types of Biomass (5)

Municipal & Fig. 2: Biomass as Renewable Feedstock

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WOOD & AGRICULTURAL PRODUCT

This category includes wood—sawdust, logs, chips, and barks —accounts for maximum percent of biomass energy. The waste product from agricultural is used to produce electricity which includes wood, wood waste, pits, and corncobs. Electricity in paper mills is created by the waste product generated during the processing.

SOLID WASTE

Solid waste is blistered to produce waste which is used to produce energy. Not all biomass is garbage: as a maximum of its energy comes from plastics waste produced from natural gas and petroleum. Waste energy plants are power plants which produce energy by burning the waste. These plants produce electricity equally as coal plants do, but the combustion rate is lower in waste energy plant as compared to a coal plant.

LANDFILL GAS & BIOGAS

Some microorganism like bacteria and fungi depends on dead and decaying matter. They eat dead animal and plants, causing them to rot or decay. It depends on sugar which is produced from alteration of cellulose to feed itself. Even though the process in a landfill is slowed, still the methane gas is extracted as the waste product. Methane is odorless, colorless and harmful gas which is highly inflammable and can cause an explosion. This gas is collected in a landfill, purified and used as fuel. Human and agriculture waste are being used to synthesize methane gas. The biogas plant is an airtight pit or containers creased with bricks or steel. (17) Bio-gas containers collect waste which is fermented in anaerobic condition to produces gas rich in methane. This gas has several advantages like it can be utilized for cooking and to produce electricity.

Fig. 3: Fixed Dome Bio-gas Plant

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ETHANOL: SUGAR CANE (18)

Ethanol is an ethyl alcohol fuel derivative which is produced by fermenting starch and sugars found plants. It can be produced from an organic material containing starch, sugar, and cellulose. One of the major sources for ethanol production is corn. With innovative technologies, ethanol is produced from cellulose in grasses, trees, and crop residues. Normal fuel like diesel is blended with ethanol which increases its efficiency. Fuel mixed with 15% gasoline and 85% ethanol qualifies as an alternative fuel.

BIODIESEL

Biodiesel is manufactured by reacting an alcohol with animal fat, vegetable oil, and grease chemically. Most biodiesel today is made from soybean oil. It is often mixed with petrol and diesel in ratio 2:5:20. It can also be used as its purest form. Sulfur content is almost zero in biodiesel, therefore, it is helpful in reducing sulfur levels in the environment.

ADVANTAGES AND DISADVANTAGES OF BIOMASS ENERGY:

There are some pros and cons of biomass energy which are discussed below. (6)

No. Advantage Disadvantage

1Biomass energy is an abundant, secure, environmentally friendly and renewable source of energy.

Biomass is still an expensive source of energy, both in terms of producing biomass and converting it into alcohols, as a very large quantity of biomass is needed.

2 Biomass does not add carbon dioxide to On a small scale, there is most likely a net

the atmosphere as it absorbs the same amount of carbon in growing as it releases when consumed as a fuel.

loss of energy as a lot of energy must be used for growing the plant mass; biomass is difficult to store in the raw form.

3Biomass can be used to generateelectricity with the same equipment or in the same power plants that are now burning fossil fuels.

One of the disadvantages of biomass isthat direct combustion of biomass can be harmful to the environment as burning biomass releases carbon dioxide, which contributes to the warming of the atmosphere and possible climatic change.

4

Biomass energy is not associated with environmental impacts such as acid rain, mine spoils, open pits, oil spills, radioactive waste disposal or the damming of rivers.

Over-collecting wood can destroy forests. Soils bared of trees erode easily and do not hold rainfall. Increased runoff can cause flooding downstream.

5

Biomass fuels are sustainable. The green plants from which biomass fuels are derived fix carbon dioxide as they grow, so their use does not add to the levels of atmospheric carbon. In addition, using refuse as a fuel avoids polluting landfill disposal.

When plant and animal wastes are used as fuel, they cannot be added to the soil as fertilizer. Soil without fertilizer is depleted of nutrients and produces fewer crops.

6 Alcohols and other fuels produced by biomass are efficient, viable, and relatively clean burning.

Biomass has less energy than a similar volume of fossil fuels

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BIOMASS IN ASIA

Biomass is becoming an essential source of energy in the south-east part of Asia. Though biomass is a popular source for energy still the use of woods for fuel dominates in 50 percent of the continent. By country, the primary biomass energy supply share in the year 1999 was: Myanmar 86%; Lao PDR - 86%; Cambodia - 83%; Vietnam - 48%; Indonesia - 29%; Philippines

21%; Thailand - 17%; and Malaysia - 8%.(14) Biomass energy is largely utilized in small-scale industries and in the household sector. Recently, biomass is used in combination with heat and power generation. The role of biomass is limited in power development, but there are opportunities that can increase its share (15).

As the population in India is increasing its energy demand is also increasing. (Ravindranath and Balachandra, 2009). Energy consumption in India has increased to 42.1% per capita. As the country has a large agriculture land, availability of biomass is high; therefore burning this biomass is the easiest and oldest method to generate energy. (14) Over 70% of the population of India lives in villages but it is these villages neither get electricity nor water supply. (19) These supplies are essential for the lives of humans, therefore, methods should be developed to fulfill these demands. Therefore biomass found in the villages must be utilized to fulfill the demands. Gasification of biomass offers large scope for electricity production and water pumping in India.

ENVIRONMENTAL IMPACT AND CHALLENGES OF BIOMASS ENERGY

Environmentally, biomass has more advantages than fossil fuels such as petroleum and coal. It contains less nitrogen and sulfur than fossil fuel; therefore, it does not cause acid rain. Growing plants for use as biomass fuels may also help keep carbon dioxide levels balanced. Plants help in the removal of Co2 from the atmosphere when they grow.

There are many challenges in the production of biomass energy technology. The most critical challenge for the biomass industry is food security.(20) Biofuels is accountable for a rapid price

increase of grains for decades in the international markets(21). Grains were exported to the production plants from the market for the biofuel production.(22) Eventually, the high price of food decreased the supply of food resulted in serious productivity, health conditions.(23) The cellulosic biomass technique allows producers to have an extensive diversity of crops for biomass production. Several cropping techniques are being developed by scientists to produce biomass, including perennial and annual species of plants species (24). Due to the comprehensive carbon cycle, these cropping methods helps in the reduction of soil erosion and nitrogen loss(24). The only barrier for these cropping technologies is deficient in of a conventional market. (25) Villamil et al.(25) advocated environmental campaigns should be organized to increase awareness and education on energy crops. In addition, harvesting cellulosic biomass requires removal of plant residues(26). Producers are concerned about how the simultaneous harvest of grain and stover will affect grain productivity, soil quality, and long-term sustainability Furthermore, the storage and transportation of cellulosic biomass are different from grains.(29) Biomass quality is also examined by its ash content and gross energy(30). There are no reviews or research articles indicating that there are developmental plans of cellulose biomass market.(31) Meyer (30) indicated increased biomass production can lead to noticeable consequences on water consumption. Quality of water is also affected by agricultural drainage containing pesticides

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and fertilizer sediments (32). Cultivation of low -water-consuming crops can be an alternative (31). There are many critical conversations among researcher, educators, and producer in how to make biomass energy production more environment-friendly (33).

CONCLUSION

In the coming years, biomass energy will be a small but significant part of Asia’s energy. If this technology is well regulated and managed, it can be very advantageous for society. This energy can be a good alternative to fossil fuel like coal and petroleum. These fuels are very harmful to

the environment which can cause a serious issue. These fuels need to be replaced to save the environment for the future. Biomass energy can be generated from waste materials also, therefore, utilization of waste material can also help in waste management. There are many benefits of biomass energy which can be considered in present to build a better future.

Apart from benefits, there are many negative impacts which cannot be ignored. Thought these industries provide employment and help economically and socially, there are many environmental issues which are a matter of concern. These problems can be overcome if the biofuel production is handled carefully. Deforestation and intensive monoculture can also be a serious issue affecting the livelihoods. Watersheds and carbon sinks could be annihilated, and various forms of wildlife could become extinct. Rising food prices could lead to political instability, as well as malnutrition and disease.

This review article fosters the dialog among the various experts in biomass and trade. Biomass-based energy can only be achieved by interdisciplinary integration of all aspects from agronomy and forestry, industrial ecology to technology development, government policies and international trade.

REFERENCES

[1] Olsson, Olle. “The Swedish biofuel market: studies of Swedish foreign biofuel trade and of the consequences of hurricane Gudrun.” (2006).

[2] Silverwood A, Canadian Biomass Magazine.[3] Petroleum, British. “BP Statistical Review of World Energy June 2015, 2015.” URL: http://www.

bp. com/content/dam/bp/pdf/energy-economics/statistical-review-2015/bp-statistical-review-of-world-energy-2015-full-report. pdf(2015).

[4] WORLD ENERGY COUNCIL | WORLD ENERGY RESOURCES 2016 https://www.worldenergy.org/wp-ontent/uploads/2017/03/WEResources_Bioenergy_2016.pdf

[5] http://www.need.org/files/curriculum/infobook/BiomassS.pdf[6] www.bchydro.com[7] Renewable Energy Network for the 21st Century (REN21). Renewable 2007 Global Status Report.

Paris: REN21 Secretariat and Washington, DC: Worldwatch Institute; 2008[8] Renewable Energy Network for the 21st Century (REN21). Renewable 2006 Global Status Report.

Paris: REN21 Secretariat and Washington, DC: Worldwatch Institute; 2007.[9] Yusuf, N.N.A.N., Siti Kartom Kamarudin, and Z. Yaakub. “Overview on the current trends in

biodiesel production.” Energy conversion and management 52.7 (2011): 2741-2751.[10] Juan, Joon Ching, et al. “Biodiesel production from jatropha oil by catalytic and non-catalytic

approaches: an overview.” Bioresource Technology 102.2 (2011): 452-460.[11] Demirbas, Ayhan. “Importance of biodiesel as transportation fuel.” Energy policy 35.9 (2007):

4661-4670.

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[12] Silitonga, A.S., et al. “A review on prospect of Jatropha curcas for biodiesel in Indonesia.” Renewable and Sustainable Energy Reviews 15.8 (2011): 3733-3756.

[13] Puppan, Daniel. “Environmental evaluation of biofuels.” Periodica polytechnica social and management sciences 10.1 (2002): 95–116.

[14] Sriram, Nisha, and Mohammad Shahidehpour. “Renewable biomass energy.” Power Engineering Society General Meeting, 2005. IEEE. IEEE, 2005.

[15] Overview of Biomass Power Generation in South East Asia www.asem-greenippnetwork.net[16] Olsson, Olle. “The Swedish biofuel market: studies of Swedish foreign biofuel trade and of the

consequences of hurricane Gudrun.” (2006).[17] Yu, Liu, et al. “Popularizing household-scale biogas digesters for rural sustainable energy

development and greenhouse gas mitigation.” Renewable Energy 33.9 (2008): 2027-2035.[18] http://www.need.org/files/curriculum/guides/secondary%20energy%20infobook.pdf[19] Zhou, Adrian, and Elspeth Thomson. “The development of biofuels in Asia.” Applied Energy 86

(2009): S11-S20.[20] Koizumi, T. Biofuels and food security. Renew. Sustain. Energy Rev. 2015, 52, 829–841. [CrossRef][21] Rosegrant, M.W. Biofuels and Grain Prices: Impacts and Policy Responses. Available

online: http://www.grid.unep.ch/FP2011/step1/pdf/004_Rosegrant_2008.pdf (accessed on 5 March 2018).

[22] Chakrabortty, A. Secret Report: Biofuel Caused Food Crisis. Available online: https://www.theguardian.com/environment/2008/jul/03/biofuels.renewableenergy (accessed on 5 March 2018).

[23] Lee, R.A.; Lavoie, J.-M. From first- to third-generation biofuels: Challenges of producing a commodity from a biomass of increasing complexity. Anim. Front. 2013, 3, 6–11. [CrossRef]

[24] Fewell, J.E.; Lynes, M.K.; Williams, J.R.; Bergtold, J.S. Kansas farmers’ interest and preferences for growing cellulosic bioenergy crops. J. ASFMRA 2013, 76, 132–153.

[25] Villamil, M.B.; Silvis, A.H.; Bollero, G.A. Potential miscanthus’ adoption in Illinois: Information needs and preferred information channels. Biomass Bioenergy 2008, 32, 1338–1348. [CrossRef]

[26] Demirba¸s, A. Biomass resource facilities and biomass conversion processing for fuels and chemicals. Energy Convers. Manag. 2001, 42, 1357–1378. [CrossRef]

[27] Karlen, D.L.; Kovar, J.L.; Birrell, S.J. Corn stover nutrient removal estimates for central Iowa, USA. Sustainability 2015, 7, 8621–8634. [CrossRef]

[28] Cantrell, K.B.; Novak, J.M.; Frederick, J.R.; Karlen, D.L.; Watts, D.W. Influence of corn residue harvest management on grain, stover, and energy yields. BioEnergy Res. 2014, 7, 590–597. [CrossRef]

[29] Singh, J.; Gu, S. Commercialization potential of microalgae for biofuels production. Renew. Sustain. Energy Rev. 2010, 14, 2596–2610. [CrossRef]

[30] Meyer, P.E. Biofuel Review Part 5: Impact onWater and Biodiversity. Available online: http://te.ieeeusa.org/2010/Nov/biofuels-pt5.asp (accessed on 5 March 2018).

[31] Dominguez-Faus, R.; Powers, S.E.; Burken, J.G.; Alvarez, P.J. The water footprint of biofuels: A drink or drive issue? Environ. Sci. Technol. 2009, 43, 3005–3010. [CrossRef] [PubMed]

[32] Hennig, A.; Kleinschmit, J.R.G.; Schoneberg, S.; Löffler, S.; Janßen, A.; Polle, A. Water consumption and biomass production of protoplast fusion lines of poplar hybrids under drought stress. Front. Plant Sci. 2015, 6. [CrossRef] [PubMed]

[33] Fritsche, U.R.; Hennenberg, K.J.; Wiegmann, K.; Herrera, R.; Franke, B.; Köppen, S.; Reinhardt, G.;Dornburg, V.; Faaij, A.; Smeets, E. Bioenergy Environmental Impact Analysis (BIAS): Analytical Framework. Available online: http://www.fao.org/3/a-am303e.pdf (accessed on 5 March 2018).

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Poly Low Tunnel Technology for off Season Tomato Cultivation with Drip Irrigation and Fertigation for Crop Diversification in Bundelkhand, UP

Shweta Soni*, Govind Vishwakarma and Pintu Meena PahadiDepartment of Vegetable Science, BUA & T, Banda (U.P.) 210001

Department of Horticulture, DCAST, Selaqui, Dehradun (U.K.) 248011E-mail: *[email protected]

ABSTRACT

Vegetables play a major role in Indian agriculture by providing food, nutritional and economic security and more importantly, producing higher returns per unit area in time. In addition, vegetables have higher productivity, shorter maturity cycle, high value and provide greater income leading to improved livelihoods. Bundelkhand region of Uttar Pradesh is predominantly vegetarian and therefore, the bulk of the population depends upon vegetables. However, the production of vegetables in the state is not keeping pace with the population growth and it has remained stagnant causing declining per capita availability of vegetables and the reason is predominantly use of years back technology and cultivation practices is also traditional leading to low productivity. There are different ways to revive from this situation. Bringing additional area under vegetable cultivation, use of hybrid seed and use of improved agrotechniques like growing of vegetables under polytunnels are some of the important ways to increase the vegetable production. In the absence of storage infrastructure and vegetable processing industry in the country, off-season vegetable farming is the only viable option that can add value to the farmers produce. Use of polytunnels has been effective to rise the off-season crop. Therefore, this is suggested that drip irrigation system has a greater scope for the production of off-season vegetables grown under plastic tunnel especially in the water-scarce area of Bundelkhand. In order to encourage early vegetable production and capture the profitable early market, growers can use plastic tunnels.

Keywords: Poly Low Tunnel, High-value Crop, Drip Irrigation, Fertigation, Offseason

INTRODUCTION

Polytunnels are miniature structures producing greenhouse—like effect. These tunnels facilitate the entrapment of carbon dioxide, thereby enhancing the photosynthetic activities of the plant that help to increase yield. Besides being inexpensive, these structures are easy to construct and dismantle. These tunnels have been used for producing healthy and high—value crops. High—value crops (HVCs) are those which give significantly higher value productivity or net income per unit of resource used for their production, compared to other competing activities. Prospects for High—Value Crops with the rise in per capita income, demand for vegetables will continue to grow. Demand projections through 2020 show that diversification in consumption patterns towards high—value agriculture products will become more pronounced with income growth and changes in other determinants such as urbanization. Also, globalization may further create opportunities for the export of high—value commodities.

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Bundelkhand region comes under semi—arid zone and now a day’s facing the problem of drought. In water shortage areas the best way of irrigation is drip irrigation. Drip irrigation improves the water use efficiency if fertilizers are applied through drips as fertigation and offers more splits of fertilizers, even micronutrients can be used, through the initial growth periods.

Tomato (Lycopersiconesculentum) belongs to the family Solanaceae is one of the most popular and widely grown vegetables in the world ranking second in importance to potato in many countries. Because of its wider adaptability and versatility, it is grown throughout the world either in outdoors or indoors. So, keeping in view the above importance of tomato if it is grown in Bundelkhand region under polytunnel in offseason using drip irrigation is the best option for farmers to overcome the adverse climatic conditions and water scarcity problem and also increases their steps towards doubling the income.

RELEVANCE IN CONTEXT OF UP

Horticulture is gaining importance as it gives more return per unit area and also gives nutritious food to human beings thereby improves quality of life and enhances the aesthetic beauty in nature. Among horticultural crops vegetables forms an integral and important component in the economy of the nation. The multicultural state of Uttar Pradesh is currently home to 16 % of India’s total population. Uttar Pradesh plays a key role in the economic development of India as it tops the chart in the most populous state of India. The state also holds the top position in high population growth rate in India (22.3 Crore in 2017). Demand for fresh or canned vegetables is increasing day by day in the national and international markets due to increasing population. Production should be increased by several folds to meet up the vegetable demands for the increased population. An adequate source of irrigation water throughout the growing season is essential for commercial vegetable cultivation. But irrigation water is not properly available in Bundelkhand region. Therefore adoption of more efficient water use technology is indispensable which may contribute a lot in such cases. So summer vegetable crops grown under poly tunnel using drip irrigation in winter season is a good option for Bundelkhand region of Uttar Pradesh because off-season vegetables can provide 15 Times higher net return compared to those of optimum sowing. Moreover, efficient use of irrigation water in polytunnel allow flexibility in planting time, establishing a more uniform plant stand, influencing soil temperature, utilizing certain herbicides and soil fumigants more effectively and assuring reliable yields. In the Bundelkhand region of Uttar Pradesh, it is also a good initiative for smallholder farmers having less than 2 hectares of land. Moreover, there is no source of supplying irrigation water when required. Therefore, farmers should grow summer vegetables in the winter season under the plastic tunnel to get more profit from a small piece of land.

So, with the introduction of polytunnel technology, the farmer would be able to diversify agriculture practices in the Bundelkhand zone. Farmers will be trained; technology will be demonstrated and disseminated among the farmers with the support of this project. Enhancement in horticulture production improved nutritional security and increased farmer’s income would be the actual relevance of the project.

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EXPECTED OUTPUT RELEVANT TO THE CONTEXT OF A FARMING COMMUNITY OF THE STATE

1. Introduction of polytunnel technology in Bundelkhand region of UP.

2. Developing and standardizing the drip irrigation and fertigation techniques.

3. Trained human resource in the polytunnel.

4. Availability of offseason vegetable.

5. Efficient use of water through drip irrigation.

6. To increase farmer’s income, per unit area productivity, nutritional security, quality of products as well as minimize the infestation of insect pest.

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Biofertilizers: A Boon for Agriculture

Govind Vishwakarma1 and Shweta Soni2*

1Department of Horticulture, DCAST, Selaqui, Dehradun (U.K.) 248011

2Department of Vegetable Science, BUA&T, Banda (U.P.) 210001


INTRODUCTION

Modern agriculture defined as agriculture with modern technologies by using hybrids seeds and high yielding varieties that are highly responsive to large doses of chemical fertilizers and irrigation facilities. The soil fertility is decreasing day by day due to the continuous use of synthetic fertilizers. These are been the cause of lacking of nutrients and organic matter in the soil for proper growth and development of plants. In the soil, there is beneficial microorganism which works as activate the different nutrients available in deactivated forms. It is estimated that by 2020, to achieve the targeted production of 321 million tons of food grain, the requirement of nutrient will be 28.8 million tons, while their availability will be only 21.6 million tons being a deficit of about 7.2 million tons, thus depleting feedstock/fossil fuels (energy crisis) and increasing cost of fertilizers which would be unaffordable to small and marginal farmers, thus intensifying the depleting levels of soil fertility due to widening gap between nutrient removal and supplies. Chemical fertilizers which are now being used extensively since the green revolution have depleted soil health by making the soil ecology non - inhabitable for soil microflora and microfauna which are largely responsible for maintaining soil fertility and providing some essential and indispensable nutrients to plants. Bio-fertilizers are the products containing one or more species of microorganisms which have the ability to mobilize nutritionally important elements from nonusable to usable form through biological processes such as nitrogen fixation, phosphate solubilization, excretion of plant growth promoting substances or cellulose and biodegradation in the soil, compost, and other environments. In other words, bio-fertilizers are natural fertilizes which are living microbial inoculants of bacteria, algae, fungi alone or in combination and they augment the availability of nutrients to the plants. The role of bio-fertilizers in agriculture assumes special significance, particularly in the present context of the increased cost of chemical fertilizer and their hazardous effects on soil health.

BIO-FERTILIZER: THE NEED OF THE HOUR IN AGRICULTURE

At present times, there is a growing concern about environmental hazards and threats to sustainable agriculture. In view of the above-stated facts, the long-term use of bio-fertilizers proves to be economical, eco-friendly, more efficient, productive and accessible to marginal and small farmers over chemical fertilizers. The need for the use of bio-fertilizer thus arises primarily for two reasons. First, because an increase in the use of fertilizers leads to increased crop productivity, second, because increased use of chemical fertilizer leads to damage in soil texture and raises other environmental problems.

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CLASSIFICATION OF BIO-FERTILIZERS

Several microorganisms and their association with crop plants are being exploited in the production of bio-fertilizers. They can be grouped in different ways based on their nature and function.

rhizoBium

Rhizobium is a soil habitat bacterium, which colonizes legume roots and fixes atmospheric nitrogen symbiotically. The morphology and physiology of Rhizobium vary from free-living condition to the bacteroid of nodules. They are the most efficient bio-fertilizer as per the quantity of nitrogen fixed concerned. They have seven genera and are highly specific to form nodule in legumes, referred to as a cross-inoculation group.

AzotoBActer

Of the several species of Azotobacter, A. chroococcum happens to be the dominant inhabitant in arable soils capable of fixing N2 (2-15 mg N2 fixed /g of carbon source) in culture media. The bacterium produces abundant slime which helps in soil aggregation. The numbers of A. chroococcum in Indian soils rarely exceeds 105/g soil due to lack of organic matter and the presence of antagonistic microorganisms in the soil.

AzoSpirillum

Azospirillumlipoferumand A. brasilense (Spirillumlipoferumin earlier literature) are primary inhabitants of soil, the rhizosphere and intercellular spaces of root cortex of graminaceous plants. They develop an associative symbiotic relationship with graminaceous plants. Apart from nitrogen fixation, growth promoting substance production (IAA), disease resistance and drought tolerance are some of the additional benefits of inoculation with Azospirillum.

cyAnoBActeriA

Both free-living, as well as symbiotic cyanobacteria (blue-green algae), have been harnessed in rice cultivation in India. Once so much publicized as a bio-fertilizer for rice crop, it has not presently attracted the attention of rice growers all over India. The benefits due to algalization could be to the extent of 20-30 kg N/ha under ideal conditions but the labor-oriented methodology for the preparation of BGA bio-fertilizer is in itself a limitation.

AzollA

Azolla is a free-floating water fern that floats in water and fixes atmospheric nitrogen in association with nitrogen-fixing blue-green alga Anabaena azollae. Azollaeither as an alternate nitrogen source or as a supplement to commercial nitrogen fertilizers. Azolla is used as bio-fertilizer for wetland rice and it is known to contribute 40-60 kg N/ha per rice crop.

phoSphAte SoluBilizing microorgAniSmS (pSm)

Several soil bacteria and fungi, notable species of Pseudomonas, Bacillus, Penicillium, Aspergillusetc. Secret organic acids and lower the pH in their vicinity to bring about the

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dissolution of bound phosphates in soil. Increased yields of wheat and potato were demonstrated due to inoculation of peat-based cultures of Bacillus polymyxaand Pseudomonas striata.

Am fungi

The transfer of nutrients mainly phosphorus and also zinc and sulfur from the soil milleuto the cells of the root cortex is mediated by intracellular obligate fungal endosymbionts of the genera Glomus, Gigaspora, Acaulospora, Sclerocystsand Endogonewhich possess vesicles for storage of nutrients and arbuscles for funneling these nutrients into the root system. By far, the commonest genus appears to be Glomus, which has several species distributed in soil.

SilicAte SoluBilizing BActeriA (SSB)

Microorganisms are capable of degrading silicates and aluminum silicates. During the metabolism of microbes, several organic acids are produced and these have a dual role in silicate weathering. They supply H+ ions to the medium and promote hydrolysis and the organic acids like citric, oxalic acid, Keto acids and hydroxy carbolic acids which form complexes with cations, promote their removal and retention in the medium in a dissolved state.

plAnt groWth promoting rhizoBActeriA (pgpr)

The group of bacteria that colonize roots or rhizosphere soil and beneficial to crops are referred to as plant growth promoting rhizobacteria (PGPR). The PGPR inoculants promote growth through suppression of plant disease (termed Bioprotectants), improved nutrient acquisition (termed Bio-fertilizers), or phytohormone production (termed Biostimulants). Species of Pseudomonas and Bacillus can produce as yet not well-characterized phytohormones or growth regulators that cause crops to have greater amounts of fine roots which have the effect of increasing the absorptive surface of plant roots for uptake of water and nutrients. This PGPR are referred to as Biostimulants and the phytohormones they produce include indole-acetic acid, cytokinins, gibberellins and inhibitors of ethylene production.

Table 1: Types of Bio-fertilizers

S. N. Types of Bio-fertilizers Examples

N2 fixing Bio-fertilizers

1. Free-living Azotobacter, Beijerinkia, Clostridium, Klebsiella, Anabaena,Nostoc

2. Symbiotic Rhizobium, Frankia, Anabaena azollae

3. Associative Symbiotic Azospirillum

P Solubilizing Bio-fertilizers

4. Bacteria Bacillus megateriumvar. phosphaticum, Bacillus subtilis, Bacillus circulans, Pseudomonas striata

5. Fungi Penicilliumsp, Aspergillusawamori

P Mobilizing Bio-fertilizers

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S. N. Types of Bio-fertilizers Examples

6. Arbuscularmycorrhiza Glomussp., Gigaspora sp., Acaulospora sp., Scutellospora sp. &Sclerocystis sp.

7. Ectomycorrhiza Laccaria sp., Pisolithus sp., Boletus sp., Amanita sp.

8. Ericoid mycorrhizae Pezizellaericae

9. Orchid mycorrhiza Rhizoctoniasolani

Bio-fertilizers for Micro nutrients

10. Silicate and Zinc solubilizers Bacillus sp.

Plant Growth Promoting Rhizobacteria

11. Pseudomonas Pseudomonas fluorescens

METHODS OF APPLICATION OF BIO-FERTILIZERS

Seed treAtment

200 g of Bio-fertilizer is suspended in 300–400 mL of water and mixed gently with 10 kg of seeds using an adhesive like gum acacia, jiggery solution, etc. The seeds are then spread on a clean sheet/cloth under shade to dry and used immediately for sowing.

Seedling root dip

This method is used for transplanted crops. For rice crop, a bed is made in the field and filled with water. Recommended bio-fertilizers are mixed in this water and the roots of seedlings are dipped for 8-10 h and transplanted.

Soil treAtment

4 kg each of the recommended bio-fertilizers is mixed in 200 kg of compost and kept overnight. This mixture is incorporated into the soil at the time of sowing or planting.

ADVANTAGES OF USING BIO-FERTILIZERS

● Some of the advantages associated with bio-fertilizers include:

● They are eco- friendly as well as cost-effective

● Their use leads to soil enrichment and the quality of the soil improves with time.

● Though they do not show immediate results, the results shown over time are spectacular.

● These fertilizers harness atmospheric nitrogen and make it directly available to the plants.

● They increase the phosphorous content of the soil by solubilizing and releasing unavailable phosphorous.

● Bio-fertilizers improve root proliferation due to the release of growth promoting hormones.

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● Microorganism converts complex nutrients into simple nutrients for the availability of the plants.

● Bio-fertilizer contains microorganisms which promote the adequate supply of nutrients to the host plants and ensure their proper development of growth and regulation in their physiology.

● They help in increasing the crop yield by 10-25%.

● Bio-fertilizers can also protect plants from soil born diseases to a certain degree.

Table 2: Amount of Nutrients Fixed by Some Bio-fertilizers in Various Crops

Microorganisms used as bio-fertilizer

Nutrient Fixed (kg/ha/year)

Beneficiary Crops

Rhizobium 50 to 300 kg N / ha Groundnut, Soybean, Redgram, Greengram, Black-gram, Lentil, Cowpea, Bengal-gram and Fodder legumes

Azotobacter 0.026 to 20 kg N / ha Plantation Crop, Rice, Wheat, Barley, Ragi, Jowar, Mustard, Safflower, Niger, Sunflower, Tobacco, Fruit, Spices, Condiment, Ornamental Flower

Azospirillum 10-20 kg N /ha Sugarcane, Vegetables, Maize, Pearl millet, Rice, Wheat, Fodders, Oil seeds, Fruit and Flower

Blue Green Algae 25 kg N /ha Rice, banana

Azolla 900 kg N /ha Rice

Phosphate solubilizingbacteria and fungi

Solubilize about 50-60% of the fixed phosphorus in the soil

All Crops (nonspecific)

CONSTRAINTS IN BIO-FERTILIZER TECHNOLOGY

● Though the bio-fertilizer technology is a low cost, eco-friendly technology, several constraints limit the application or implementation of the technology. The constraints may be:

● Technological constraints like unavailability of good quality carrier material and lack of qualified technical personnel in production units.

● Infrastructural constraints like lack of essential equipment, power supply, etc.

● Financial constraints like non-availability of sufficient funds and problems in getting bank loans.

● Environmental constraints like seasonal demand for bio-fertilizers, simultaneous cropping operations and short span of sowing/planting in a particular locality, etc.

● Human resources and quality constraints like lack of technically qualified staff in the production units, lack of suitable training on the production techniques.

● Unawareness on the benefits of the technology due to the problem in the adoption of the technology by the farmers due to different methods of inoculation, no visual difference in the crop growth immediately as that of inorganic fertilizers.

● Marketing constraints like non availability of right inoculant at the right place at the right time, lack of retail outlets or the market network for the producers.

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● The different constraints in one way or the other affect the technique at production, or marketing or usage.

CONCLUSION

Bio-fertilizers being essential components of organic farming play a vital role in maintaining long-term soil fertility and sustainability by fixing atmospheric di-nitrogen, mobilizing fixed macro and micronutrients in the soil into forms available to plants. Currently, there is a gap of ten million tons of plant nutrients between removal of crops and supply through chemical fertilizers. In the context of both the cost and environmental impact of chemical fertilizers, excessive reliance on chemical fertilizers is not practicable in the long run because of the cost, both in domestic resources and foreign exchange involved in setting up of fertilizer plants and sustaining the production. In this context, bio-fertilizers would be the viable option for farmers to increase productivity per unit area.

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Application of Sen’s Multi-Objective Programming Approach: Analysis of Farmers’ Livelihood Strategies by Optimizing Resource Use in Farming Area of Adamawa State, Nigeria

Gwandi O.1,2,*, V. Kamalvanshi1, Saidu Buba2 and 1Saket Kushuwaha

1Department of Agricultural Economics, Institute of Agricultural Sciences

Banaras Hindu University, Varanasi–2210052Federal Polytechnic, Mubi, Adamawa State, Nigeria


ABSTRACT

This paper explores the likelihoods of optimal allocation of resources as livelihood strategies for the farmers in Adamawa State, Nigeria. The study determined the best production plan and resource allocation among food crop farmers in Adamawa State, Nigeria. The objective of the study was to examine the socio-economic characteristics of food crop farmers and to formulate alternative farm plans for improving the farm economy. A multistage random sampling technique was used to select 150 food crop farmers from eight villages of the 21 local government area of the state. A structured questionnaire survey was used to obtained data from the respondents in the study area. Descriptive statistics and Sen’s Multi-Objective Programming (MOP) Model was used to analyze the data obtained from the field survey. The study shows that the majority of 68.7% were full-time farmers with an average mean of 31 years of age and 30.96 years of farming experience. The majority (85.3%) were male farmers and only 15.3% of the respondent had no formal education with the average land holding of 3.1 hectares. The result of the multiple objective programming reveals that the existing average income of `69348.97 was realized while the optimal income obtained from the multi-objective programming was `71979.95 which is 3.79 percent higher over present income. Consequently, for employment, the existing plan was 156.5 man days while the optimal plan for the maximization of employment recommends 162 man-days which represent 3.51per cent increase. Lastly for the minimization of fertilizer the existing plan allocated 282.15 kg of fertilizer while the optimal plan for minimization of fertilizer use recommends 218.03 kg which represents a decrease of 22.73 percent. It is recommended among others that the food crop farmers be educated on the allocation of resources for optimum utilization to raise their level of production and income for a better livelihood.

Keywords: Farmers’ Livelihood Strategies: Optimising Resource Use; Sen’s Multiobjective Programming

INTRODUCTION

Livelihood strategies reveal collection and combinations of activities and alternatives that people make to achieve goals and livelihoods. Livelihood strategies evolve according to implicit and/or explicit decision-making basis on the internal and external verity of livelihood.

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Application of Sen’s Multi-Objective Programming Approach: Analysis of Farmers’ Livelihood Strategies 101

ISBN: 978-93-88237-24-6

Subsistence strategies are diverse and are in a constant process of change and adaptation. An efficient agricultural system aims to develop optimal combinations in enterprises for greater integration of agricultural activities. In order to make better use of agricultural lands, in order to support farmers’ families and produce crops in a sustainable way, agricultural planning must be carefully organized at the farm level. Most farmers build a diversified portfolio of social support activities and survival skills to raise living standard. They grow more crops in a season to meet the needs of family consumption along with generating sufficient income for other household expenses. Therefore, improving farmers’ income is an important consideration for the formulation of alternative farm plans. Farmers use high-dose chemical fertilizers with less use of organic manure in crops that are not suitable for soil health (Kushwaha et al, 1998). The reduction in the use of chemical fertilizers becomes the second goal for agricultural planning. It is also desirable to offer more job opportunities for rural workers. The third objective of agricultural planning is to increase the use of labor in crop cultivation. All these objectives can be achieved individually using Linear Programming. Linear programming has been extensively applied to optimize single objective (Sen and Shah, 1983, Sen 1986,1998, Dubey and Sen 1988, 1994, Kushwaha et. al. 1998. Therefore, this study attempt to formulate alternative farm plans to increase income and employment by reducing the use of fertilizers in farms of Varanasi Uttar Pradesh, India using Sen’s MOP method (Sen, 1983). This paper aims to examine the socioeconomic characteristics of food crop framers and formulate alternative farm plans for improving farm economy that will consequently have a positive impact on their livelihood strategies. This method has been used successfully by many researchers (Sen, 1982, Sen and Painuli 1984, Kushwaha 1992, Memariani, 1993, Sen and Dubey 1994, Gangwar 1994, Sen and Singh 1996, Singh 2002, Kumar 2012, Gautam 2015, Kumari et al. 2017) to formulate the right farming plan to achieve multiple goals at the same time.

METHODOLOGY

deScription of the Study AreA

The study was conducted in Adamawa state Nigeria. Adamawa State is located in the North East part of Nigeria between latitude 7.00N and 11.00N of the equator and longitude 11.00E and 14.00E of the Greenwich meridian (Adaebayo, 1999). The State was created in 1991 from the defunct Gongola State. The state shares common boundary with Taraba State in the south and west, Gombe State in the North West and Borno State in the North. Adamawa State has an international boundary with the Cameroun Republic along with its eastern border. The State covers a land area of about 38,741 square kilometers and is divided into 21 Local Government Areas (LGA). The state has population of 3,161,374 people comprising of 1,580,333 males and 1,581,041 females (NPC, 2006). As opposed to a national annual population growth rate of 3.2%, the population of Adamawa State is growing at 2.8% per annum (Adamawa State MDGs report, 2006). By 2015, the state is expected to have 4,067,411 inhabitants.

The State has a tropical climate marked by dry and rainy seasons. The rainy season commences in April and ends in late October. The wettest month is August and September. The mean annual rainfall pattern shows that the amounts range from 700mm in the North-West part to 1600mm in the southern part (Adebayo, 1999). The mean annual rainfall is less than 1000mm in the central and north-west part of the State. On the other hand, the north-eastern strip and the southern part have over 100mm of rainfall. The temperature characteristic in the state is

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typical of the West Africa Savannah. The climate is characterized by high temperature almost throughout the year due to high solar radiation which is relatively evenly distributed throughout the year. The maximum temperature in the state can reach 400C, particularly in April, while minimum temperature can be as low as 180C between December and January. Mean monthly temperatures in the State ranges from 26.7 0C in the south to 27.8 0C in the northeastern part of the state. The major economic activity of the inhabitants is agriculture (farming, fishing, and cattle rearing).

SAmpling procedure And dAtA collection

Adamawa State is made up of 21 local Government areas (LGAs)) and is divided into four agricultural zones by the Adamawa State Agricultural Development Programme (AD.ADP) for administrative convenience namely the southwest zone, the central zone, the North West zone and northeast zone. Multi-stage random sampling technique was employed in the selection of respondents in these zones. In the first stage, one local government area was randomly selected in each of the AD.ADP zones, to give a total of four sampled local government areas. In the second stage, two villages were randomly sampled in each of the selected local government areas to give a total of 8 sampled villages. The third stage sampling involved the random selection of 150 farmers in the 8 villages.

Primary data was used for the study, which was obtained through the administration of a questionnaire to farmers in the sampled villages with the assistance of trained personnel. The data collected was for 2016 and 2017 farming seasons.

methodS of dAtA AnAlySiS

Linear programming was used to achieve the optimum utilization and resource allocation for the farmers in the study area. The linear Programming model is described as:

Subject to the constraints,

x_j≥0 j=1,2,…..,n

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i=1,2,………….,m

Where,

Z1 = Total net returns from all the crops in rupees

Z2 = Total employment on the farm in man days and

Z3= Total fertilizer use on the farm in Kg.

Ij= Net return from the jth crop in rupees/ha.

Ej= Employment of jth

crop in man-days/ha

Fj= Fertilizer use in jth

crop in kg/ha

Xj = Area under jth crop in ha.

aij = Quantity/Number of ith input required per hectare by jth crop.

bi= Quantity/Number available of the ith resource/ Input

The individual optimization of income, employment, and fertilizer use have generated three different cropping patterns with the conflicts in the achievement of the objectives. To overcome this problem and generating an appropriate farming system that achieves all the three objectives simultaneously, Sen’s MOP method was used. Sen’s MOP method is described as below:

Subject to the constraints,

xj≥0i=1,2,………….,mj=1,2,…586..,n and W1, W2 & W3 >0

Where, Z* = Multi Objective Function, W1 = Maximum Income, W2 =Maximum Employment and W3 = Minimum Fertilizer use.

Temporally-Ordered Routing Algorithm (TORA) computer-based software was used to obtain the optimum land use plan for food crop farmers.

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lineAr progrAmming model And mop for lAnd AllocAtion of fArmerS in nigeriA

The results of the linear programming matrix for Nigeria farms is presented in Table 1. The table shows that the total land allocated for the production of maize, paddy, sorghum, groundnut, and cowpea was 3.1 hectares. The farmer’s net income for maize was `29082.44, paddy `16189.29, sorghum `3934.524, groundnut `17335.71, and cowpea `27081.04. The land area allocated for maize was 1.13 hectare, paddy 0.46 hectare, sorghum 0.36 hectare, groundnut 0.35 hectare, and cowpea 0.70 hectare. Table 20 shows the basic information necessary to construct a linear programming model for land utilization.

the deciSion vAriABleS Are

X1 = area allocated for the maize crop

X2= area allocated for paddy crop

X3= area allocated for sorghum crop

X4= area allocated for groundnut crop

X5= area allocated for cowpea crop

X6= labor hiring

X7= capital borrowing

Table 1: Linear Programming Matrix for Nigeria

Crops Income(Rs./ha)

Land(ha)

Labour(man-days/ha)

Operating capital(Rs./ha)

Fertilizer(kg/ha)

Top 20% Bottom 20%

Maximum area

Minimum area

Maize (X1) 29082 1.13 50 150 1.95 0.57

Paddy(X2) 16189 0.47 45 75 1.37 0.41

Sorghum (X3) 3934 0.36 40 30 1.14 0.24

Groundnut(X4) 17335 0.35 60 100 1.70 0.35

Cowpea (X5) 27081 0.79 55 40 1.76 0.42

Total 3.1

Source: field survey 2017

RESOURCE CONSTRAINTS

a. land (3.1 ha)

b. labor (160 man-days)

c. Wage rate (Rs.300 man-days)

d. The rate of interest on borrowings (15% p.a)

e. Own capital (Rs.27300)

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FORMULATION OF LINEAR PROGRAMMING (LP) MODEL

Maximize Z = 29082.44X1+16189.29X2 +39394.524X3+17335.71X4+27081.04X5

−170X6 – 0.15X7

Subject to

Crop Land Constraints

X1+X2 +X3+X4+X5 +0X6 + 0X7 ≤ 3.1

Labour Constraints

80X1+50X2 +40X3+60X4+35X5 - 0X6 + 0X7 ≤ 160

Operating Capital Constraints

11647.21X1+3943.143X2 +982.744X3+5619.583X4+4106.711X5 +0X6 - 0X7 ≤ 27300

Temporally-Ordered Routing Algorithm (TORA) computer-based software was used to obtain the optimum land allocation areas for food crop farmers.

Table 2 reveals the optimal farm plan generated for maximizing income, employment and minimizing fertilizer use and this is based on the assumption that maximization of income, employment maximization and minimization of fertilizer use is the underlying behavioral principle guiding the farmers in their resource use and allocation decision. The table shows that the existing average income of `69348.97 was realized while the optimal income obtained from the multi-objective programming output is `71979.95 which represent 3.79 percent enhancement in income. This result reveals that the farmers in the study area were already working close to the efficiency level as there is only a marginal variation between the existing and the alternative suggested plan. Consequently, for employment, the existing plan was 156.5 man days while the optimal plan for the maximization of employment recommends 162 man-days which represent a 3.51 percent increase. Lastly for the minimization of fertilizer the existing plan allocated 282.15kg of fertilizer while the optimal plan for minimization of fertilizer use recommends 218.3 kg which represents a marginal decrease of 22.73 percent.

Table 2: Results of Existing and Alternative Plans of Income, Employment and Fertilizer use of Farmers in Nigeria Farms

Particulars Existing plan Individual Optimization Sen’s M.O.P.

Max.Income

Max.Employment

Min.Fertilizer

Income (Rs.) 69348.97 74281.09(+7.11)

60772.05(-12.37)

51147.65(-26.25)

71979.95(+3.79)

Employment(Man-days) 156.5 129.25

(-17.41)167.75(+7.19)

148(-5.43)

162(+3.51)

Fertilizer use (kg.) 282.15 263.80(-6.50)

287.30(+1.83)

209.30(-25.82)

218.03(-22.73)

Source: Field Survey 2017

Note: Figures in Parentheses Shows the Percentage Increase/Decrease over the Existing Levels.

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The optimal farm plan of land allocation for food crop farmers in the study area generated and recommended by multi-objective programming output is presented in table 3. For maize, the existing farm plan allocated 1.71 hectares while the MOP output recommends 0.56 hectares. Paddy was 0.40 hectares while 0.41 hectares was suggested, sorghum 0.23 ha was allocated, the MOP recommends 1.23 hectares, groundnut 0.35 hectares was allocated while the MOP recommended 0.35 hectares. Similarly for cowpea (0.41 ha) while the MOP recommended 1.56 hectares.

Table 3: Optimize MOP Matric for Land Use of Nigeria

Crops INCOME LABOUR FERTILIZER MOP

Maize 1.71 0.56 0.56 0.56

Paddy 0.40 0.40 0.40 0.41

Sorghum 0.23 0.23 1.13 1.23

Groundnut 0.35 1.50 0.35 O.35

Cowpea 0.41 0.41 0.66 1.56

Total 3.11 3.11 3.11 3.11


Table 4 presents the percentage allocation of existing cropping pattern along with the MOP percentage efficient recommended cropping pattern if the farmers in the study area are to enhance their income by reallocating the existing plan to adopt the MOP recommended efficient best technology and management practice. The table reveals that the efficient cropping pattern that enhances the income of the farmers is by reducing the area under maize from 1.13 ha which represents 36.33% of the total land earlier allocated to 0.56 ha i.e.18.01%. Similarly decrease area for paddy from 0.47 ha (15.11%) to 0.41 ha (13.18%) and the area under sorghum from 0.36 ha (11.58%) to 0.41 ha (13.18%) and 0.23 ha (7.40%) respectively. Consequently, the existing plan for groundnut allocated 0.35 ha (11.25%) while MOP recommended the same plan, for cowpea the existing plan allocated 0.80 (25.72%) ha while the MOP recommended that the allocation is increased to 1.56 (50.16%) ha. This agrees with Kushwaha (1996) in their study of estimation of hectarage response of irrigated tomato to some selected economic factors in Bauchi State, Nigeria.

Table 4: Percentage Change of Existing and Optimal Plan for Food Crop Farms in Nigeria

CropsExisting plan Optimal plan

Area (ha) Percentage Area (ha) Percentage

Maize x1 1.13 36.33 0.56 18.01

Paddy x2 0.47 15.11 0.41 13.18

Sorghum x3 0.36 11.58 0.23 7.40

Groundnut x4 0.35 11.25 0.35 11.25

Cowpea x5 0.80 25.72 1.56 50.16

Total 3.11 100 3.11 100


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CONCLUSION AND RECOMMENDATIONS

The result the multiple objective programming for Nigerian farmers revels that the existing average income of `69348.97 was realized while the optimal income obtained from the multi-objective programming output is `71979.95 which represent 3.79 percent enhancement in income. This result reveals that the farmers in the study area were already working close to the efficiency level as there is only a marginal variation between the existing and the alternative suggested plan. Consequently, for employment, the existing plan was 156.5 man days while the optimal plan for the maximization of employment recommends 162 man-days which represent a 3.51 percent increase. Lastly for the minimization of fertilizer the existing plan allocated 282.15kg of fertilizer while the optimal plan for minimization of fertilizer use recommends 218.3 kg which represents a marginal decrease of 22.73 percent. Based on this findings, the following recommendation is made:

1. The need to support the farmers with the extension service for better subsistence strategies cannot be underestimated. Therefore, it is recommended that extension services be modernized and strengthened through appropriate governmental and non-governmental funding. This will help and encourage extension workers to educate farmers about the allocation of critical resources and managerial skills that will enable farmers to plan and evaluate commercial activities on farms for a better standard of living.

2. There is a need to instruct the farmers on how to utilize their limited resources for optimal allocation and use them to enable them to harness the best productivity and income.

REFERENCES

[1] Adebayo, A.A. (1999). Climate I (Sunshine, temperature, evaporation and relative humidity) In: Adamawa State in Maps, Adebayo, A.A. and Tukur A.L. (eds). Paraclete Publishers, Yola, Nigeria PP 3–5

[2] Chandra Sen (1986) Land use pattern in the hills of Uttar Pradesh-An ecological abuse. National Geographical Journal of India. 32 (2), 111–117

[3] C.Sen and C.M.Singh. (1996). An integrated pasture and grass land development planning in the hills of Uttar Pradesh. National Geographical Journal of India, 42 (3&4), 281–283.

[4] Chandra Sen (1998) Possibilities of increasing employment opportunities in Agricultural Sector- A case study. The Economic Studies, Aug. 16-31, 1998, 9–12.

[5] Gangwar, L. S.,(1994). Technological Advancements and its Implications on Sustainable Agriculture- A Case Study of NainitalTarai of Uttar Pradesh. Ph.D. thesis. Department of Agricultural Economics, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi, India.

[6] Gautam, K., Sen C and Prakash J. (2015).Optimization of Employment and Income of Agricultural labourers through crop enterprise: Linear Programming Approach, Progressive Research- An International Journal, Volume 10 Special Part III, pp. 1465–1471.

[7] Kumari, M., Singh, O.P. and Meena, D.C.,(2017). Optimizing cropping pattern in Eastern UttarPradeshusingSen’s Multi Objective Programming Approach, Agricultural Economics Research Review,Vol. 30 (No.2), 285–291.

[8] Kushwaha, S. ,J.E.Ochi, E.O. Adeleke, and Chandra Sen,(1998). Estimating animal waste required for use as fertilizer: A linear programming simulation approach. Journal of Agricultural Development and Policy, Vol.10 (1), 80–88

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[9] Kushwaha, S.,(1992b). Resource Allocation for Alternative Farming System in Varanasi District, U.P.. Ph.D. thesis,Ph.D. thesis, Department of Agricultural Economics, Institute of Agricultural Sciences, Banaras Hindu University,Varanasi, India.

[10] Kumar, H. (2012) Economic Analysis of Fresh Water Aquaculture in Maharajganj district of Eastern Uttar Pradesh. Ph.D. thesis Department of Agricultural Economics, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi, India.

[11] Memariani, A.,(1993). Some Studies in Multiple Criteria Decision Making in CRISP, RANDOM and FUZZY Environment. Ph.D. thesis, Department of Mathematics, Banaras Hindu University. Varanasi, India.

[12] P.P.Dubey and Chandra Sen (1988) Resource use planning in agriculture-a case study of Chiraigaon block in Eastern Uttar Pradesh. Agril. Situation in India. (April), 39–41.

[13] P.P.Dubey and Chandra Sen (1994). An alternative system for sustainability of Indian Agriculture- A case study of Eastern Uttar Pradesh. Economic Affairs, 39 (3), 185–191.

[14] Sen C. (1982) Integrated multi period rural development plan for Dwarahat block, Almora (U.P.): A multi-objective programming Approach. Ph.D. thesis, G.B.P. University of Agriculture and Technology, Pantnagar, Uttrakhand, India.

[15] Sen, C. and S.L. Shah (1983) Employment, unemployment and under employment among landless agricultural labourers- A case study. Economic Affairs 28(2), 662–664.

[16] Sen, C. (1983) A new approach to Multi-objective Rural Development Planning. The Indian Economy Journal Vol.30 No.4. 91–96.

[17] Sen, C. and D.K.Painuli, (1984). An integrated land use planning for minimizing soil erosion in the hills of Uttar Pradesh. Indian Journal of Soil Conservation, 12(1), 1–4.

[18] Sen, Chandra and P.P. Dubey, (1994). Resource use planning in Agriculture with single and Multi-objective programming approaches (A comparative study). Journal of Scientific Research, 44, 75–81

[19] Singh, V.K., (2002). Agricultural Development and Environmental Pollution-A Case Study of District Varanasi. Ph. D. thesis, Department of Agricultural Economics, Institute of AgriculturalSciences, Banaras Hindu University, Varanasi, India

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Assessment of Heavy Metal Contamination in Leafy Vegetables Near Sewage Treatment Plants of Allahabad City, Uttar Pradesh, India

Harshita Baranwal1, Dr. Satyendra Nath2, Tarence Thomas2 and P. Smrity Rao2

1Department of Environmental Sciences and NRM, Sam Higginbottom University of Agriculture,

Technology and Sciences, Allahabad–211007, U.P., India2Department of Soil Science, Sam Higginbottom University of Agriculture,

Technology and Sciences, Allahabad–211007, U.P., India

ABSTRACT

This study investigated that the extent of heavy metal contamination in leafy vegetables and associated health risks in agriculture crop field near Sewage treatment plant (STP). The total concentration of Cd, Pb and Cu were determined in two leafy vegetables i.e., Palak and Sarso and soils at 5 different sites which included treated and untreated sites together. Not just the crops irrigated with wastewater are hazardous, in the present study, we have found that vegetables growing in the vicinity of wastewater drain are also not safe for human consumption. Pb crossed the safe limit in both the vegetables.

Keywords: Heavy Metal, Vegetables, Wastewater, Hazardous

INTRODUCTION

Injudicious use of resources and haphazard urbanization have over-exploited the natural resources and caused detrimental effects on the environment. Wastewater irrigation is a major concern for the potential health risk of the human population as it transfers accumulated heavy metal from soil to vegetable and through consumption, by human beings, it enters in the food chain. Metal being persistent keep accumulating and magnifying with an increase in each trophic level in the food chain.

Production of vegetables as well as food crops is carried out at places which are unsuitable for agriculture like along wastewater drains, near sewage treatment plants or other polluted sites to overcome with the problems of food demand due to the exponential growth of human population (Sharma et al., 2016). According to the World Health Organization (WHO), food security is achieved when “everyone and always” have access to “sufficient and safe” food. Consumption of metals through diet is reported across the globe and health hazards associated with these metals are also known (Arora et al. 2008; Orisakwe et al. 2012; Petroczi and Naughton 2009; Singh et al. 2010; Zhuang et al. 2009).

Lead and cadmium are among the most abundant heavy metals and are particularly toxic. The excessive amount of these metals in food is associated with etiology of a number of diseases,

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especially with cardiovascular, kidney, nervous as well as bone diseases (Sanchez-Castillo et al., 1998). Vegetables are widely used for the culinary purpose and are very important in the human diet because of the presence of vitamins and minerals salts.

MATERIALS AND METHODOLOGY

The study was conducted around Sewage Treatment Plant (STP) of Allahabad district Uttarpradesh during Jan-March 2018. The sample of vegetables and soil was collected from treated and untreated wastewater irrigated Ganga and Yamuna banks where vegetable crops are cultivated with sewage water. The study area is situated near the effluent discharge point of Sewage treatment plant.

Site Selection

Site 1: (S1) Arail ghat; (lat: 25°25՛12.31” North, long.: 81°51՛40.08”East)

Site 2: (S2) Salori treated; (lat: 25°27՛23.57” North, long.: 81°52՛47.41”East)

Site 3: (S3) Rajapur; (lat: 25°29՛30.59” East, long.: 81°50՛29.59”North)

Site 4: (S4) Salori untreated; (lat: 25°27՛38.20” North, long.: 81°52՛27.99”East)

SAmple prepArAtion And digeStion

Soil samples (three samples from each irrigation plots) were taken randomly at three depths (0-10, 10-20, 20-30cm) in each block by using a trowel. The soil sample from each depth was mixed, dried in an oven at 70 ᵒC and sieved with < 2 mm sieve. The prepared soil samples then stored in airtight packets for analysis. Leafy vegetables growing across each site were coded and collected from the four corners of the plot and mixed them together (For each vegetable at each site). All the leaves samples were brought to the laboratory and wrapped in the absorbent paper after sufficient washing with distilled water to remove air borne pollutants. Initially, edible part of the vegetables was weighed and it was supposed with air-drying first. All the samples were the oven dried in hot air oven at 70-80 ᵒC for 14hours to remove moisture. Weight them again for calculating moisture percentage content. Dried samples were powdered using mixer grinding. Sieved through Muslin cloth.

0.1 Gram of soil sample was taken in a 50ml beaker. Add 10 ml of aquaregia solution. Put it on a hot plate at 120 C temperature for 2 hours. If the solution dry and still not dissolve then add 10 ml aquaregia more to complete digestion of solution.(Aquaregia=3:1, HCl: HNO3). It turns white in color not transparent, dissolve precipitation. After cool down the solution, filter it with Whatman’s No.42 filter paper. Add 100 ml double distilled water to make up the volume. Keep the sample in the fridge, till analysis was completed. Similarly1gram of leaves sample (powder form) was taken in 50 ml beaker and mark the code. Add 20 ml of aquaregia and followed the above procedure for digestion (Di-Acid mixture). The final volume was made 100 ml using double distilled water. The heavy metal content was analyzed using Atomic Absorption Spectrometer (Perkin Elmer A Analyst 400).

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Assessment of Heavy Metal Contamination in Leafy Vegetables Near Sewage Treatment Plants 111

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Table 1: Showing Heavy Metal Concentration in Soil at Each Site

Heavy Metals Site 1 Site 2 Site 3 Site 4

Cd 0.019 0.003 0.001 0.002

Pb 5.711 5.395 5.457 5.593

Cu 0.076 0.058 0.05 0.035

The result of this study showed that the average concentration detected range from 0.007 to 5.434 in the vegetable sample and from 0.001 to 5.711 mg/kg in a soil sample at each site. The highest concentration of lead (Pb) was found followed by Cu and Cd at each site. Cd was found in order S3>S1>S2>S4 while Pb was found in order of S1>S4>S3>S1 and Cu follow S4>S2>S3>S1 in case of Palak Table 2. Cd and Cu concentration are below than the safe limit. Overall this study indicates that the vegetable sample is contaminated by toxic heavy metals.

Table 2: Table Showing Safe Limit and Metal Concentration at Different Sites in Palak

Heavy Metals Safe Limits of Heavy Metals in Plants* Site 1 Site 2 Site 3 Site 4

Cd 0.2 0.044 0.011 0.085 0.007

Pb 5.0 5.434 4.968 5.03 5.088

Cu 40.0 0.132 0.19 0.15 0.352

*WHO/FAO(2007) (mg/kg), Chauhan and Chauhan, 2014)

In case of Sarso we found the same order of heavy metal contamination as we found in case of Palak i.e. Pb> Cu>Cd. Cd was found in order of S1>S3>S2>S4, Pb follows S2>S4>S3>S1 while Cu shows maximum at S1=S2>S3>S4 at different sites in table 3. From the given result it shows that Cd, Pb, and Cu were present in each leafy vegetable at each site. These heavy metal shows toxic potential with an injury to human health as it starts accumulating in the human body. Consumers are suggested to take fresh vegetables at the sites where a low level of heavy metal was recorded.

Table 3: Table Showing Safe Limit and Metal Concentration at Different Sites in Sarso

Heavy Metals Safe Limits of Heavy Metals in Plants* Site 1 Site 2 Site 3 Site 4

Cd 0.2 0.161 0.009 0.021 .008

Pb 5.0 4.58 5.23 4.74 4.799

Cu 40.0 0.201 0.201 0.106 0.104

CONCLUSION

Due to limited use of water sources and wastewater treatment costs for discharge, the use of sewage water for irrigation on agriculture field has gained importance throughout the world. Which directly led to the accumulation of heavy metals in soil consequently passes into vegetables through food chain it enters in the human beings. Prolonged consumption of these vegetables may cause a disturbance in biological and biochemical processes in the humans as Cd affects directly on kidney and liver. The mean concentration of all metals in

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all vegetables at each site was found within the safe limits of the WHO/FAO, national and international permissible limits with the exception in Pb which cross the safe limit. The current study indicates that sewage water irrigation is the primary source of metal accumulation in food crops, which upon human consumption may lead to adverse health outcomes on a large scale.

Thus, regular monitoring of heavy metal contamination in vegetable grown at STP sites is necessary and consumption of these leafy vegetables should be avoided in order to reduce the health risk caused by taking the contaminated vegetables.

REFERENCES

[1] Arora M., Kiran B., Rani S., Rani A., Kaur B., Mittal N. (2008) Heavy metal accumulation in vegetables irrigated with water from different sources. Food Chem 111:811–815 Cross Ref Google Scholar.

[2] FAO/WHO, Evaluation of certain food additives and Contaminants. Geneva, World Health Organization, Joint FAO/WHO Expert Committee on Food Additives, World Health Organization Technical Report Series, vol. 859, pp. 29-35, 1995.

[3] G. Chauhan, U.K. Chauhan; 2014, Human health risk assessment of heavy metals via dietary intake of vegetables grown in wastewater irrigated area of Rewa, India Int. J. Sci. Res. Publ., 4 (2014), p. 9.

[4] Orisakwe O.E., Nduka J.K., Amadi C.N., Dike D.O., Bede O. (2012) Heavy metals health risk assessment for population via consumption of food crops and fruits in Owerri, South Eastern, Nigeria. Chem Cent J 6:77–83.

[5] Petroczi A., Naughton D.P. (2009) Mercury, cadmium and lead contamination in seafood: a comparative study to evaluate the usefulness of Target Hazard Quotients. Food Chem Toxicol 47:298–302.

[6] Sanchez-Castillo C.P., Dewey P.J.S., Aguirre A., Lara J.S., Vaca R., de la Barra P.L. (1998) The mineral content of Mexican fruits and vegetables. J Food Compos Anal 11:340–356.

[7] Sharma, A., Katnoria, J.K. & Nagpal, A.K., (2016); Heavy metals in vegetables: screening health risks involved in cultivation along wastewater drain and irrigating with wastewater; Publisher Name Springer International Publishing Online ISSN 2193-1801.

[8] Singh A., Sharma R.K., Agrawal M., Marshall F.M. (2010) Health risk assessment of heavy metals via dietary intake of foodstuffs from the wastewater irrigated site of a dry tropical area of India. Food Chem Toxicol 48:611–619.

[9] Zhuang P., Zou B., Li N.Y., Li Z.A. (2009) Heavy metal contamination in soils and food crops around Dabaoshan mine in Guangdong, China: implication for human health. Environ Geochem Health 31:707–715.

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Front Line Demonstrations: An Effective Way of Productivity Enhancement of Pearlmillet in Hanumangarh District of Rajasthan

Bheiru Singh, Akshaya Ghintala, Mukesh Kumar Verma and Manohar Lal Sain

Krishi Vigyan Kendra, Nohar, Hanumangarh-II (Raj.)

ABSTRACT

Pearl millet (Pennisetum glaucum (L) R.Br. emend. Stuntz) is an important food crop in areas with low rainfall and shallow soils. Being short in duration, it is the most drought-tolerant millet grown in the arid and semi-arid regions of the world (Bhagavatula et al. 2013). Majority of farmers used locally available seeds and inputs due to unawareness of improved production technologies of pearlmillet. Therefore, the Krishi Vigyan Kendra, Nohar, Hanumangarh-II (Rajasthan) conducted frontline demonstrations with improved variety along with recommended package of practices during Kharif 2017 at farmer’s field. The results of the studied showed that the average grain yield of pearlmillet under demonstration plots was 2060 kg/ha as compared to local check 1740 kg/ha. During the course of study the average 18.39 percent yield was increased over local check. Technology gap and technology index values were 140 kg per hectare and 3.36 percent, respectively. It’s concluded that frontline demonstrations an effective tool for increasing the productivity of pearlmillet in Hanumangarh district of Rajasthan.

Keywords: Frontline Demonstration, Extension Gap, Technology Gap, Technology Index, Pearlmillet, Production Technology

INTRODUCTION

Pearl millet (Pennisetum glaucum (L) R.Br.emend.Stuntz) is an important food crop in areas with low rainfall and shallow soils. Being short in duration, it is the most drought-tolerant millet grown in the arid and semi-arid regions of the world (Bhagavatula et al. 2013). It is one of the most important sources of staple food and fodder in the predominantly rainfed areas of the country. Its grain has very high nutritive value for human consumption and livestock also relish its straw, both in fresh and dried forms. In India, pearlmillet grown in 7.2 million ha with an average total production of 9.26 million tonnes in 2017-18 (Anonymous, 2018). It is largely a rainfed crop, except when it is grown as a summer irrigated crop. Overall, only 10% of the pearl millet area is irrigated in India. Majority of farmers used locally available seeds and inputs due to unawareness of improved production technologies of pearlmillet.

Frontline demonstration may play a very important role in proper transfer of technologies and changing scientific temperament of the farmers. The main objective of frontline demonstrations is to demonstrate newly released crop production and protection technologies and its management practices in the farmer’s field under different agro-climatic conditions and farming situations.

As such there always appears gap between the recommended technology by the scientist and farmer’s field. The technology gap is thus the major problem in the efforts of increasing

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agricultural production in the country. A need of the day is to reduce the technological gap between the agricultural technology recommended by the scientist and its acceptance by the farmers on their field. In view of the above factors, frontline demonstrations were undertaken in a systematic manner on farmer’s field to show the worth of improved production technology for increasing productivity of pearlmillet. Keeping in view the present investigation attempted to study the yield gap between frontline demonstration trails and farmers yield, extend of technology adoption and benefit-cost ratio.

RESEARCH METHODOLOGY

The study was carried out by Krishi Vigyan Kendra, Nohar, Hanumangarh-II (Rajasthan) during Kharif 2017 at farmer’s field on a recommended package of practices and improved variety of prealmillet (HHB 67 improved) in four-hectare area with ten locations (0.4 ha each farmer).

The data collected from frontline demonstrations conducted by the Krishi Vigyan Kendra at different farmer fields on the production technology of prealmillet were compared with prevailing farmers production technologies of prealmillet (check plots).

The study of recommended package of practices and improved variety seed evaluated visiting the FLD’s farmer fields, proper recording of growth and yields parameters, field days and by taking crop-cut experiments. Production and economic data of frontline demonstrations and local practice were collected and analyzed.

In the present study, technology index was operationally defined as the technical feasibility obtained due to implementation of frontline demonstration in prealmillet. To estimate the technology gap, extension gap and technology index following formulae used by Samuel et al. (2000) have been used:

Extension Gap (kg/ha) = Demonstration yield-Farmer practices yield (Local check)Technology Gap (kg/ha) = Potential yield-Demonstration yieldTechnology Index = Potential yield-Demonstration yield/ Potential yield X 100


performAnce of frontline demonStrAtion

As data indicated that average grain yield of pearlmillet under demonstration plots was 2060 kg/ha as compared to local check 1740 kg/ha. The average percentage of grain yield increased over local check was 18.39 percent. Higher yield of pearlmillet under demonstration plots might be due to application of recommended package of practices and improved variety of prealmillet (HHB 67 improved). Similar, more and less yield enhancement in different crops in front line demonstration has amply been documented by Hirenmath et al. (2007) and Patel et al. (2013). From these results, it is evident that the performance of improved variety was found better than the local check under same environment conditions. Yield of the frontline demonstration trails and potential yield of the crop was compared to estimate the yield gaps which were further categorized into technology index.

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Front Line Demonstrations: An Effective Way of Productivity Enhancement of Pearlmillet 115

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Table 1: Productivity of Wheat Crop under Demonstration and Farmer Practice

Year Name of Variety Average Grain Yield (Kg/ha) % Yield Increased Over Local Check

Demonstration Plot Farmer Practice

2017-18 HHB 67 improved 2060 1740 18.39

technology gAp

The frontline demonstrations were laid down under the supervision of scientists at farmer’s field. The technology gap shows that gap in the demonstration yield over potential yield was 140 kg/ha (Table 2).There exist gap between the potential yield and demonstration yield may be due to weather conditions. These findings are similar to the findings of Patel et al. (2013).

technology index

Technology Index shows the feasibility of the variety at the farmer’s field. The lower the value of the technology index more is the feasibility. Results of the study depicted in Table 2 revealed that the technology index value was 6.36%. The results of the present study are in consonance with the findings of Singh et al. (2007) and Patel et al. (2013).

Table 2: Yield, Technology Gap, Technology Index and Extension Gap of Wheat Grown under Demonstration and Local Check

Variables Yield (Kg/ha)

% Yield Increased over Local Check

Extension Gap (Kg/ha)

Technology Gap (Kg/ha)

Technology Index (%)

Local check 2060 - - - -

Demonstration (HHB 67 improved) 1740 18.39 320 140 6.36

Potential yield: 2200 (Kg/ha)

economic of frontline demonStrAtion

The economics of pearlmillet production under frontline demonstrations were estimated and the results of the study have been presented in Table 3. The results of economic analysis of pearlmillet production revealed that demonstrations plot recorded higher gross return (Rs. 24720/ha). Higher net return (Rs.9920/ha) and benefit-cost ratio (1.67) recorded under demonstration plots as compared to local checks. These results are in accordance with the finding of Hirenmath et al. (2007) and Hirenmath and Nagaraju (2009). Further, additional cost of Rs. 400 per ha in demonstration has increased additional net returns Rs. 3240 per ha with incremental benefit-cost ratio 8.10 suggesting it’s higher profitability and economic viability of the demonstration. More and less similar results were also reported by Hirenmath et al. (2007) Dhaka et al. (2010) and Patel et al. (2013).

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Table 3: Economic Analysis of Demonstration Plot and Farmer Practice

Variables Gross Cost (Rs./ha.)

Gross Return (Rs./ha.)

Net Return (Rs./ha.)

B:C Ratio

Demonstration plot 14800 24720 9920 1.67

Farmer plot 14200 20880 6680 1.47

CONCLUSIONS

The finding of the study revealed that improved technologies in frontline demonstrations enhanced grain yield of pearlmillet over the farmers practice in Hanumangarh district of Rajasthan. Therefore, frontline demonstration an effective tool for increasing the productivity of pearlmillet. This will substantially increase the income as well as the livelihood of the farming community. This created greater curiosity and motivation among other farmers who do not adopt improved practices of pearlmillet cultivation. The demonstrations also built the relationship and confidence between farmers and scientist of Krishi Vigyan Kendra.

The study emphasizes the needs to educate the farmers in the adoption of improved technology to narrow the extension gaps.

REFERENCES

[1] Anonymous, (2018). Second Advance Estimates of Production of Food grains for 2017-18. Agricultural Statistics Division, Directorate of Economics & Statistics, Department of Agriculture, Cooperation and Farmers Welfare, Government of India. Accessed online at http://agricoop.gov.in/sites/default/files/2ND_ADV_EST_APY_201718_E.pdf and http://agricoop.nic.in/sites/default/files/CWWG%20Data%2029.09.2017.pdf

[2] Bhagavatula, S., Rao, Parthasarathy, P., Basavaraj, G. and Nagaraj, N (2013). “Sorghum and Millet Economies in Asia–Facts, Trends and Outlook”. International Crops Research Institute for the Semi-Arid Tropics. Patancheru 502 324, Telangana, India, 80 pp. ISBN: 978-92-9066-557-1.

[3] Dhaka, B. L., Meena, B. S. and Suwalka, R. L. (2010).“Popularization of Improved Maize production technology through frontline demonstrations in south-eastern Rajasthan”.Journal of Agri. Sci., 1(1):39-42.

[4] Hiremath, S. M., Nagaraju, M. V. and Shashidhar, K. K. (2007). “Impact of frontline demonstration on onion productivity in farmers field”. Nation. Sem. Appropriate Extn. Strat. Manag. Rural Resources, Univ. Agric. Sci. Dharward. December 18-20:100.

[5] Patel, M. M., Jhajharia, A. K., Khadda, B. S. and Patil, L. M. (2013). “Frontline demonstration: An effective communication approach for dissemination of sustainable cotton production technology”. Ind. J. Extn.Edu.& R.D., 21: 60-62.

[6] Samuel, S. K., Miha, S., Roy, D. K., Mandal, A. K. and Saha, D. (2000).“Evaluation of Frontline demonstration on groundnut”.Journal of Indian Society Coastal Agril.Res.,18:180-183.

[7] Singh, D. K. Gautam, U. S. and Singh R. K. (2007). “Study on yield gap and level of demonstrated crop production technology in Sagar district”. Ind. Res. J. Extn. Edu.,7(2&3):94-95.

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Effect of Fly Ash on Soil Physical Properties under Sunflower-Spinach-Sunflower Crop Rotation System

Nouraldin Almadi Ibrahim Basha1, Abhishek James1*, Ram Bharose1 and Smriti Rao2

1Department of Environmental Sciences and NRM, SHUATS2Teaching Assistant, Department of Soil Science and Agricultural Chemistry, SHUATS


ABSTRACT

The present study was conducted for two year at two different depth(0-15cm) and (15-30cm) of soil at the research farm of College of Forestry, Department of Environmental Sciences and NRM, SHUATS, Allahabad. The findings of the present study revealed that the impact in control soil and fly ash admixed soil at different treatment level varied markedly. Addition of fly ash in soil improved the soil physical properties like bulk density, particle density, water holding capacity (W.H.C.) and porosity. The concentration of major nutrients such as nitrogen, phosphorus, and potassium are slightly increased in treated soils as compared to control. Soil applications to fly ash at lower levels were found to be beneficial for the plant growth in the present study. However, at higher application levels of fly ash, reduction in growth and yield of sunflower and spinach were observed. It was found that the T5 (Flyash @ 30 metric tons ha-1+ RDF) gives the high growth and yield for the sunflower and spinach. The present study showed a significant increase in yields, as well as biomass without any adverse effect on soil health or crop and the presence of heavy metal, is too low to make any harmful impact.

Keywords: Flyash, Crop Rotation, Bulk Density, Particle Density, Water Holding Capacity

INTRODUCTION

India has an enormous coal diffidence of 211 billion tonnes, coal is one of the most widely used fossil fuels for the generating of power. However, the ash content of 40% to 50% in Indian coal presents an intrinsic problem of ash dumping. The year 2012, 175 million tonnes or more than fly ash are usually to be generated in the country. According to the Ministry of Power, (Government of India) around 1800million tonnes coal will be use every year foremost to the generation of 600 million tonnes fly ash by 2031-2032. Fly ash is the waste product of burning materials. These light particles are flown above with reducing gases. Fly ash constitutes above 70% of the whole amount of residues formed in power plants through the combustion of coal. Since a huge amount of fly ash is generated every year, an enormous convention of research requirements to be conducted to find out the possibility of its exploitation in cultivation, manufacture and other industries around 10% of the total fly ash were utilized, generated as against 3-5%. Consequently, fly ash is currently treated as a precious source for appropriate conventional avenues of fly ash management. According to the Central Electricity Authority (CEA) New Delhi, India In year 2010-2011, 90 coal/ lignite thermal power stations of assorted power utilities in the country by way of total installed capacity of about 83797 MW, the whole generated fly ash is 66.49 million tonne and utilized ash was 36.26 million tonne, which

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provides percentage exploitation is 54.23% Raj and Mohan (2014). In India unaccompanied, the generation rate of fly ash is more than 112 million tons annually and it also shows that the production as well as both fly ash and bottom ash, may possibly to exec 170 million tons per year with the year 2015 (Pandey et al, 2009; Pandey and Singh 2010). The management of this enormous amount of solid waste, at both regional as well as the global stage, is a most important alarm in favor of the present and coming future (Ahmaruzzaman 2010, Kishore et al, 2010). The elementary composition both nutrient, as well as toxic elements, vary due to types and sources of used coal (Camberato et al. 1997).

Fly ash has tremendous potential as a nutrient supplement and plays a favorable role in increasing growth and yield of groundnut (Ray et al., 2003). Fly ash has similar physicochemical properties with soil. It can mix homogeneously and can improve the agronomic properties of soil (Change et al., 1979). Fly ash is the treasure of trace elements. It makes the trace element readily available to the crop when mixed with soil (Plank and Mortens, 1974). Auxin increased respiration rates are suggestive of the parallel relationship of growth, respiratory activity and found to increase RNA synthesis in the tissue of higher plants (Still and Pill, 2003). Use of fly ash ameliorates soil acidity for maximum uptake of trace elements from fly ash which acted as a reserve of trace element when mixed in the soil. Fly ash helps to retain water in the soil and also helped CO2 evolution. The plant hormone Indole acetic acid and Gibberellic acid helped protein, oil synthesis and also increased respiration rate. Soil metabolic manners, the performance of amylase invertase and protease, chlorophyll a and b, carotenoid and protein content are augmented in fly ash amended soil (Bhandari, 2006; Bozkurt and Karacal, 2001; Chadha, 1998).

Fly ash is valuable materials for agriculture and a good soil ameliorate. The addition of Fly ash in the soil improves or changes various physical, chemical and biological characteristics of the soil. Fly ash is used for the improvement of the soil texture, water holding capability, density, pH, bulk density, porosity etc. by using in different ratio with soil. For the growth of plant and crop yield fly ash is used as ameliorating in acidic soils. Fly ash is comprised mainly of silt and clay sized particles. It has the prospective if applied at high adequate rates to enduringly improve soil texture and enhance moisture holding capacity. Fly ash is used in clayey soil considerably reduced bulk density and WHC stuffing of gratis lime and augmented the content of fine sand which enhanced the soil consistency thereby the growth and yield performance of sunflower. Fly ash is mixed into soil for increasing soil porosity and soil drainage and mobility of nutrients.

MATERIAL AND METHODS

The experiment was conducted during the years 2008 and 2009 in the Rabi season to study the effect of Flyash on Soil Health and Quality Sunflower and spinach Crops Under Sunflower-Spinach-Sunflower Crop Rotation at Allahabad, India. The area is situated on the right bank adjacent to Yamuna river in the south of Allahabad city, which is located at 25°24’ 08.71 N latitude and 81°50’16.95’’ E longitude and 98 meters above the sea level. All the facilities necessary for experimentation were made available from the department. The area of Allahabad District comes under subtropical and arid climate prevailing in the south East part of U.P. with extremes in the temperature dropping to 5-6 °C in December and January and very hot in summer with temperature ranging between 46-47 °C in the month of May and June.

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Effect of Fly Ash on Soil Physical Properties under Sunflower-Spinach-Sunflower Crop Rotation System 119

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The average rainfall is around 1013.4 mm with maximum concentration during July to September and occasional frost in winter and hot wind (loo) in summer.

chArActeriStic propertieS of Soil

The soil of the experimental field is alluvial under the soil order inceptisol and suborder fluvents. The mechanical and chemical analysis of soil was done before the start of the experiment in order to characterize the various soil properties.

Soil SAmple prepArAtion

Before conducting the experiments soil sample were taken from the different place of the experimental fields from the 0-15, and 15-30 depth. The samples collected were mixed again, portioning and sieving (by the sieve of 2 mm).

mechAnicAl AnAlySiS

The results of the mechanical analysis of soil are given below. The mechanical analysis was done by “Bouyoucous hydrometer method” as described by Jackson (1957).

flyASh AnAlySiS

The fly ash was brought from the IFFCO Phulpur. After homogenization and drying three portions were taken, digested with a nitric perchloric solution and toxic element concentrations was determined by Atomic Absorption Spectrophotometer.

StAtiSticAl AnAlySiS

The experiment was conducted in 4 × 4 factorial design having four treatments and three replications. For the mustard crop. The data recorded during the course of the investigation was subjected to statistical analysis as per the method of “Analysis of variance” (Fisher 1950). The significant and nonsignificant of treatment effect was judged with the help of ‘F’ variance ratio test calculated ‘F’ at 5% level of significance. Either effect was considered to be significant or nonsignificant. The significant difference between the mean was tested against the critical difference at 5% level of significance. For testing of hypothesis, the following ANOVA table is used.


poroSity

The tables of 4.1(a) & (b) and figures of 4.1.(a), (b), (c) & (d) shows that the effect of fly ash on porosity (%) of post-harvest soil under sunflower-spinach-sunflower crop rotation at 0-15 cm and 15-30 cm soil depth was found satisfactory in both experimental years 2015-16 and 2016-17. The maximum porosity percentage 46.52(%) and 47.22 (%) was found in T7 (Flyash @ 50 metric tons ha-1+ RDF) at 0-15 cm soil depth which was statistically at par with the T6 in 2015-16 and 2016-17 and minimum porosity percentage 42.99 (%) and 42.63 (%) was found in T1 (Control). It was found that the percentage of porosity was increased as the dose of fly

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ash increases in each treatment and also found that the percentage of porosity were decreased after harvesting of each crop under crop rotation in both experimental years. The maximum porosity percentage 46.42(%) and 46.55 (%) was found in T7 (Flyash @ 50 metric tons ha-1+ RDF) at 15-30 cm soil depth which was statistically at par with the T6 in 2015-16 and 2016-17 and minimum porosity percentage 42.91 (%) and 42.88 (%) was found in T1 (Control). It was found that the percentage of porosity was increased as the dose of fly ash increases in each treatment and also found that the percentage of porosity were decreased after harvesting of each crop under crop rotation in both experimental years. The results showed that the porosity of soil increases with the increasing doses of fly ash to T5 after that it started to decrease due to the condition of the soil similar results obtained by Aitken et al., 1984; Pathan et al., 2001.

Table 4.1a: An Effect of Flyash on Porosity (%) of Post Harvest Soil under Sunflower Spinach Sunflower Crop rotation at 0-15 cm Depth

Treatment2015-16 2016-17

Sunflower Spinach Sunflower Mean Sunflower Spinach Sunflower Mean

T1 45.36 42.79 40.83 42.99 44.84 42.61 40.43 42.63

T2 46.16 43.63 41.82 43.87 46.35 43.85 41.72 43.97

T3 46.38 44.59 42.46 44.48 46.83 44.81 42.42 44.69

T4 47.03 45.20 43.10 45.11 47.42 45.44 43.07 45.31

T5 47.25 45.93 43.82 45.67 47.93 46.16 43.89 45.99

T6 47.27 46.40 44.55 46.07 48.53 46.65 44.80 46.66

T7 47.15 47.07 45.33 46.52 48.76 47.32 45.57 47.22

F-test S S S S S S S S

S. Ed. (±) 0.319 0.210 0.243 0.26 0.548 0.911 0.213 0.56

C.D. at 5% 0.658 0.434 0.501 0.53 1.131 1.881 0.440 1.15

Table 4.1b: Effect of Flyash on Porosity (%) of Post Harvest Soil under Sunflower Spinach Sunflower Crop Rotation at 15-30 cm Depth

Treatment 2015-16 2016-17


T1 45.27 42.70 40.75 42.91 45.01 42.79 40.83 42.88

T2 45.94 43.55 41.63 43.71 45.66 43.63 41.82 43.70

T3 46.33 44.42 42.41 44.39 45.68 44.59 42.46 44.24

T4 46.83 45.12 42.81 44.92 46.53 45.20 43.10 44.94

T5 46.94 45.62 43.73 45.43 46.98 45.93 43.82 45.58

T6 47.20 46.28 44.50 45.99 47.11 46.40 44.55 46.02

T7 47.11 47.03 45.12 46.42 47.25 47.07 45.33 46.55


S. Ed. (±) 0.367 0.224 0.209 0.27 0.500 0.210 0.243 0.32

C.D. at 5% 0.757 0.463 0.431 0.55 1.031 0.434 0.501 0.66

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Fig. 4.1a: An Effect of Flyash on Porosity (%) of Post Harvest Soil under Sunflower Spinach Sunflower Crop Rotation at 0-15 cm Depth in 2015-16

Fig. 4.1b: Effect of Flyash on Porosity (%) of Post Harvest Soil under Sunflower Spinach Sunflower Crop Rotation at 0-15 cm Depth in 2016-17

Fig. 4.1c: Effect of Flyash on Porosity (%) of Post Harvest Soil under Sunflower Spinach Sunflower Crop Rotation at 15-30 cm Depth in 2015-16

Fig. 4.1d: Effect of Flyash on Porosity (%) of Post Harvest Soil under Sunflower Spinach Sunflower Crop rotation at 15-30 cm Depth in 2016-17

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Bulk denSity (mg/m3)

The tables of 4.2(a) & (b) and figures of 4.2.(a), (b), (c) & (d) shows that the effect of fly ash on soil bulk density (mg/m3) of post-harvest soil under sunflower-spinach-sunflower crop rotation at 0-15 cm and 15-30 cm soil depth was found satisfactory in both experimental years 2015-16 and 2016-17. The maximum soil bulk density 1.35(mg/m3) and 1.33 (mg/m3) was found in T1

(Control) at 0-15 cm soil depth which was statistically at par with the T2 in 2015-16 and 2016-17 and minimum soil bulk density 1.11 (mg/m3) and 1.07 (mg/m3) was found in T7 (Flyash @ 50 metric tons ha-1+ RDF). It was found that the soil bulk density was decreased as the dose of fly ash increases in each treatment and also decreases the soil bulk density after harvesting of each crop under crop rotation in both experimental years. The maximum soil bulk density 1.35(mg/m3) and 1.34 (mg/m3) was found in T1 (Control) at 0-15 cm soil depth which was statistically at par with the T2 in 2015-16 and 2016-17 and minimum soil bulk density 1.11 (mg/m3) and 1.10 (mg/m3) was found in T7 (Flyash @ 50 metric tons ha-1+ RDF). It was found that the soil bulk density was decreased as the dose of fly ash increases in each treatment and also decreases the soil bulk density after harvesting of each crop under crop rotation in both experimental years. The particle size range of fly-ash is similar to silt and changes the bulk density of soil. (Several experiments have been performed to measure the physical properties for a variety of soils mixed with up to 50% fly-ash (Chang et al., 1977; Jones and Amos, 1977) which reveals that soil fly-ash mixture tend to have lower bulk density than soil alone. The results revealed that the application of fly-ash at 0%, 5%, 10%, 20%, 30%, 40%, and 50% by weight in soil significantly reduced the bulk density and improved the soil structure, similar results obtained by (Garg, et al., 2005; Kene, et al., 1991).

Table 4.2a: An Effect of Flyash on Bulk Density (mg/m3) of Post Harvest Soil under Sunflower Spinach Sunflower Crop Rotation at 0-15 cm Depth

Treatment2015-16 2016-17


T1 1.37 1.35 1.32 1.35 1.35 1.33 1.31 1.33

T2 1.34 1.32 1.30 1.32 1.34 1.33 1.32 1.33

T3 1.31 1.26 1.21 1.26 1.31 1.28 1.28 1.29

T4 1.28 1.22 1.18 1.23 1.26 1.22 1.21 1.23

T5 1.24 1.18 1.12 1.18 1.18 1.18 1.15 1.17

T6 1.22 1.15 1.08 1.15 1.14 1.15 1.12 1.14

T7 1.19 1.11 1.02 1.11 1.11 1.10 0.99 1.07


S. Ed. (±) 0.008 0.016 0.050 0.02 0.044 0.015 0.085 0.05

C.D. at 5% 0.016 0.033 0.103 0.05 0.091 0.030 0.176 0.10

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Table 4.2b: Effect of Flyash on Bulk Density (mg/m3) of Post Harvest Soil under Sunflower Spinach Sunflower Crop Rotation at 15-30 cm Depth

Treatment 2015-16 2016-17Sunflower Spinach Sunflower Mean Sunflower Spinach Sunflower Mean

T1 1.37 1.35 1.32 1.35 1.36 1.34 1.31 1.34

T2 1.34 1.32 1.30 1.32 1.33 1.31 1.29 1.31

T3 1.31 1.26 1.21 1.26 1.30 1.25 1.20 1.25

T4 1.28 1.22 1.18 1.23 1.27 1.21 1.17 1.22

T5 1.24 1.18 1.12 1.18 1.23 1.17 1.11 1.17

T6 1.22 1.15 1.08 1.15 1.21 1.15 1.06 1.14

T7 1.19 1.11 1.02 1.11 1.18 1.10 1.01 1.10


S. Ed. (±) 0.008 0.016 0.050 0.02 0.008 0.017 0.050 0.03

C.D. at 5% 0.016 0.033 0.103 0.05 0.016 0.035 0.104 0.05

Fig. 4.2a: An Effect of Flyash on Bulk Density (mg/m3) of Post Harvest Soil under Sunflower Spinach Sunflower Crop Rotation at 0-15 cm Depth in 2015-16

Fig. 4.2b: Effect of Flyash on Bulk Density (mg/m3) of Post Harvest Soil under Sunflower Spinach Sunflower Crop Rotation at 0-15 cm Depth in 2016-17

Fig. 4.2c: Effect of Flyash on Bulk Density (mg/m3) of Post Harvest Soil under Sunflower Spinach Sunflower Crop Rotation at 15-30 cm Depth in 2015-16

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Fig. 4.2d: Effect of Flyash on Bulk Density (mg/m3) of Post Harvest Soil under Sunflower Spinach Sunflower Crop Rotation at 15-30 cm Depth 2016-17 Oil Particle Density (mg/m3)

The tables of 4.3(a) & (b) and figures of 4.3.(a), (b), (c) & (d) shows that the effect of fly ash on soil particle density (mg/m3) of post-harvest soil under sunflower-spinach-sunflower crop rotation at 0-15 cm and 15-30 cm soil depth was found satisfactory in both experimental years 2015-16 and 2016-17. The maximum on soil particle density 3.22(mg/m3) and 3.14 (mg/m3) was found in T1 (Control) at 0-15 cm soil depth which was statistically at par with the T2 in 2015-16 and 2016-17 and minimum on soil particle density 1.11 (mg/m3) and 1.07 (mg/m3) was found in T7 (Flyash @ 50 metric tons ha-1+ RDF). It was found that the on soil particle density was decreased as the dose of fly ash increases in each treatment and also decreases the on soil particle density after harvesting of each crop under crop rotation in both experimental years. The maximum on soil particle density 3.16(mg/m3) and 3.22 (mg/m3) was found in T1 (Control) at 0-15 cm soil depth which was statistically at par with the T2 in 2015-16 and 2016-17 and minimum on soil particle density 2.43 (mg/m3) and 2.44(mg/m3) was found in T7 (Flyash @ 50 metric tons ha-1+ RDF). It was found that the on soil particle density was decreased as the dose of fly ash increases in each treatment and also decreases the on soil particle density after harvesting of each crop under crop rotation in both experimental years.

Table 4.3a: An Effect of Flyash on Particle Density (mg/m3) of Post Harvest Soil under Sunflower Spinach Sunflower Crop Rotation at 0-15 cm Depth

Treatment2015-16 2016-17


T1 3.34 3.18 3.14 3.22 3.22 3.13 3.08 3.14

T2 3.19 3.09 2.99 3.09 3.32 3.11 2.93 3.12

T3 2.99 2.99 2.83 2.94 3.13 3.09 2.72 2.98

T4 2.88 2.86 2.65 2.80 2.83 2.79 2.54 2.72

T5 2.76 2.77 2.50 2.68 2.58 2.49 2.39 2.49

T6 2.71 2.65 2.33 2.56 2.35 2.31 2.19 2.28

T7 2.63 2.54 2.16 2.44 2.18 2.16 2.05 2.13


S. Ed. (±) 0.052 0.040 0.200 0.10 0.175 0.143 0.188 0.17

C.D. at 5% 0.108 0.083 0.413 0.20 0.362 0.294 0.388 0.35

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Table 4.3b: Effect of Flyash on Particle Density (mg/m3) of Post Harvest Soil under Sunflower Spinach Sunflower Crop Rotation at 15-30 cm Depth


T1 3.24 3.15 3.10 3.16 3.34 3.18 3.14 3.22

T2 3.16 2.93 2.90 3.00 3.19 3.09 2.99 3.09

T3 2.87 2.88 2.77 2.84 2.99 2.99 2.83 2.94

T4 2.77 2.67 2.62 2.69 2.88 2.86 2.65 2.80

T5 2.71 2.58 2.45 2.58 2.76 2.77 2.50 2.68

T6 2.69 2.55 2.31 2.52 2.71 2.65 2.33 2.56

T7 2.62 2.53 2.14 2.43 2.63 2.54 2.16 2.44


S. Ed. (±) 0.096 0.114 0.183 0.13 0.052 0.040 0.200 0.10

C.D. at 5% 0.199 0.235 0.377 0.27 0.108 0.083 0.413 0.20

Fig. 4.3a: An Effect of Flyash on Particle Density (mg/m3) of Post Harvest Soil under Sunflower Spinach Sunflower Crop Rotation at 0-15 cm Depth in 2015-16

Fig. 4.3b: Effect of Flyash on Particle Density (mg/m3) of Post Harvest Soil under Sunflower Spinach Sunflower Crop Rotation at 0-15 cm Depth in 2016-17

Fig. 4.3c: Effect of Flyash on Particle Density (mg/m3) of Post Harvest Soil under Sunflower Spinach Sunflower Crop Rotation at 15-30 cm Depth 2016-17

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Fig. 4.3d: Effect of Flyash on Particle Density (mg/m3) of Post Harvest Soil under Sunflower Spinach Sunflower Crop Rotation at 15-30 cm Depth in 2016-17

Solid SpAce (%)

The tables of 4.3(a) & (b) and figures of 4.3.(a), (b), (c) & (d) shows that the effect of fly ash on soil solid space (%) of post-harvest soil under sunflower-spinach-sunflower crop rotation at 0-15 cm and 15-30 cm soil depth was found satisfactory in both experimental years 2015-16 and 2016-17. The maximum on soil solid space 43.83(%) and 42.98 (%) was found in T1 (Control) at 0-15 cm soil depth which was statistically at par with the T2 in 2015-16 and 2016-17 and minimum on solid space 40.37 (%) and 40.28 (%) was found in T7 (Flyash @ 50 metric tons ha-1+ RDF). It was found that the soil solid space was decreased the increased dose of fly ash in each treatment and also decreases the on soil solid space after harvesting of each crop under crop rotation in both experimental years. The maximum on soil solid space 43.51(%) and 43.83 (%) was found in T1 (Control) at 15-30 cm soil depth which was statistically at par with the T2 in 2015-16 and 2016-17 and minimum on soil solid space 40.28 (mg/m3) and 40.37(mg/m3) was found in T7 (Flyash @ 50 metric tons ha-1+ RDF). It was found that the soil solid space was decreased as the dose of fly ash increases in each treatment and also decreases the on soil solid space after harvesting of each crop under crop rotation in both experimental years.

Table 4.4a: An Effect of Flyash on Solid (%) of Post Harvest Soil under Sunflower Spinach Sunflower Crop Rotation at 0-15 cm Depth

Treatment2015-16 2016-17


T1 44.84 43.68 42.96 43.83 43.16 43.14 42.64 42.98

T2 44.85 42.93 42.39 43.39 44.51 42.55 42.36 43.14

T3 44.61 42.40 41.80 42.94 44.05 42.02 41.70 42.59

T4 44.45 41.53 40.95 42.31 43.86 41.96 41.10 42.31

T5 44.46 40.62 39.94 41.67 43.81 41.62 40.00 41.81

T6 44.19 39.74 39.05 40.99 43.46 41.00 39.34 41.27

T7 43.92 38.98 38.22 40.37 42.43 39.66 38.76 40.28


S. Ed. (±) 0.184 0.657 0.633 0.49 0.488 0.595 0.317 0.47

C.D. at 5% 0.379 1.356 1.307 1.01 1.008 1.227 0.655 0.96

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Table 4.4b: Effect of Flyash on Solid (%) of Post Harvest Soil under Sunflower Spinach Sunflower Crop Rotation at 15-30 cm Depth


T1 44.84 43.24 42.44 43.51 44.84 43.68 42.96 43.83T2 44.85 42.77 42.28 43.30 44.85 42.93 42.39 43.39T3 44.61 42.06 41.62 42.76 44.61 42.40 41.80 42.94T4 44.45 41.13 40.90 42.16 44.45 41.53 40.95 42.31T5 44.46 40.22 39.75 41.48 44.46 40.62 39.94 41.67T6 44.19 39.36 38.76 40.77 44.19 39.74 39.05 40.99T7 43.92 38.79 38.13 40.28 43.92 38.98 38.22 40.37F-test S S S S S S S SS. Ed. (±) 0.184 0.591 0.717 0.50 0.184 0.657 0.633 0.49C.D. at 5% 0.379 1.219 1.480 1.03 0.379 1.356 1.307 1.01

Fig. 4.4a: An Effect of Flyash on Solid (%) of Post Harvest Soil under Sunflower Spinach Sunflower Crop Rotation at 0-15 cm Depth in 2015-16

Fig. 4.4b: Effect of Flyash on Solid (%) of Post Harvest Soil under Sunflower Spinach Sunflower Crop rotation at 0-15 cm depth in 2016-17

Fig. 4.4c: Effect of Flyash on Solid (%) of Post Harvest Soil under Sunflower Spinach Sunflower Crop rotation at 15-30 cm depth in 2015-16

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Fig. 4.4d: Effect of Flyash on Solid (%) of Post Harvest Soil under Sunflower Spinach Sunflower Crop rotation at 15-30 cm Depth in 2016-17

Soil WAter holding cApAcity (%)

The tables of 4.4.(a) & (b) and figures of 4.4.(a), (b), (c) & (d) shows that the effect of fly ash on soil water holding capacity (%) of post-harvest soil under sunflower-spinach-sunflower crop rotation at 0-15 cm and 15-30 cm soil depth was found satisfactory in both experimental years 2015-16 and 2016-17. The maximum on soil water holding capacity 69.24(%) and 70.44 (%) was found in T7 (Flyash @ 50 metric tons ha-1+ RDF) at 0-15 cm soil depth which was statistically at par with the T2 in 2015-16 and 2016-17 and minimum on soil water holding capacity 62.45 (%) and 62.27 (%) was found in T1 (Control). It was found that the soil water holding capacity was increased with the increased dose of fly ash in each treatment and also observed that decreases the on soil water holding capacity after harvesting of each crop under crop rotation in both experimental years. The maximum on soil water holding capacity 69.46(%) and 69.79 (%) was found in T7 (Flyash @ 50 metric tons ha-1+ RDF) at 15-30 cm soil depth which was statistically at par with the T2 in 2015-16 and 2016-17 and minimum on soil water holding capacity 62.34 (%) and 62.45 (%) was found in T1 (Control). It was found that the soil water holding capacity was increased with the increased dose of flyash in each treatment and also observed that decreases the on soil water holding capacity after harvesting of each crop under crop rotation in both experimental years. Fly-ash generally decreased the bulk density of soils leading to improved soil porosity, workability and enhanced water-retention capacity (Page et al., 1979). The results revealed that the increase in fly-ash concentration in the soil (0%, 10%, and 20% up to 50%) increase water-holding capacity Similar results obtained by Khan and Khan, 1996; Singh and Siddiqui, 2003.

Table 4.5a: An Effect of Flyash on Water Holding Capacity (%) of Post Harvest Soil under Sunflower Spinach Sunflower Crop Rotation at 0-15 cm Depth

Treatment2015-16 2016-17

Sunflower Spinach Sunflower Mean Sunflower Spinach Sunflower MeanT1 63.39 62.40 61.56 62.45 63.30 62.35 61.15 62.27T2 66.22 64.10 64.48 64.93 66.32 64.83 64.35 65.17T3 67.22 65.25 65.60 66.02 67.26 66.28 65.38 66.31T4 68.25 65.86 66.33 66.81 68.35 67.12 66.28 67.25T5 69.21 66.45 66.93 67.53 69.31 67.99 67.01 68.10T6 70.34 67.38 67.94 68.55 70.40 68.92 68.13 69.15T7 71.55 68.59 69.24 69.79 71.56 70.55 69.20 70.44F-test S S S S S S S SS. Ed. (±) 0.404 0.586 0.539 0.51 0.371 0.605 0.347 0.44C.D. at 5% 0.833 1.209 1.112 1.05 0.766 1.248 0.717 0.91

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Table 4.5b: Effect of Flyash on Water Holding Capacity (%) of Post Harvest Soil under Sunflower Spinach Sunflower Crop Rotation at 15-30 cm Depth


T1 63.23 62.31 61.48 62.34 63.39 62.40 61.56 62.45

T2 66.07 63.97 64.35 64.80 66.22 64.10 64.48 64.93

T3 67.14 65.03 65.38 65.85 67.22 65.25 65.60 66.02

T4 68.12 65.81 66.28 66.74 68.25 65.86 66.33 66.81

T5 69.00 66.20 66.68 67.29 69.21 66.45 66.93 67.53

T6 70.20 67.24 67.80 68.41 70.34 67.38 67.94 68.55

T7 71.30 68.21 68.86 69.46 71.55 68.59 69.24 69.79


S. Ed. (±) 0.401 0.604 0.604 0.54 0.404 0.586 0.539 0.51

C.D. at 5% 0.829 1.247 1.246 1.11 0.833 1.209 1.112 1.05

Fig. 4.5a: An Effect of Flyash on Water Holding Capacity (%) of Post Harvest Soil under Sunflower Spinach Sunflower Crop Rotation at 0-15 cm Depth in 2015-16

Fig. 4.5b: Effect of Flyash on Water Holding Capacity (%) of Post Harvest Soil under Sunflower Spinach Sunflower Crop Rotation at 0-15 cm Depth in 2016-17

Fig. 4.5c: Effect of Flyash on Water Holding Capacity (%) of Post Harvest Soil under Sunflower Spinach Sunflower Crop Rotation at 15-30 cm Depth in 2015-16

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Fig. 4.5d: Effect of Flyash on Water Holding Capacity (%) of Post Harvest Soil under Sunflower Spinach Sunflower Crop Rotation at 15-30 cm Depth in 201

CONCLUSION

The findings of the present study conclude that impact in control soil and fly ash admixed soil at different treatment level varied markedly. Addition of fly ash in soil improved the soil physical properties like bulk density, particle density, water holding capacity (W.H.C.) and porosity. The concentration of major nutrients such as nitrogen, phosphorus, and potassium are slightly increased in treated soils as compared to control. Soil applications to fly ash at lower levels were found to be beneficial for the plant growth in the present study. However, at higher application levels of fly ash, reduction in growth and yield of sunflower and spinach were observed. It was found that the T5 (Flyash @ 30 metric tons ha-1+ RDF) gives the high growth and yield for the sunflower and spinach. The present study showed a significant increase in yields, as well as biomass without any adverse effect on soil health or crop and the presence of heavy metal, is too low to make any harmful impact.

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Impact of Thermal Effluent by Some Selected Physiochemical Properties on Total Bacterial Counts in Kota Barrage Lake, Kota, Rajasthan, India

Parveen Kumar1, Manju Rawat Ranjan1, Ashutosh Tripathi1 and S. Balachandaran2

1Amity University Uttar Pradesh, India 2Departments of Environmental Studies, Siksha Bhavana,

Visva-Bharati, Santiniketan, India

ABSTRACT

This study examined to explore the impact of thermal effluents from a power plant on Total Bacterial Counts in Kota barrage lake, Rajasthan. Kota Barrage Lake is an artificial water reservoir in Kota city. This lake is the main source of drinking water in Kota city. In the current study, Total bacterial counts and different physiochemical properties were analyzed in 54 samples. These samples have been collected from different locations i.e. upstream, midstream and downstream sampling stations in the study area during every month of winter and summer season i.e. Oct 2015-Feb 2016 and March-June 2016 respectively. Water sampling was carried out judgementally from designated points nearby confluence point of effluent and analyzed for physiochemical properties and Total bacterial counts using standard methods of APHA. Effect of selected parameters such as temperature, dissolved oxygen (DO), total organic carbon (TOC), chloride and sulfate on Total bacterial counts (TBC) was observed by regression analysis. On regression analysis, it was observed that TBC is positively correlated with Temperature (R2=0.332), TOC (R2=0.389), Chloride (R2=0.306), and Sulfate (R2=0.022), negatively correlated with Dissolved oxygen (R2=0.11). On statistical analysis, one way ANOVA test shows that Kota Barrage Lake has been affected by the effluent from the thermal power plant. On calculating the analysis of variation (ANOVA) of Total Bacterial Counts it was concluded at 5% level of significance, samples had come from populations having the same mean but the value of ‘F’ was found very close to the standard value of ‘F’ so it has the potential to exceed the standard value slowly with time.

Keywords: Thermal Effluent, Kota Barrage Lake, Physiochemical Properties, Total Bacterial Counts, Analysis of Variation (ANOVA)

INTRODUCTION

Total bacterial count (TBC)is a parameter which could reflect the bio film formation in water systems. It has been widely adopted as a standard and simple traditional technique for microbiological testing and safety management of drinking water (SU F et al. (2009)). Bio films, which are well-organized communities of microorganisms, are wide spread in nature. They constitute a major problem in many environmental, industrial and medical settings (Szymańska J (2003)). The presence of dissolved organic compounds in finished drinking water is responsible for the growth of bacteria and colonization of water surfaces (Bitton G (2005)). The presence of heterotrophic bacteria in surface water has implications for public health, especially pathogenic organism (Davisa et al. 2005). These organisms can cause stomach and intestinal

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ISBN: 978-93-88237-24-6

illness including diarrhea and nausea and can be fatal (Al-Mezori et al. 2011). Monitoring of the microbiological quality of the water largely depends on both the spatial and the temporal variation of the bacterial populations in the aquatic systems (Maul et al. 1985). Therefore, the analysis of heterotrophic bacteria in water reservoirs can be helpful in assessing water quality and the regression analysis between physiochemical properties and total bacterial counts will be very helpful to know the causes of the growth of total bacterial counts in the water reservoir.


Study AreA And field Study

Kota is a city located in the southeast of the northern Indian stateof Rajasthan. It is located around 250 kilometers south of the state capital Jaipur, situated on the banks of Chambal River. The cartographic coordinates are 25.18°N 75.83°E. The Chambal River separates these districts from Kota district, forming the natural boundary. Kota thermal power plant is located on the bank of Chambal River in Kota city. The effluent of Kota thermal power plant has been drained into Kota Barrage Lake. The map (Figure 1) on the following page shows Kota Barrage Lake where is located and selected sampling points. Six sampling points (A, B, C, D, E, and F) were taken from the confluence point as 2.5 km, 2.0 km, 1.5 km, 1.0 km, 0.7 km and 0.5 km respectively.

Fig. 1: Selected Surface Water Sampling Points Near Confluence Point of Kota Super Thermal Power Plant

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Impact of Thermal Effluent by Some Selected Physiochemical Properties 133

ISBN: 978-93-88237-24-6

Six sampling stations established along the stretch of Chambal river (Kota Barrage Lake) upstream (US) midstream (MS) and downstream (DS) to Kota Thermal Power Plant (KTPP) for the collection of water samples. The study was carried out for two seasons’ viz. summer, and winter seasons. The upstream, midstream and downstream sampling stations were visited in every month of winter and summer season during Oct 2015-Feb 2016 and March-June 2016 respectively. The study was limited to six sample points A, B, C, D, E and F, representing sample point A) upstream: the river before the point of wastewater discharge. B, C, and D, E) midstream: the river at the point of wastewater discharge and F) downstream: the river after the point of wastewater discharge. Precautions were taken to ensure that the samples were representative of the river. The water samples were collected from amber colored bottles in the morning time between 9-11 am from six selected sampling points in Kota barrage lake, Rajasthan. Some selected physiochemical properties such as Temperature, DO, TOC, Chloride, and sulfate was analyzed nearby confluence point in Kota barrage lake, Rajasthan and at respective sampling point total bacterial counts were also analyzed, had been investigated all according to American Public Health Association (APHA, 2012).

MICROBIOLOGICAL PARAMETERS ANALYSIS

heterotrophic BActeriA AnAlySiS

Analysis of heterotrophic bacteria has been undertaken by an aliquot of the sample or by dilution several times to minimize the bacterial population to a number which can be counted and then transferred to a sterilized Petri dish. Once in the Petri dish, the sample is mixed with liquefied nutrient agar and incubated at 30–37°C for 24–48 hrs, according to the Standard Methods for the examination of water and waste water 2005.

reSultS And StAtiSticAl AnAlySiS

‘F’ test statistics for a test of unequal of means and Regression analysis between selected physiochemical parameters and total bacterial count.

One way ANOVA for Total Bacterial Counts:

Test for equal means (table 1)

Table 1

Source of Variation

Sum of Squares

Degree of Freedom

Mean Square F p (Same)

Between groups: 5.61367E06 5 1.12273E06 2.02 0.09252

Within groups: 2.66734E07 48 555696

Total: 3.22871E07 53

F (5, 48) =2.409 at 5% level of significance.

On calculating the analysis of variation (ANOVA) of total bacterial counts it is concluded at a 5% level of significance, samples had come from populations having the same mean but the value of ‘F’ was found very close to the standard value of ‘F’ so it has the potential to exceed the standard value slowly with time (table1).

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regreSSion AnAlySiS

There were made the relationship between the various physiochemical properties and total bacterial counts, observed their relationship as positive correlation or negative correlation gave the quantitative value via regression analysis.

Fig. 2: Regression Analysis between TBC and Temperature

Fig. 3: Regression Analysis between TBC and Dissolved Oxygen

Fig. 4: Regression Analysis between TBC and TOC

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Impact of Thermal Effluent by Some Selected Physiochemical Properties 135

ISBN: 978-93-88237-24-6

Fig. 5: Regression Analysis between TBC and Chloride

Fig. 6: Regression Analysis between TBC and Sulfate

On regression analysis, it was observed that TBC is positively correlated with Temperature (R2=0.332), TOC (R2=0.389), Chloride (R2=0.306), and Sulfate (R2=0.022), negatively correlated with Dissolved oxygen (R2=0.11).

CONCLUSION AND DISCUSSION

Effect of selected parameters such as temperature, dissolved oxygen (DO), total organic carbon (TOC), chloride and sulfate on Total bacterial counts (TBC) was observed by regression analysis. On regression analysis it was observed that TBC is positively correlated with Temperature (R2=0.332) (Fig 2), TOC (R2=0.389) (Fig 4), Chloride (R2=0.306) (Fig 5), and Sulfate (R2=0.022) (Fig 6), negatively correlated with Dissolved oxygen (R2=0.11) (Fig 3,). The difference of total bacterial counts (between upstream and downstream) reaches more than 32 %. This indicates that temperature is the dominant factor affecting bacterial growth (Li and W. K. W. 1998).

On statistical analysis, one way ANOVA test shows that Kota Barrage Lake has been affected by the effluent from the thermal power plant. On calculating the analysis of variation (ANOVA) of Total Bacterial Counts it was concluded at 5% level of significance, samples had come from populations having the same mean but the value of ‘F’ was found very close to the standard value of ‘F’ so it has the potential to exceed the standard value slowly with time.

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REFERENCES

[1] Al-Mezori, Hassan Amin and Hawrami, Karzan A. M., Evaluation of microbial quality of the drinking water of Duhok province/Kurdistan region of Iraq, 2011 2nd International Conference on Environmental Science and Development, IPCBEE vol.4 2011, IACSIT Press, Singapore, pp. 141–147.

[2] APHA. Standard Methods for the Examination of Water and Wastewater, 21st ed.; American Public Health Association: Washington, DC, USA, 2012.

[3] Bitton G (2005). Wastewater Microbiology. 3rd ed. John Wiley & Sons Inc, Canada. pp. 419-455.[4] Davisa, Kristal., Anderson, Michael A., and Yates, Marylynn V.Distribution of indicator bacteria in

Canyon Lake, California, WaterResearch 39,2005, pp. 1277–1288.[5] Li, W. K. W., Annual average abundance of heterotrophic bacteria and ynechococcus in surface

ocean waters. American Society of Limnology and Oceanography, 43(7), pp. 1746-1753, 1998.[6] Maul, A., El-Shaarawi, A. H. and Block, J.C., Heterotrophic bacteria in water distribution system,

I. Spatial and Temporal variation, The Science of the Total Environment, 44,1985, pp. 201–214.[7] SU F, Luo M, Zhang F, Li P, Lou K, Xing X (2009). Performance of microbiological control by a

point-of-use filter system for drinking water purification. J Environ Sci, 21 (9): 1237-46. [8] Szymańska J (2003) Bio film and dental unit waterlines. Ann Agric Environ Med, 10 (2): 151-7.

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Piper nigrum: An Ecofriendly Source for Finish Application on Base Fabric for Museum Showcases

Pooja Singh* and Alka GoelDepartment of Clothing & Textiles, College of Home Science, Govind Ballabh Pant University of Agriculture & Technology,

Pant Nagar, Uttarakhand, IndiaE-mail: *[email protected]

ABSTRACT

Piper nigrum has a large number of therapeutic properties with rich phytochemistry, therefore, can serve as an ecofriendly source for the conservation of textile antiquities. Various qualitative and quantitative tests were carried out which confirmed the presence of secondary metabolites in the extracts of Piper nigrum seeds. The antimicrobial activity of the plant extracts showed a maximum zone of inhibition at 5% (Plant extract) against both test organisms viz. Staphylococcus pasteuriand Pseudomonas aeruginosa. Therefore the plant extracts of Piper nigrum (seeds) can be used to apply antimicrobial finish on the base fabric of museum showcases on which the antiquities were displayed against two microorganisms i.e. Staphylococcus pasteuriand Pseudomonas aeruginosa which are cellulose degrading.

Keywords: Flavonoid, Phytochemistry, Piper nigrum, Pseudomonas aeruginosa, Staphylococcus pasteuri

INTRODUCTION

Piper nigrum commonly called as Black Pepper is a member of family Piperaceae. The genus Piper is having a rich phytochemistry by the presence of alkaloids, amides, and terpenoids. The various pharmacological activities of Piper nigrum are radical scavenging, antioxidant, anti-insecticidal, anti-inflammatory and antibacterial. Due to all these properties Piper nigrum can be used as a antimicrobial textile finish for conservation of museum textiles. Textile antiquities are very fragile therefore a base fabric of showcases on which the antiquities are placed can be finished with the extract of seeds of Piper nigrum so that the antiquities can be conserved from the microbial attack which is a major threat to museum textiles.


collection And prepArAtion of plAnt Source

Seeds of Piper nigrum (Black pepper) were purchased from local market of Pantnagar, G.B.P.U.A & T (Uttarakhand). They were grounded by the domestic electric grinder. Prepared powder was stored in the airtight container for further use.

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prepArAtion of extrAct

In the present study five solvents in the order of increasing polarity were selected namely distilled water, methanol, acetone, hexane, and dichloromethane. Soxhlet method of extraction was carried out during the study. Conventional soxhlet extraction method given by Azmir et al. (2013) was used for the plant extraction.

phytochemicAl Screening of plAnt extrActS

Qualitative and quantitative screening helps in identification of the secondary metabolites present in the seeds extract and quantification of these bioactive compounds respectively. Therefore the researcher carried out the phytochemical screening of plant extract of Piper nigrum which was used in the present study.

Table 1: Qualitative and Quantitative Screening of Piper nigrum

Secondary Metabolites Name of the Test Reference

Qualitative Tests

Alkaloids

Dragendorff’s test Sasikala and Sundaraganapathy (2018)

Hager’s test Sasikala and Sundaraganapathy (2018)

Mayer’s test Sasikala and Sundaraganapathy (2018)

Wagner’s test Raaman (2006)

Tannic Acid Test Sasikala and Sundaraganapathy (2018)

Flavonoids

Ammonia test Vimalkumar et al. (2014)

Lead acetate test Vimalkumar et al. (2014)

Alkaline reagent test Singh et al. (2011)

Ferric chloride test Vimalkumar et al. (2014)

TanninsFerric chloride Test Zohra et al. (2012)

Match Stick test Kaur (2018)

Phenolic compounds

Ferric chloride test Vimalkumar et al. (2014)

Lead acetate test Vimalkumar et al. (2014)

Dilute iodine solution test Vimalkumar et al. (2014)

SaponinsFoam Test Zohra et al. (2012)

Lead acetate Test Devmurari (2010)

Terpenoids Salkowski test Elezabeth and Subramanian (2013)

Quantitative tests

Total Phenolic Content Ainsworth and Gillespie (2007)

Total Flavonoid Content Quettier et al., 2000

Total Tannins Content Sun et al., 1998

teSt microorgAniSmS

Two different strains including Gram Positive-Staphylococcus pasteuri and Gram Negative-Pseudomonas aeruginosawere used for the study. These strains were procured from the Department of Microbiology, College of Basic Sciences and Humanities, G.B.P.U.A & T, Pantnagar, Uttarakhand. The selected bacterial strains were maintained at 4°C in nutrient broth in Microbiology lab of the university (G.B.P.U.A&T).

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Piper nigrum: An Ecofriendly Source for Finish Application on Base Fabric for Museum Showcases 139

ISBN: 978-93-88237-24-6

AntimicroBiAl Activity of plAnt extrActS

The antimicrobial activity of plant extracts was assessed as per agar well diffusion method (Jahangirian et al., 2013). In the present study, various concentrations ranging between 2 percent to 5 percent of diluted plant extracts by the agar well diffusion method were used in the analysis. The lowest concentration at which zone of inhibition observed was recorded as the minimum concentration of the extracts and was selected for further experimentation.


percentAge yield of extrActS of PiPer nigrum

Piper nigrum (black pepper) produced a higher yield in acetone and methanol (16.245% and 15.967%) against distilled water, dichloromethane and hexane (12.192%, 8.315%, and 7.075%).

QuAlitAtive AnAlySiS of PiPer nigrum

The extract of Piper nigrum (Black pepper) was tested for various phytochemicals in Table 2.

Table 2: Qualitative Screening of Black Pepper (Piper nigrum) Extracts

S. No

Phytochemical Tests SolventsDistilled Water Methanol Acetone Dichloromethane Hexane

1. Alkaloidsa) Dragendroff’s Test + ++ ++ - -

b) Hager’s Test - + + + +

c) Mayer’s Test - ++ + + -

d) Wagner’s Test + + + - +

e) Tannic Acid Test + ++ + + -

2. Flavonoidsa) Ammonia Test + + + + -

b) Lead acetate Test + ++ + ++ ++

c) Alkaline reagent Test - - + + -

d) Ferric chloride Test ++ ++ - + -

3. Tanninsa) Match stick Test + ++ + - -

b) Ferric chloride Test - ++ + + -

4. Phenolic compoundsa) Ferric chloride Test ++ ++ - + -

b) Lead acetate Test + +++ + + +

c) Dilute Iodine Solution Test ++ - - + -

5. Saponins a) Foam Test - ++ + + +

b) Lead Acetate Test + +++ ++ ++ ++

6. Terpenoidsa) Salkowski Test - ++ - - -

+ ++= High concentration, ++ = Moderate concentration, + = Low concentration,-=Absent

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QUANTITATIVE SCREENING OF PLANT EXTRACTS

totAl phenolic content (tpc)

Total Phenolic Content in Piper nigrumwas calculated by using the standard curve of gallic acid shown in figure 1.

The yield of total phenolic content in Piper nigrum (Black pepper) was higher in acetone (156.27±.0.112 mg/g) extract followed by hexane (56.13±0.118 mg/g), dichloromethane (34.17±0.086 mg/g), distilled water (29.98±0.092 mg/g) and methanol (26.84±0.116mg/g).

Fig. 1: Calibration Curve for Total Phenols

totAl flAvonoid content (tfc)

To calculate the Total Flavonoid Content, quantitative analysis of the plant extracts were carried out. The amount of total flavonoid was calculated by using the calibration curve of quercetin shown in figure 2. The yield of Total phenolic content in Piper nigrum (Black pepper) was higher in methanol (13.17±0.087 mg/g) extract followed by dichloromethane (7.37±0.174mg/g), hexane (6.13±0.098mg/g), acetone (5.54±.098mg/g) and distilled water (3.95±0.087mg/g).

Fig. 2: Calibration Curve for Total Flavonoids

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Piper nigrum: An Ecofriendly Source for Finish Application on Base Fabric for Museum Showcases 141

ISBN: 978-93-88237-24-6

totAl tAnninS content (ttc)

The yield of Total phenolic content in Piper nigrum (Black pepper) was higher in dichloromethane (7.63 ± 0.095 mg/g) extract followed by hexane (6.01 ± 0.132 mg/g), acetone (5.27 ± 0.117mg/g), methanol (4.72 ± 0.056 mg/g) and distilled water (2.91 ± 0.173 mg/g).

Fig. 3: Calibration Curve for Total Tannins

AntiBActeriAl Activity of plAnt extrActS

Piper nigrum (Black pepper) exhibited maximum zone of inhibition at 5 percent of extract (1 ± 0.05cm) against Staphylococcus pasteuri followed by 4 % (1 ± 0.05cm) and 3% (0.8 ± 0.05cm). In case of gram negative bacteria i.e. Pseudomonas aeruginosa, leaves extract of Piper nigrum (Black pepper) exhibited maximum zone of inhibition at 5 percent of extract (0.9 ±0.02cm) followed by 4 % (0.6 ±0.02cm) and 3 % (0.6 ±0.05cm).

Plate 1 Antibacterial testing of Piper nigrum extract in three concentration

Staphylococcus pasteuri Pseudomonas aeruginosa

CONCLUSION

Various qualitative tests confirmed the presence of secondary metabolites in the extracts of Piper nigrum seeds. The further quantitative analysis confirmed that seeds of Piper nigrum

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(Black pepper) yielded higher total phenols (156.27±.0.112 mg/gin acetone). Quantification of flavonoids and tannins showed that total flavonoid (13.17±0.087 mg/gin methanol) and total tannins (7.63 ± 0.095 mg/g in dichloromethane). The antimicrobial activity of the plant extracts showed a maximum zone of inhibition at 5% against both test organisms viz. Staphylococcus pasteuri and Pseudomonas aeruginosa. Therefore the plant extracts of Piper nigrum(seeds) can be used to apply antimicrobial finish on textiles against two microorganisms i.e. Staphylococcus pasteuri and Pseudomonas aeruginosa which are cellulose degrading. The finish can be applied with various techniques such as dip dry, spray, microencapsulation, nanoencapsulation and many more.

REFERENCES

[1] Ainsworth, E.A. and Gillespie, K. M. 2007. Estimation of total phenolic content and other oxidation substrates in plant tissues using Folin-Ciocalteu reagent. Nat Protoc.2(4):875–877.

[2] Azmir1, J., Zaidula, I.S.M., Rahmana, M.M., Sharifa, K.M., Mohameda, M., Sahenab, F., Jahurulb, M.H.A., Ghafoorc, K., Norulainid, N.A.N. and Omarb, A.K.M. 2013. Techniques for extraction of bioactive compounds from plant materials: A review. Journal of Food Engineering. 117(4):426-436.

[3] Devmurari, V.P. 2010. Phytochemical screening study and antibacterial evaluation of Symplocos racemosa Roxb. Archives of Applied Science Research. 2 (1):354-359.

[4] Elezabeth, D.V. and Subramanian, A. 2013. Identification of Phytochemical Constituents and Antimicrobial Activity of Indigofera Suffruticosa Leaves. International Journal of Current Biotechnology. http://ijcb.mainspringer.com/1_7/702.html. Retrieved on 4 June 2018.

[5] Kaur, M., 2018. Tannins: Classification, Properties and Chemical Tests. http://www.yourarticlelibrary.com/pharmacognosy/tannins/tannins-classification-properties-and-chemical-tests/49892. Retrieved on 4 June 2018.

[6] Quettier, D.C., Gressier, B., Vasseur, J., Dine, T., Brunet, C., Luyckx, M.C., Cayin, J.C., Bailleul, F., Trotin, F. 2000. Phenolic compounds and antioxidant activities of buckwheat (Fagopyrum esculentum Moench) hulls and flour. J. Ethnopharmacol.72:35-42.

[7] Raaman, N., 2006. Phytochemical techniques. New India Publishing Agency, New Delhi.[8] Sasikala, M. and Sundaraganapathy, R. 2018. Qualitative Analysis of Alkaloids Exist in the

Hydroalcoholic Extract of Ipomoea aquatica for SSK. in Tamil Nadu. International Journal of ChemTech Research. 10(7):446-454.

[9] Singh, T.P., Singh, H.B and Singh, O.M. 2011. Adhatoda vasica Nees: Phytochemical and pharmacological profile. The Natural Products Journal, 1: 29-39.

[10] Sun, B., Silvia, J.M.R.D. and Spranger, I. 1998. Critical factors of vanillin assay for catechins and proanthocyanidins. J. Agric. Food Chem., 46, pp. 4267-4274.

[11] Vimalkumar, C.S., Hosagaudar, V.B., Suja, S.R., Vilash, V., Krishnakumar, N.M. and Latha, P.G. 2014. Comparative preliminary phytochemical analysis of ethanolic extracts of leaves of Olea dioica Roxb., infected with the rust fungus Zaghouania oleae (E.J. Butler) Cummins and non-infected plants. Journal of Pharmacognosy and Phytochemistry. 3(4):69-72.

[12] Zohra, S.F., Meriem, B., Samira, S. and Alsayadi, M.M.S. 2012. Phytochemical Screening and identification of some compounds from Mallow. J. Nat. Prod. Plant Resour. 2(4):512-516.

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Strategy for Doubling Farmers Income— A Case of Organic Turmeric Growers of Kandhamal District of Odisha

Prangya Paramita Sahoo*1, K.K. Sarangi2, Suvangi Rath3

1-3Department of Agricultural Economics, Orissa University of Agriculture and Technology,

Bhubaneswar- 751003E-mail: *[email protected]

ABSTRACT

The present study entitled “Strategy for Doubling Farmers Income–A Case of Organic Turmeric Growers of Kandhamal District of Odisha” was undertaken with the objectives to develop strategy to double the farmer’s income and assess the importance and role of the FPO and processing industry for the sustainable development of the organic turmeric farmers of the district. The present study was carried out in Kandhamal district putting emphasis on twelve blocks, 120 organic turmeric farmers were randomly chosen and interviewed. Farmer producers organization help farmers for successfully dealing with a range of Challenges that small producers are facing today. From the study, it was revealed that for successful value chain of organic turmeric more number of FPO should be promoted. FPO is the best way of linking producers to market for getting fair prices for their produce. Organic turmeric cultivation in Kandhamal is characterized by an informal or traditional supply chain that delivers products to the local middleman and then to small local stores. Formal value chain can deliver the same product with some processing or more uniform quality to more commercial firms, and this objective can be fulfilled with the establishment of processing or food industry in the district. The pathway for doubling farmers income by 2022 can be achieved mainly through the discussed strategies which include the establishment of the processing industry, institutional change, and promotion of FPO. This laudable objective could not only improve the wellbeing of our farmers but can also be a trigger to boost agri-based manufacturing growth in rural India. Doubling farmer’s income by 2022 is quite challenging but it is needed and is attainable.

Keywords: FPO; Doubling Income; Organic Turmeric; Supply Chain; Processing Industry

INTRODUCTION

Kandhamal occupies a unique position in spice production in the state. The tribal of the district is traditionally growing Turmeric and ginger organically from ages, which is the main cash crop for their economic development. Kandhamal Turmeric is an important product and now become popular in the organic food market of Europe and North America. It has gained a good market share in the International and Local market. The golden yellow Kandhamalhaldi is creating ripples in the world of spices. It smells just right, lasts longer and only a pinch adds the color and the flavor to the food. The local variety grown from time immemorial is having 2-3 percent curcumin, 12-15 percent of oleoresin and 5.3 percent of the volatile oil.

But nowadays there is a need to move away from the agri production based model to a rural manufacturing model. The vision of doubling farmer’s income by 2022 is a serious attention

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not only to uplift the standard of living of the farmers but also boost the manufacturing growth in rural India. There is the need to involve an underemployed adult in low skill noncrop activities. The underdeveloped district Kandhamal produces quality organic turmeric which has pharmaceutical and cosmetically importance so if the farmer, rural poor and unemployed youth involve in value addition after harvest of turmeric finger, it will help in increasing the farm gate price for the tribal farmers as they move from selling to small and big trader to a value-added use of turmeric. The pathway for the doubling of farmers’ income encompasses several dimensions, from production to post-harvest management. These include: bridging yield gap, proper management of irrigation and organic manure application, scientific boiling and drying operation etc. The resource-poor farmer does not get the appropriate price for their produce due to information asymmetry. There is wastage of produce due to lack of scientific storage facilities and proper processing structures. To overcome the problem of wastage, and to get the actual return from the labor there is need to find out other sustainable ways, which will make proper use of the surplus produce, also generate income and employment along the process. Primary and to some extent secondary processing and food processing industry provides a way out for this problem. Despite the growth of the food processing sector in Odisha to some extent, the processing activity in Kandhamal district is at a premature state with very low so to say no penetration.

THE OBJECTIVE OF THE STUDY

● To study the socio-economic profile of the sample farmers

● To assess the importance and role of the FPO and processing industry for the sustainable upliftment of the status of the organic turmeric farmers of the district.

● To develop a strategy to improve the farmer’s income.


The study was conducted in Kandhamal district of Odisha and is both qualitative and quantitative in nature since it involves more of observing and understanding the conditions in the study region. Data were collected from the primary sources (respondents) with the aid of a structured interview schedule consisting of both open and close-ended questions. The data collected was on general characteristics of farmers, land holding, costs, returns and yield of Turmeric etc. The primary data from 120 sample respondents pertained to the agricultural year 2017-18. Multistage purposive cum random sampling method was used for the study. Both Farm budgeting and partial budgeting technique were used to estimate the cost and return structure of turmeric cultivation.

Socio-Economic Profile of the Respondents

The socio-economic profile of the organic Turmeric growers of the study area is presented in Table 1. The average age of the sample farmers was found to be 43 years. The analysis of the occupational pattern of the sample respondents revealed that, in the study districts, all the sample farmers practiced agriculture as the main occupation. The average annual main income and subsidiary income of traditional farmers was Rs 62598 and Rs 38695, respectively. The average area under Turmeric crop was 1.57 ha. Livestock is an important source of income

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Strategy for Doubling Farmers Income—A Case of Organic Turmeric Growers of Kandhamal District of Odisha 145

ISBN: 978-93-88237-24-6

for farm families. Adding livestock to cropping system significantly reduces the risks associated with farm income.

Study Area Importance

For the research work to be carried out the district Kandhamal was selected purposefully, as the district is endowed with prevailing conducive agro-climatic conditions in sub-plain, no dearth of well-drained uplands soil and maximum area and production of organic turmeric from Kandhamal.

Table 1: Socio Economic Characteristics of Sample Respondents (n=120)

Sl. No. Particulars Unit Number of farmers Percentage of total

I Age group of the farmers

Below 35 years36 - 45 years46 – 55 yearsAbove 55 years

Number17533812

14.1644.1631.66

10

Average age 43

II Education Number

Literate Primary Secondary

762420

63.3320.0016.66

III Family Type Number

Nucleus Joint

6555

54.1645.83

IV Family size Number

Small (2-4) Medium (4-6) Large (>6)

267816

21.6665

13.33

Average family size 6

V Livestock status

Goat Hen Cow Buffalo Sheep

Number

8780443962

7.8825.6414.1812.519.87

VI Agriculture as occupation Number

Main Subsidiary

7248

60.0040.00

VII Average Annual Income Rupee

Main Subsidiary

6259838695

VIII Average area under Turmeric

Traditional farmer KASAM farmers Hectare 1.57

1.41

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Tab

le 2

.: A

rea,

Pro

duct

ion

of T

urm

eric

in

diff

eren

t blo

cks

of K

andh

amal

dis

tric

t fr

om

20

08

to

20

16

Are

a-M

illio

n H

ecta

res

Pro

duct

ion-

Mill

ion

Ton

nes

Sl

noN

ame

of t

he

Blo

ck2

00

8-0

92

00

9-1

02

01

0-1

12

01

1-1

22

01

2-1

32

01

3-1

42014-1

52015-1

6

Are

aP

rodu

c-

tion

Are

apr

oduc

-

tion

Are

aP

rodu

c-

tion

Are

aP

rodu

c-

tion

Are

aP

rodu

c-

tion

Are

aP

rodu

c-

tion

Are

aP

rodu

c-

tion

Are

aP

rodu

c-

tion

1K

haju

riap

ada

560

3304

550

3251

560

3310

560

3325

662

6854

670

7241

642

6133

634

5541

.16

2P

hiri

ngia

1900

1189

418

9811

900

1900

1191

319

1012

050

2027

2004

520

3020

140

1998

1908

819

9017

392.

6

3P

hulb

ani

682

4215

675

4178

690

4271

680

4325

802

8120

810

8546

780

7452

772

6747

.28

4B

alig

uda

370

2202

370

2211

370

2211

370

2180

495

3896

500

4572

465

4441

457

3994

.18

5K

otag

arh

650

3783

648

3817

650

3829

650

3835

760

7102

765

7254

747

7127

739

6458

.86

6Tum

udib

andh

a74

040

5569

538

6469

538

6474

040

6577

969

8678

275

8375

872

7475

065

55

7C

haka

pad

580

3115

540

2986

540

2986

560

3125

670

6203

675

6523

654

6248

646

5646

.04

8G

. U

daya

giri

1250

6950

1280

7194

1295

7278

1250

7325

1420

1398

614

2514

520

1388

1330

013

8012

061.

2

9R

aiki

a19

0011

571

1875

1145

618

9011

548

1900

1159

020

2018

596

2025

2042

519

9619

165

1988

1737

5.12

10Tik

abal

i85

052

4584

051

9185

052

5385

052

4510

0096

5410

1010

142

985

9500

977

8538

.98

11D

arin

gbad

i16

5010

263

1438

8973

1445

9017

1520

9125

1545

1458

315

5015

124

1518

1449

815

1013

197.

4

12K

.Nua

gaon

1580

9670

1606

9965

1615

1002

116

2510

075

1730

1547

517

3516

752

1710

1631

817

0214

875.

48

Tot

al12

712

7626

712

415

7498

612

500

7550

112

615

7626

513

910

1314

8013

977

1388

2213

641

1305

4413

545

1183

83

Sou

rce:

http

/kan

dham

al.n

ic.in

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Strategy to Improve Farmer’s Income in the Study Area

The important avenue to enhance farmers’ income is selecting a proven pathway i.e nothing but the farmers producer organization to successfully deal with a range of challenges that faced by the farmers today, especially small producers. FPO can help farmers for the production of agricultural produce as well as during the process of value addition and marketing the produce. Through FPO farmers can access quality inputs at low cost, modern technology for production, market information on different markets and prices in different markets, secure access to new technologies, and tap into high-value markets. FPO is the best way of linking producers to market for getting fair prices for their produce.

Another avenue which is necessary to diagnose the problems of the district and providing an improved production and marketing environment and value-added economic benefits to the farmer and entrepreneur trough appropriate science and technological policies for various post-harvest functions in food processing industries.

Farmer’s Perception about Various Activities of FPO

A detailed analysis of various activities of FPO to be undertaken was discussed with the farmers. A total of 7 activities, which determined the farmers perception on the promotion of FPO were included.

Role of fPo in the Study AReA

When the farmers unite they can clearly articulate their needs, organize different services like credit, machinery, organic input etc. A Farmer Producer organization in the respective villages gives a strong framework for the small and marginal organic turmeric producers for organizing themselves for effective linkage with markets.

PRoPoSed StePS in eStAbliShing fARmeR PRoduceR oRgAniSAtion in the Study AReA

Understanding the village community, cultivation, and marketing practices

Listing out of different problems

Identification of potential leaders

Seeking cooperation from Govt. and other agencies

Nominating core group leader like president secretary

Developing organizational structure

Monitoring the activities performed

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The FPO will offer a variety of services to its members as illustrated in the table. it is providing almost all kind of services to its members, covering all aspects of cultivation (from inputs, technical services to processing, certification, and marketing). The FPO will facilitate linkages between farmers, processors, traders, and retailers to coordinate the supply and value chain.

Table 3: Distribution of respondents according to their perception on activities of FPO

Sl No

Item Highly satisfied Satisfied Not satisfied

No % No % No %

1 Advice to producers 48 58.53 28 34.14 6 7.31

2 Technical Training to farmers 64 78.04 13 15.85 5 6.09

3 Collective request for credit (Financial Services) 42 51.21 32 39.02 8 9.75

4 Bulk purchase of input(Input Supply Services) 53 64.63 17 20.73 12 14.63

5 Management for selling of produce (procurement and marketing service)

44 53.65 29 35.36 9 10.97

6 Arrangement of communal storage godown 51 62.19 27 32.92 4 4.87

7 Certification 46 56.09 29 35.36 7 8.53

The Objective of FPO should be

● To help small and marginal turmeric farmers in the district to enhance agricultural production, productivity, and profitability.

● To provide access to modern technology through community-based processes for improving productivity and quality of produce.

● To facilitate to access forward linkages for new technologies for improving productivity, for value addition of the produce and market tie-ups.

● To ensure access to use of quality inputs and mechanization for improving agricultural production and for minimizing labor cost.

● To help to link producers to market for getting fair prices for their produce.

● Availability of more services to farmers through a single point.

PoSt-hARveSt mAnAgement And food PRoceSSing

Effective post-harvest management of turmeric finger which includes boiling, drying, powder formation, cur cumin extraction, turmeric oil extraction etc., will help farmers realize remunerative prices for their produce. It is more important for the poor farmer to aware about the price information of value-added products so that they can involve in the entrepreneurship activities which indirectly help them to improve their income and thereby the standard of living.

PARtiAl budgeting

It is a statement of anticipated changes in costs, returns and profitability for a minor modification. when a farmer contemplates few modifications or minor changes in the existing system, partial budgeting technique is employed. It is similar to that of marginal analysis, where in the changes in cost and return resulting from proposed modification is considered.

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NET CHANGE = (Added return + Reduced cost) – (Added cost + Reduced return)

Partial Budgeting Processing Functions Carried Out by the Sample Respondents in the Study Area

This is a technique used to test the profitability for a minor modification done at the farmer level. When the farmer undertakes the pre-processing activities like boiling and drying after harvesting it fetches more price than the existing i.e. selling raw turmeric. It was also seen that sometimes raw turmeric also fetches more price than dry because of the demand and supply condition. But in overall, the pre-processing brings more return to the farmer. From the marginal analysis it is concluded that by adopting the proposed modification the farmer get a worth of 17400 per ha as net change when they undertake boiling and drying and get 167000 when undertaking processing i.e powder formation so in this context it was concluded that farmer should undertake some value addition so that he can get more return with low investment.

Table 4: Analysis of Partial Budgeting of Primary Processing (boiling and drying)functions carried out by the

Sample Respondents in the Study Area

ITEMS ITEMS

Added cost Added return

Boiling-2000Drying-600

10 × 10000 = 10000060 × 2000 = 120000120000 – 100000 = 20000

Reduced return Reduced cost

NIL NIL

Total = 2600 Total = 20000

Net Change = 20000 – 2600 = 17400; Raw turmeric price = 10/kg; Dry turmeric price = 60/kg

Table 5: Analysis of Partial Budgeting of secondary Processing (powder formation) functions carried out by the Sample Respondents in the Study Area

ITEMS ITEMS

Added cost Added return

Processing =3000 100 × 1700 = 170000

Reduced return Reduced cost

NIL NIL

Total = 3000 Total = 170000

Net change = 170000 – 3000 = 167000 Powder turmeric price=100/kg

Opportunity for the Establishment of Processing Industry in the Study Area

Promoting processing of agricultural product could strengthen the link between agriculture and industry and help in generating farm income and employment as also in reducing wastage of agricultural products.

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The district observes the following scope for setting up of food/processing industry:

1 Availability of land for the building of industry.

2 Availability of dedicated human resources

3 Government support to encouraging of the establishment of the processing industry

4 Transportation facilities.

5 Potential of the district to produce organic turmeric

6 the vast untapped potential for food processing industry

tuRmeRic And itS PotentiAlS

Turmeric is one of most essential spices all over the world with a long and distinguished human uses. This spice with the flavor is obtained from the dried and grounded rhizomes of the plant. Apart from being a major ingredient in culinary, turmeric powder is used as a food-colouring agent and also as a natural dye. It is a very rich source of many essential vitamins such as pyridoxine (vitamin B6), choline, niacin, and riboflavin, etc. Turmeric contains good amounts of minerals like calcium, iron, potassium, manganese, copper, zinc, and magnesium. Turmeric has various properties like anti-inflammatory (painkiller), carminative, anti-flatulent and anti-microbial properties. The main compound present in turmeric i.e. cur cumin has anti-tumor, antioxidant, anti-arthritic, anti-amyloid, anti-ischemic, and anti-inflammatory properties. Apart from the above turmeric has also one promising potential of used as natural pesticides.

AgRo-PRoceSSing AS A WAy to double fARmeRS income

Agriculture and forestry remain the key source of livelihood in the study area supporting large sections of resource-poor people. The district endowed with a suitable agro-climatic condition for the cultivation of vegetables and spices (turmeric, ginger, pepper) which ultimately play a significant role in the promotion of food/pharmaceutical industry. This may act as a link between agriculture and industry sector. The emerging vegetable and spice products require suitable preservation and processing and appropriate marketing channels to reach the target market. Processing is a means of value addition to farm produced products and a link between the field and the plate. However, the proposed food/pharmaceutical-processing can become a major source of livelihood for the unemployed people of the district. The establishment of food/pharmaceutical processing industries is profound and deep with several institutions like farmer producer organization, retail organizations, small and medium enterprises, machine manufacturers and other agencies like small traders, transporters and women’s collectives having some roles. An improvement in one sector is likely to spill over into the other sector also.

The value addition for fresh turmeric is sorting, washing, cleaning, drying and packaging and value-added products can be turmeric powder, curry powder, turmeric oil, cur cumin, turmeric juice, turmeric root powder etc. value addition to the crops will generate more employment, increase income of self-employed people.

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induStRiAl ScenARio of KAndhAmAl diStRict

Type of Industry No. of Units

Agro-based 888

Textile based 241

Wood/wooden based furniture 153

Leather-based 24

Electrical machinery and electronics 7

Large Scale Industries / Public Sector undertakings Nil

Turmeric processing food/pharm industry 1

Source: Directorate of Industries, Odisha

In the district, only one turmeric processing plant is there at Bandhagada by KASAM (Kandhamal Apex Spices Association for Marketing), which is not sufficient.The plant undertook only turmeric powder preparation and to some extent turmeric oil, no other value addition was carried out.

concluSionS And Policy imPlicAtionS

To realize the goal of doubling farmers’ income by 2022-23, it is important that the farmers should not only streamline the production pattern of organic turmeric but also consider Processing as a means of value addition. Besides, effective post-harvest management and small-scale food processing, promotion of farmers producer organization would facilitate growth in farmers income.There is a need to prioritize areas for investment based on their potential to contribute to the targeted growth, and both the public and private sectors work in tandem to achieve the goal of doubling farmers ‘income. Improvement in the status of the farmer i.e. increasing the income of the group is possible only through diversification and commercialization of their agricultural activities. This is possible through bringing about institutional change, value chain integration developing human resources capital and through the participation of the non-governmental sector in agriculture. Persistent low level of farmer’s income can also cause a serious adverse effect on the future of agriculture in the country. To secure the future of agriculture and to improve the livelihood of the tribal farmers, adequate attention needs to be given to improve the welfare of farmers and raise agricultural income.

REFERENCES

[1] Ankita trebbin.2014.Linking small farmers to modern retail through producer organizations-experiences with producer companies in India, food policy,

[2] Christos A. Damalas, Potential uses of turmeric (Curcuma longa) products as alternative means of pest management in crop production, POJ 2011:4(3): 136-141.

[3] http//kandhamal.nic.in[4] http://diodisha.nic.in/[5] http://niti.gov.in[6] http://vikaspedia.in/agriculture/policies-and-schemes/policy-paper-on-doubling-farmers-income

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[7] Policy & Process Guidelines For Farmer Producer Organisations Govt. Of India Ministry Of Agriculture Dept. Of Agriculture And Cooperation, 2013

[8] Raka Saxena et al. 2017. Doubling Farmers’ Income in India by 2022–23: Sources of Growth and Approaches, Agricultural Economics Research Review, 30(2):265-277

[9] Sahoo PP.2017. Value Chain Analysis of Organic Turmeric In Kandhamal District of Odisha. M.Sc. (Agri) Thesis, Orissa University of Agriculture and Technology (India)

[10] SMALL FARMERS’ AGRI-BUSINESS CONSORTIUM , ANNUAL REPORT 2015-16 Department of Agriculture, Cooperation and Farmers’ Welfare, Ministry of Agriculture and Farmers’ Welfare, Government of India

[11] www.thehindubusinessline.com

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Review on: Response of Nitrogen, Sulphur and Foliar Application of Zinc on Growth, Yield, Quality and Economics of Green Gram (Vigna radiata L.)

Prasad Mithare*1, R.S. Muniswamy2, Rachana3 and Vikram Singh4

1-4Department of Agronomy, Allahabad School of Agricultural,

Sam Higginbottom University of Agriculture Technology & Sciences,

Allahabad- 211007, (Uttar Pradesh), IndiaE-mail: *[email protected]

ABSTRACT

Pulses play a significant role in Indian agriculture as they provide protein-rich components in the average human diet. They contain 20-24 percent i.e., about 2.5 times more amount of protein than in cereal and hence, offers the most practical means of eradicating malnutrition. India is a major pulse growing country of the world, sharing. Green gram is one of the widely cultivated short duration grain legumes in India and occupies third place after chickpea and Pigeonpea. It is one of the major protein rich pulse crop grown principally for both human and animal. Green gram can supplement the cereal-based diet to improve the nutritional value of food and has a special importance in the intensive crop production system of the country for its short growing period. Nutrient management is one of the most important factors in green gram that greatly affect the growth and yield of green gram. In general application of 25 kg N ha–1 + 40 kg S ha–1 + 0.1% zinc (Pre flowering and Pod initiation) significantly increased growth, yield, quality and economics parameters viz, Maximum plant height (65.30 cm), number of branches–1(3.47), number of nodules plant–1 (46.40), plant dry weight (7.7 g), number of pods plant–1(30.33), number of seeds pod-1

(10.33), Test weight (41.68 g), Seed yield (8.89 q ha-1), Stover yield (27.10 q ha–1) and Harvest index (32.82). Similarly application of 25 kg N ha–1 + 40 kg S ha–10.1% zinc (Pre flowering and Pod initiation) recorded maximum Gross return (` 44092.0 ha–1), Net return (` 24739.0 ha–1) and B:C ratio (2.30) while lowest attributes are recorded in (control) respectively.

Keywords: Sulphur; Legume, PPM; Foliar Spray; Stover

INTRODUCTION

Pulses are commonly known as foods legumes while are secondary to cereals in production and consumption in India. Pulses are an integral part of many diets across the globe and they have great potential to improve human health, conserve our soils, protect the environment and contribute to global food security. It is mainly grown for human consumption but also used as fodder for cattle and green manure for soil fertility. Seeds are mainly cooked, as ‘Dal’ in our country. Being a legume crop, black gram has the ability to fix atmospheric nitrogen

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ISBN: 978-93-88237-24-6

symbiotically with the nodule producing bacteria Rhizobium sp. Green gram is scientifically known as Vigna radiata (L.) and commonly known as moong in India. Greengram seeds are highly nutrition’s with protein (23-24%), carbohydrates (60%), minerals, amino acids, and vitamins. Nitrogen enhances the uptake of other nutrients and increasing nitrogen content in the crop which increases the protein content of Greengram. Responses of a green gram to added fertilizers such as nitrogen phosphorus, sulfur, & zinc have been found to vary with soil conditions.

The increase of pulse production is urgently needed to meet up the demand of the people to reduce import, to save foreign currency and to increase pulse consumption for maintaining good health. The increase of pulse production can also minimize the scarcity of fodder because the whole plant or it is by-products can be used as good animal feed. The increase of pulse production can also minimize the scarcity of fodder because the whole plant or it is by-products can be used as good animal feed. Pulses in India have long been considered as the poor man’s meat and important diet due to rich in protein that nutritionally imbalances the protein from cereal grain, supply minerals, and vitamins and provide an abundance of energy. But protein deficiency is a chronic problem in developing countries like India. The World Health Organization recommends a per capita consumption of pulses at 80 g per day and the Indian Council of Medical Research has a recommended a minimum consumption of 47 grams but at present, the per capita availability of pulses is only 40g per day in India Chaturvedi and Masood Ali 2002 (1). Modern intensive farming has resulted in higher demand for fertilizer because of removal of all the essential nutrients in higher proportions by the crops. Most of our attention for fertilizer use has been restricted to the use of N, P and K, the three primary nutrients required by the crops in large quantities. The United Nations, declared 2016 as International Year of Pulses (IYP) to heighten public awareness of the nutritional benefit of pulses as part of sustainable food production aimed at food security and nutrition. India is the largest producer and consumer of pulse contributes 25% of global production, 27% of world consumption and importer 14% of pulses in the world. The area under pulse has increased from 19 m ha–1 in 1950-51 to 25 m ha–1 in 2013-14, indicating an increase of 31 percent whereas production of pulse during the same period has increased from 8.41 million ha–1 to 19.27 million ha–1 an increase of over 100% GOI 2015 (2). In 2014-15 17.20 million tones and estimate production for 2015-16 about 18.32 million tons Commodity Profile: DES, DAC&FW, & DoC 2015 (3).

Green gram is a legume crop, it responds well to added nitrogen to overcome its lag phase and it influences nutrient uptake by promoting root growth and nodulation. Nitrogen enhances the uptake of other nutrients and increasing nitrogen content in the crop which increases the protein content of green gram. Application of small amount of nitrogen as a starter dose has a beneficial effect on crop yield and quality. Mineral nutrition of plants is still one of the most important factors determining the final production of plants. Nitrogen is an essential nutrient that is needed to grow plants in a large amount, needed for plant growth which its deficiency in the soil is usually common. Soil mineral fertilizers in agricultural systems are important institutions because the need for food plants resolves in the shortest possible time. Nitrogen deficiency reduces the number of branches per plant, plant height, stem diameter, pod length, number of nodes. Mungbean is one of the major crops having a high percentage of protein, for human nourishment. Adequate nitrogen is one of the most important management factors that cause increasing in seed yield Malik et al., 2003 (4).

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Review on: Response of Nitrogen, Sulphur and Foliar Application of Zinc on Growth 155

ISBN: 978-93-88237-24-6

Sulfur is recognized as fourth major plant nutrient along with N, P, K, a performance many important functions in the plant and plays an important role in improving yield and quality of pulses. Sulfur is required in the plant for the synthesis of chlorophyll and essential for activation of certain proteolytic enzymes such as papinase. Increased use of sulfur-free fertilizers, intensive cropping, and use of high-yielding varieties have led to Sulphur deficiency in many countries. Sulfur deficiency is increasingly becoming one of the limiting factors to further sustainable increase in agricultural production. Sulfur fertilizer, besides enhancing yield and quality of crops, enhances nutrient uptake, particularly nitrogen, and fertilizer-use efficiency through the interaction of sulfur with other fertilizer nutrients.

Sulfur is needed for conversion of reduced nitrogen into protein in symbiotic nitrogen fixation in pulses (like green gram), thus its positive effect on nitrogen absorption is quite likely. Sulfur not only improved grain yield but also improved the quality of crops Banik and Sengupta 2012 (5). Sulfur is an essential element for plant growth because it is present in major metabolic compounds such as amino acids (methionine and cysteine), glutathione, proteins, and sulpholipids in oilseeds and pulses. Pulses are particularly sensitive to S deficiency, which imparts the low quality of seeds and yield. Similarly, sulfur is also known to promote nodulation in legumes thereby enhancing the N fixation and also plays a vital role in protein synthesis Dhanushkodi et al., 2009 (6). The acidity produced by oxidation helps to solubilizing plant nutrients and improves alkali soils Surendra and Katiyar 2013(7).

Micronutrients are essential for plant growth; Zinc is one of the seven pillars of nutrition and is needed for the growth of the plant, animals, and humans. The amount of zinc in pasture and forage is very little and varies from 20 to 30 mg kg-1 in the soil. Zinc is involved in Auxin metabolism like, tryptophan synthesis, protein synthesis, the formation of nucleic acid and helps in the utilization of nitrogen as well as phosphorus by plants. Lack of zinc causes a deficiency in the formation of RNA and protein. Therefore, the plant with lack of zinc is poor in the amount of protein. Foliar spraying of microelements for the growth of green gram and its quality in industry views is necessary for growth and quality of green gram. The zinc fertilizer application causes root and shoot growth during the growing season and therefore, lead to increased seed yield. Spraying the leaves with the nutrient elements is one of the methods of plant supply. Although the leaves and shoots can absorb nutrients as well as water, gas through the stomata, leaf spraying method in addition to the rapid response, will also save money. The fertilization procedure in addition to economic aspects and the effectiveness of the immediate environment in order to achieve sustainable agriculture Fard et al., 2012 (8).

EFFECT OF NITROGEN ON GROWTH AND YIELD OF GREEN GRAM

Nitrogen is an essential plant nutrient being a component of amino acids, nucleic acids, nucleotides, chlorophyll, enzymes, and hormones. N promotes rapid plant growth and improves grain yield and grain quality through higher tillering, leaf area development, grain formation, grain filling, and protein synthesis. Nitrogen is so vital because it is a major component of chlorophyll, the compound by which plants use sunlight energy to produce sugars from water and carbon dioxide (i.e., photosynthesis). It is also a major component of amino acids, the building blocks of proteins. Among the nutrients, nitrogen is required in comparatively greater quantities than other essential elements derived from the soil. Nitrogen plays a vital role in the growth and consequently the yield of crops. Deficiency of soil nitrogen supply is one of the

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main limiting factors for achieving high rice yields. Hence, constant replenishment through extraneous nitrogen inputs becomes mandatory for optimal yield. The application of 20 kg Nha-1significantly increase the plant height number of nodules and grain yield (9.5%) over the control in green gram Carangalet al., 2000 (9).The research trial conducted byRudreshappa and Halikatti 2002 (10) observed that application of 12.5 kg N ha-1 recorded significantly higher grain yield (764 kg ha-1), haulm yield (1662 kg ha-1) as compared to control. Fertilizer combination of 25-75 kg NP ha-1 resulted in maximum seed yield (1112.96 kg ha-1) and maximum protein content (25.6%) was obtained from plots fertilized @ 50-75 kg NP ha-1 followed by the protein content of 25.1% obtained from plots fertilized @ 25-75 kg NP ha-1. The highest net income (Rs. 21374.9) was also obtained by applying N and P @ 25 and 75 kg NP ha-1 respectively Malik et al.,2003 (4). A similar experiment conducted by Kumar and Jayakumar 2004 (11) reveals that application of 50 kg N ha-1 excelled other treatments in increasing the growth, yield characters and protein content of green gram.

Choudhary et al.,2014 (12)revealed that significant variations among the different treatments combination in terms of nodulation, growth, yield, and quality. The result showed that Bradyrhizobiuminoculation significantly increased the number of pod plant-1, number of seedpod-1, 1000 seed weight, stover yield, and grain yield. The highest number of pod plant-1 (18.78), number of seed pod-1 (11.89), 1000 seed weight (43.40 gm), stover yield (3.80 t ha-1) and grain yield (1.92 t ha-1) were recorded the application of 30 kg N ha-1. The different fertilizer levels did significantly (p<0.05) influenced most of the growth attributes of the mungbean. Maximum days to flowering (48.25) and a number of branches plant-1 (3.83) were recorded for plants subjected to the highest dose of applied N fertilizer viz., 100 kg ha-1. Similar responses towards added N fertilizer also noted for various cultivars of mungbean Khan et al., 2012 (13). The application of 30:60:00 kg NPK ha-1 recorded significantly higher growth and yield contributing characters followed by application of 25:50:00 NPKha-1and 20:40:00NPK ha-1. The highest seed yield of 8.9 grams m-2 and the number of sub-branches with (1.5) and the height of the first pod from ground level with (25.51 cm) and stem diameter (1.13 cm) and number of nodes (8.28) and pod length (7.5 cm) was obtained at 150 kgha-1 ureaRathod and Gawande2012 (14).

The application of 30 kg N ha-1significantly differed in plant height, the weight of pods plant-1, seed and straw yields-1, Nand protein contents in the seeds. Giza-88 cultivar significantly surpassed Giza-2 cultivar in plant height, a number of pods plant-1, the weight of pods plant-1, seed yield plant-1, seed, and straw yields-1. The combination of Zn foliar application at different growth stages and nitrogen fertilizer treatments resulted in significant effects on plant height, number, and weight of pod plant-1, seed yield plant-1 and seed, straw and biological yield ha-1Habbashaet al.,2013 (15). The basal dose of 20 kg N ha-1 and 20 kg N ha-1as split + one irrigation at flower initiation gave maximum plant m-2, plant height, number of branches plant-1 and number of trifoliate leaves plant-1 followed by 15 kg N ha-1as basal and 15 kg N ha-1as split + one irrigation at flower initiation and 10 kg N ha-1as basal and 10 kg N ha-

1as split + one irrigation at flower initiation and lowest in control. The seed yield of green gram was significantly higher over control due to an increase in the number of pods plant-1 (43.4), pod length (10.4 cm), number of seeds pod-1(10.5), test weight (46.3 g), yield per plant (5.60 g) and seed yield (16.6 q ha-1). The highest germination percentage, vigor index, nitrate, and nitrite reductase activity were observed with 20 kg N ha-1as basal and 20 kg N ha-

1as split + one irrigation at flower initiation (100.0). The maximum seedling dry weight was

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recorded with the application of 10 kg N ha-1as basal and 10 kg N ha-1as split + one irrigation at first flower initiation stage (156.0) which was on par with 40 kg N ha-1as basal dose Manoj et al., 2014 (16). Similarly, the experiment conducted by Sharma and Sharma2014 (17)reported that application of S alone or combined with N significantly increased plant height, number of seeds per pod and total seed yield. S containing amino acids viz., methionine and cysteine increased significantly (P≤0.05) by all the treatments in comparison to control and a maximum increase of 1.3 fold was observed by urea application.

EFFECT OF SULPHUR ON GROWTH AND YIELD OF GREEN GRAM

Sulfur is one of the essential plant nutrients for all plants and is indispensable for growth and metabolism. Sulfur has a number of oxidizing function in soil and plant nutrition. It is a constituent of certain amino acids like methionine, cystine and cysteine and also a constituent of Fe-S proteins called ferredoxin. Sulfur is also known to promote nodulation in legumes thereby enhancing the N fixation. It is a constituent of a free amino acid such as methionine, cysteine, and plays a vital role in protein synthesis. Gypsum is preferred more as a source of sulfur because of its diverse role in soil especially in saline and alkaline soils; gypsum is also used as amendments. The objective is to bring soil pH to range favorable for nutrient availability, plant growth, and development.

Sulfur at 40 kg ha-1 exhibited its superiority by registering the highest number of pods plant-1 which was on par with 30 kg ha-1. Also, there is a significant effect of source and levels of S on grain yield of black gram during both the seasons. Gypsum yielded 1245 kg ha-1 and 979 kg ha-1 of grain during kharif and rabi season of 1995 while it was 1209 kg ha-1 and 1023 kg ha-1

during 1996 respectively Srinivasan et al., 2001 (18). Sulfur at 30 kg ha-1 application resulted in increased growth attributes, yield attributes & protein content. The S-containing amino acids viz; methionine, Cystine and cysteine content of the grains, were highest with the application of 30 kg S ha-1, which was at par with the application of 20 kg S ha-1Shahi et al., 2002 (19). The yield attribute except for pod length and the number of grains pod-1 of green gram increased significantly with increasing level of sulfur 30 kg ha-1Singh et al., 2004 (20). Sulfur at 40 kg ha-1 gave the highest number of pods plant-1, a number of seed pod-1, 1000 - Seed weight, seed yield, net return, and rupees invested Mitra et al., 2006 (21).

The application of 30 Kg S ha-1and 5 Kg Zn ha-1 produced a significantly higher number of pods plant-1, numbers of grains pod-1, test weight grain and straw yield of a green gram over control. Significantly higher N, P, K, S and Zn uptake was also recorded with the same treatment. Protein content also increased significantly with Rhizobium inoculation, S and Zn application over control Srivastava et al., 2006 (22). Successive increase in Sulphur levels up to 20 kg ha-1 significantly increased plant height, number of leaves plant-1, and number of branches plant-1, plant dry weight, seed and straw yield by 3.67, 21.29, 5.29, 8.12 and 5.92 percent, respectively. Application of 40 kg S ha-1 showed a significant increase in the length and vertical spread of root, nodules/plant and dry weight of nodules at 40 and 60 DAS over 20 kg S ha-1 and control Rahul et al., 2007 (23). A similar trend was observed in case of grain yield, with the application of 40 kg S ha-1 recorded the highest grain yield of black gram 980 kg ha-1. Application of 20 kg ha-1sulphur as gypsum synthesized more protein and account as 24.45% and application of sulfur recorded significantly higher number of pods per plant (22.77), pod length (5.10 cm), seed per pod (6.77) and 100 seed weight (4.88 g) also synthesized more

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protein and accounted as 24.48 percent Govind et al., 2008 (24). Rhizobium inoculation with sulfur and micronutrients give maximum grain yield (11.32 and 10.81 q ha-1) as compared to any other treatment. Yield attributing characters like a number of pods (55 and 54) and 100-grain weight (4.69 and 4.165) were also higher in the treatment comprising Rhizobium, sulfur and all the micronutrients Brijesh et al., 2009 (25).

Kaiser et al., 2010 (26) reported that sulfur at 30 kg ha-1and boron at 5 kg ha-1 significantly increased plant height, number of branches plant-1, number of pods plant-1, number of seeds pod-1, 1000 seed weight, seed yield and protein content(%). Sulfur application of 30 kg ha-1 significantly influenced the quality parameters, growth and yield attributes viz. plant height at 40 DAS and at harvest, number of branches plant-1, seed and straw yields and protein content, as well as chemical parameters such as uptake of S showed the similar trend Patel et al., 2010 (27). Application of P 50 kg ha-1 was optimum to harvest maximum yield of green gram and S application at 40 kg ha-1 was beneficial to increase growth and yield of green gram while there was no positive effect of P and S interaction on growth and yield of green gram Patel et al., 2011 (28). The number and weight of nodules, grain and straw yield, the content of P and S were increased with an increase in the level of P and S individually as well as in various combinations. Applied P and Increased grain N and protein contents Yadav et al., 2011 (29).Similarly Banik and Sengupta 2012 (5) reported that application of gypsum at 30 kgha-1 with recommended a dose of NPK gives highest seed yield of green gram crop, growth characters like plant height and dry matter production and seed yield were significantly higher than the control.

Fardet al., 2012 (8) revealed the superiority of the length of main stem’s pod number, main stem node number, the node number of lateral stem and seed yield was obtained in the method of spraying. Analysis of variance showed that the effect of plant density on seed yield, plant height, pod length in the main stem and main stem node number was significant and the highest yield of 1787.5 kg ha-1was related to the density of 33 plants m-2 and one spraying and this treatment is justified for the region. Application of 45 kg S ha-1 recorded significantly highest yield (grain and straw) and yield attributing characters viz. a number of pods, pod length, seed per pod and 1000 seed weight, similarly increase in protein content were recorded with the application of 45 kg S ha-1 Tripathi et al., 2012 (30). The 45 kg S ha-1recorded higher plant height, primary branches, green trifoliate, leaf area index, dry matter accumulation, nodule numbers, and nodule dry weight, increased days to maturity, number of the pod and higher grain and straw yield Tripathi et al., 2012 (30).

Jawahar al., 2013 (31)revealed that application of 40 kg S ha-1 recorded highest growth (plant height, leaf area index, chlorophyll content, dry matter production and number of branches plant-1), yield components (number of pods plant-1 and number of seeds pod-1) and yield (grain and haulm) of black gram. Application of S @ 40 kg ha-1recorded maximum plant height (47.31 cm), number of leaves plant-1 (49.80), number of nodules plant-1 (25.58), haulm yield (28.80 q ha-1), grain yield (7.92 q ha-1) and, S and protein content (0.295 , 0.281 and 21.79% respectively) Mir et al.,2013 (32). The research trial conducted by Patel et al., 2013 (33)reported that 40 kg S ha-1recorded significantly maximum number of branches plant-1(4.48), plant spread (34.10), number of nodules plant-1 (16.46), dry matter plant-1 (9.27g), seed yield (1486.08 kg ha-1), stalk yield (2161.79 kg-1) and protein content (22.46%) as well as gave the highest net realization(Rs.28,440 ha-1) with a net ICBR (1: 27.63). Surendra and Katiyar 2013 (7) revealed that application of 40 Kg S ha-1 and 10 Kg Zn ha-1 significantly increased the

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plant height, number of branches plant-1, number of nodules plant-1, number of pods plant-1, number of seeds pod-1, seed yield, protein content (%) and test weight was non-significant. The interaction effect between S and Zn on various parameters of summer mungbean was found significant and test weight was found non-significant during both the years. The highest seed yield (13.69 and 14.40 q ha-1) was observed in combination with 40 Kg S ha-1and 10 Kg Zn ha-1 which was significantly superior over rest of the combinations.

Barret al.,2014 (34)reported that application of 45 kg S ha-1 produced significantly higher grain (743 kg ha-1) and stover (12264 kg-1) yields. He also reported that increase in the application of sulfur led to an increase in the concentration and in turn uptake of N, P, K, Sand B in pods, seeds as well as stover up to 45 Kgha-1. However, the increase in nutrient concentration and uptake parameters with the increase in sulfur from 30 Kgha-1to 45 Kgha-1showed no significance. Kumawat et al., 2014 (35) in their experiment showed that significantly the highest plant height (43.53 cm), number of branches per plant (5.79), leaf area index (3.97, 4.17 and 4.65 at 20, 40 and 60 DAS, respectively) and dry matter content (4.64, 7.63 and 10.65 g plant-1 at 20, 40 and 60 DAS, respectively) were observed in treatment S3 (30 kg Sha-1). With respect to yield attributes and yield, the results indicated that significantly the maximum number of pods plant-1 (20.47), the weight of 100 seeds (4.07 g), seed yield (819 kgha-1) and straw yield (1551 kg-1) were found with the application of 30 kg Sha-1. Similar findings are also confirmed by Sharma and Sharma 2014 (17) reported that gypsum at 20 kg S ha-1 alone or in combination with recommended doses of N for soybean improved the storage protein and yield and also reported that improvement of soybean nutritional quality can be achieved by application of gypsum at 20 kg S ha-1.

Application of 36 kg N, 70 kg P2O5 and 30 kg S/ha gave the maximum values of growth parameters, yield attributes, and grain yield as well as removal of N, P and S over lower fertility levels. Further, under interaction effect the significantly highest grain yield was observed with the treatment combination of Rhizobium + PSB + 36 kg N, 70 kg P2O5, 30 kg S kg ha-1 (964.9 kg ha-1) but remained at par with medium level of fertility 24 kg N, 50 kg P2O5, 20 kg S/ha (941.6 kg ha-1) applied along with Rhizobium and PSBKudi and Singh 2016 (36).

Gokila et al., 2017 (37) concluded that highest growth parameters such as plant height (54.7 cm, 55.9 cm), Number of leaves plant-1 (54.8, 58.8), Number of pods plant-1 (34.7, 38.8), Number of seed pod-1 (7.4, 8.4) like yield parameters such as grain (1145, 1275 kg ha-1) and straw yield (1645, 1990 kg ha-1) viz., protein (23, 24.2 %) and methionine (8.92, 8.97 mg g-1) were significantly increased by the different S sources when compared to control in Vylogam and Peelamedu series. Irrespective of the different S sources, S @ 20 kg ha-1 as K2SO4 coupled with a recommended dose of fertilizers plus 0.5 % K2SO4 foliar spray at 30th and 45th DAS have significantly registered a better response in black gram. Similar trends of results are confirmed by Mithare et al., 2017 (38) revels that application of 40 kg Sulphur ha–1+ 5.0 kg Zinc ha–1 + 1.0 kg Molybdenum ha–1 + 40 ppm NAA significantly increased growth and yield parameters viz. Plant height (31.0 ppm), number of branches plant–1 (19.40), number of nodules plant–1 (28.33), number of pods plant–1 (31.46), seed yield (8.63 q ha–1), stover yield (23.73 q ha–1) and harvest index (36.39) respectively.

EFFECT OF ZINE ON GROWTH AND YIELD OF GREEN GRAM

Application of Zn, K or Mg had a positive effect on growth parameters, yield, and yield components but K application surpassed the two other nutrients Tooth et al., 2006 (39).

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The combined application of soil (5.5 kg Zn ha-1) and foliar application of Zn(two sprays of 0.1% Zn, one at pre-flowering and another at pod initiation stage) resulted in a 5.5 fold increase in Zn concentration in straw and a 3.5 fold increase in seed over the control Detroit al., 2007 (40). Effect of zinc on growth, yield, and quality of black gram was experimented by various scientists and research persons in different agro-climatic conditions across the country. The application of Zn results in the enhancement of grain yield and quality. Zinc application also contributed in an increase in seed yield probably owing to its influence on Auxin synthesis, nodulation, and nitrogen fixation, which promoted plant growth and development, thereby favorably influencing grain yield Sharma and Abraham 2010 (41). The research experiment conducted byPathak and Pandey 2010 (42) reported that foliar applications of Zn showed the morphological changes in pollen shape and size with changes in the exine ornamentation. Foliar application of Zn also improved the yield, boldness, vigor, and viability of seeds. Seed Zn was also appreciably enhanced in Zn sufficient plants given foliar Zn. Nasir et al., 2011 (43) observed that N, K and Zn-foliar application significantly affected Zn in pod, nitrate in pod, carbohydrate percentage, carbohydrate yield, protein percentage,protein yield, chlorophyll of leaf, radiation use efficiency, extinction coefficient, number of plant in m-2, number of cutting in plant, number of pod in plant, number of pod in m-2, number of seed in pod, 100 seed weight,fresh pod yield, seed yield, biological yield, harvest index and plant height. Fard et al.,2012 (8)observed that spraying the leaves with the nutrient elements is one of the methods of plant supply. Although the leaves and shoots can absorb nutrients as well as water, gas through the stomata, leaf spraying method in addition to the rapid response, will also save money. The fertilization procedure in addition to economic aspects and the effectiveness of the immediate environment in order to achieve sustainable agriculture is also very effective and useful. Similar results are confirmed by Arora et al., 2012 (44).

Ali and Mahmoud 2012 (45) reported that foliar application of salicylic acid enhanced significantly plant height, number of branches plant-1, number of pods plant-1, number of seeds pod-1, 1000 seeds weight, seed weight plant-1 and seed yield ha-1 as compared with control and the superiority was due to the high salicylic acid concentration. A significant increase in all above mention traits occurred with foliar application of zinc as compared with untreated plants. Lateef et al.2012 (46)revealed that micronutrient application showed beneficial effects on yield and yield components from the association of urea with Zn on pod-number and with all micronutrients on pod-weight plant-1. The highest seed yield per plant was recorded when the plants were foliar sprayed with Fe and Mn alone or Urea+Zn. However, the highest seed yield ha-1 was achieved by foliar spraying with Fe or Zn alone as well as by the combined application with urea Fe, Mn or Zn. Foliar spray of urea combined with Fe or Zn may increase seed yield and improve the quality of seeds. Zinc is involved in Auxin metabolism like, Tryptophane synthesis, tryptamine metabolism, protein synthesis, the formation of nucleic acid and helps in the utilization of nitrogen as well as phosphorus by plants. Zinc also stimulates resistance for dry and hot weather, bacterial and fungal diseases and ribosomal fraction in the plants. It also promotes nodulation and nitrogen fixation in leguminous crops Patel et al., 2013 (33). Similarly, application of zinc also increased the growth, yield attributes and significantly up to 10 kg Zn ha-1 during both the years. The magnitude of increase in seed yield was 23.82% in the first year and 25.48% in the second year by seed, respectively as compared to control. The increase in growth, yield attributes and yield might be due to the role of zinc in the biosynthesis of indole acetic acid (IAA) and especially due to its role in initiating of primordial for reproductive parts and partitioning of photosynthesis towards them which resulted in better flowering and fruiting

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Surendra and Katiyar2013 (7). Similar trends are observed by Upadhyay et al., 2013 (47) reveals that increase in the level of zinc from 0 to 6 kg ha-1 resulted in a significant increase in the grain yield of lentil from 17.22 to 18.85 q ha-1.

Roy et al.,2013 (48) reported that application of 5.5 kg Znha-1 + 0.1% Zn foliar spray increased the straw yield by 56.6% seed yield by 57%, concentration, and its uptake in seed and straw in green gram. Samreenet al.,2013 (49) reported that plant growth, chlorophyll contents, crude proteins, and Zn contents were noted to be higher when a greater supply of zinc doses was applied. Plant phosphorous contents declined with a supply of Zn from 1 M to 2 µM compared to the control signifying a Zn P-1 complex foundation possibly in roots of the plant, preventing the movement of P to plant. Khan and Prakash 2014 (50) reported that maximum plant height 24.75 cm and the number of primary 4.11 and secondary branches 13.46 plant-1of urdbean was significantly increased with the application of 2.5 kg Zn ha-1 as compared to control. The significantly higher number and dry weight of nodules plant-1 5.55 23.78 and 7.58 13.82 at 30 and 45 days after sowing was recorded with the application of2.5 kg Zn ha-1 as compared to control. Similarly, grain and stover yield of urdbean significantly increased up to 5.0 kg Zn ha-1

and grain and stover yield at this level was 11.60 q ha-1and 21.87 q ha-1 respectively. Highest grain yield 14.59 and 14.25 g pot-1 were obtained when S (40 ppm) and Zn (5 ppm) were applied individually. The highest yield attributes vizplant height(43.5 cm), branches plant-1(6.7), capsule plant-1(13.0), grain capsule-1(3.2), 100-grain weight(996 g)were also obtained for treatment combination of 40 ppm S and 5 ppm ZnChoudary et al.,2014 (12). The combined soil application of Zn @ 5 kg ha-1+ one foliar spray of Zn @ 0.5% significantly increased the seed and straw yields, net returns, protein content, N, P and Zn content in seed and straw and total uptake of N, P and Zn over control and it remained at par with soil application of zinc @ 5 kg ha-1Puniyaet al.,2014 (51).

CONCLUSION

From the present study conducted in the response to nitrogen, sulfur and foliar application of zinc on growth, yield, quality, and economics of green gram (Vigna radiata L.). The data pertaining from the different reviews, it may be concluded that by using 25 kg nitrogen ha-1+ 40 kg sulfur ha-1+0.1% ZnSO4 (Pre flowering & Pod initiation) was found to be the best for obtaining highest growth, yield, quality attributes and economics Viz, Seed yield, Stover yield, protein content and benefit-cost ratio, over control. The findings are similar to various reviews which are presented in this article. This study will be helpful in increasing the green gram production and productivity per unit area by using necessary essential nutrients; Nitrogen, Sulphur, and Zinc (Foliar spray). Similarly, it helps to meet the daily protein, vitamin & minerals requirement in terms of nutritional security. The stover after the harvest of the crop is feed to cattle’s to meet out the forage requirement during the lean period for getting a higher income to small and marginal farmers.

ACKNOWLEDGMENTS

The author acknowledges the Department of Agronomy, Allahabad School of Agricultural, Sam Higginbottom University of Agriculture Technology & Sciences, Allahabad (Uttar Pradesh) for providing financial support to carry out the work.

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REFERENCES

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[15] Habbasha, S. F., Mohamed, H. S., Lateef, E. M., Mekki, B. B. and Ibrahim, M. E. (2013). Effect of combined zinc and nitrogen on yield, chemical constituents and nitrogen use efficiency of some chickpea cultivars under sandy soil conditions,World Journal of Agricultural Sciences, 9 (4): 354-360.

[16] Manoj, Singh, R. K., Singh, A., Ram, H. and Prasad, S. R (2014). Growth, yield attributes and quality of summer greengram (Vigna radiata L.) as influenced by nitrogen and irrigation levels. Ann. Agric. Res., 35 (1):47-53.

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[18] Srinivasan. K, Sankran. N and Prabhakaran. J. (2001). Influence of sulphur application on nodulation and protein content of blackgram. Madras Agri. J. 87(7/9): 456-458.

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[23] Khatkar Rahul, Abraham Thomas and Joseph Ann Shalu.(2007). Effect of biofertilizers and sulphur levels on growth and yield of Black gram (Vigna mungo (L). Legume Res. 30(3):233-234.

[24] Kumar Govind, Shrivastava G. P. and Kumar Rakesh. (2008). Rooting Pattern of Blackgram as Influenced by Levels of Phosphorus, Sulphur and PSB in Blackgram-Toria Cropping System. Journal (BAU). 2008; 20(1), 19-24.

[25] Rathi Kumar Brijesh, Jain Kumar Amit, Kumar. S and Panwar J.D.S. (2009). Response of rhizobium inoculation with sulphur and Micronutrients on yield and attributes of Black gram (Vigna mungo (L.). Legume Res. 32(1):62-64.

[26] Kaisher, M. S., Rahman, A. M., Amin, M. H. A. (2010). Effect of sulphur and boron on the seed yield and protein content of mungbean (vigna radiata (L.). Bangladesh Research Publications Journal.3 (4):1181-1186.

[27] Patel, P. M., Patel, J. S., Patel, J. J., and Patel, H. K. (2010). Effect of levels & sources of sulphur on seed yield and quality of summer greengram. International J. of Agricultural Sciences, 6(1):169-171.

[28] Patil S.C, Jagtap, D.N. and Bhale V.M.(2011). Effect of phosphorus and sulphur on growth and yield of mungbean (Vigna radiata L). International Journal of Agriculture Sciences. 7(2):348-351.

[29] Yadav, B. K. (2011). Interaction Effect of Phosphorus and Sulphur on Yield and Quality of Clusterbean in Typic Haplustept.World Journal of Agricultural Sciences, 7 (5): 556-560.

[30] Tripathi, P. K., Singh, M. K., Singh, J. P. (2012). Effect of rhizobial strains and sulphur nutrition on mungbean (vigna radiata (L.) wilczek) cultivars under dry land agro-ecosystem of indo- Gangetic plain. African Journal of Agricultural Research, 7(1):34-42.

[31] Jawahar S, Vaiyapuri V, Suseendran K., Kalaiyarasan and Sri Ramachandrasekharan M.V. (2013). Effect of sources and levels of sulphur on growth and yield of rice fallow black gram (Vigna mungo). International research Journal of Chemistry (IRJC). (1):2321-2845.

[32] Mir A.H, Lal S.B, Salmani. M, Abid. M and Khan. I. (2013). Growth, yield and nutrient content of blackgram (Vigna mungo) as influenced by levels of phosphorous, sulphur and phosphorous solublizing bacteria. SAARCJ. Agri. 11(1): 1-6.

[33] Patel H. R., Patel H. F., Maheriya V. D. and Dodia I. N. (2013). Response of kharif greengram (Vigna radiata L) to sulphur and phosphorus fertilization with and without. The Bioscan an International Quarterly Journal of Life Sciences. 8(1): 149-152.

[34] Bairwa, R. K., Nepalia, V., Bala, C. M., Jalwania, R. and Meena, H. P. (2014).Yield and nutrient uptake of summer greengram(vigna radiata (L.) wilczek) under different levels of phosphorous and sulphur fertilizations, SAARC J. Agri., 12(1);162-172.

[35] Kumawat Ram Sita, Khistriya M.K, Yadav S.L and Kumar Manoj.(2014). Effect of sulphur and phosphorus on growth and yield attributes on summer green gram (Vigna radiate L.). International Journal of Agricultural Science. 10(2): 770-773.

[36] Kudi V.K. And Singh J.K. (2016). Effect of Biofertilizers and Fertility Levels on Blackgram (Vigna Mungo L.) Under Custard Apple (Annona Squamosa L.) Based Agri-Horti System In Vindhyan Region Of Uttar Pradesh.International Journal of Agriculture Sciences. 52(8) 2534-2537.

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[37] B. Gokila, K. Baskar and P. Saravanapandian. (2017).Nutritional Significance of Sulphur on Growth, Yield and Quality of Blackgram in Major Contrasting Soil Series of Tamil Nadu, India. Int J Curr Microbiol. App Sci. 6(11):3139-3149.

[38] Prasad Mithare, Joy Dawson, R. S. Muniswamy and Rachana. (2017). Response of Secondary, Micro Nutrients and Naphthalene Acetic Acid (NAA) on Growth, Yield and Economics of Summer Blackgram [Vigna mungo (L.) Hepper]. Environment & Ecology. 35(4): 2769-2775.

[39] Thalooth. A, T. Tawfik M. M and Mohamed H. M. (2006). A Comparative Study on the Effect of Foliar Application of Zinc, Potassium and Magnesium on Growth, Yield and Some Chemical Constituents of Mungbean Plants Grown under Water Stress Conditions.World Journal of Agricultural Sciences. 2(1): 37-46.

[40] Debroy, P., Narwal, R. P., Malik, R. S. (2007). Response and enrichment of greengram (vigna radiata L.) Genotypes with respect to zinc application. Directorate of Research, CCS Haryana Agricultural University, Hisar, India.

[41] Sharma Vishal and Abraham Thomas.(2010). Response of blackgram (Phaseolus mungo) to nitrogen, zinc and farmyard manure. Legume Res. 33(4): 295-298.

[42] Pathak, G. C., and Pandey, N. (2010). Improving zinc density and seed yield of greengram by foliar application of zinc at earlier reproductive phase. Indian Journal of Plant Physiology, 15(4):338-342.

[43] Nasri, M., Khalatbari, M. and Farahani, H. S. (2011). Zn-foliar Application Influence on Quality and Quantity Features in Phaseolous Vulgaris under Different Levels of N and K Fertilizers.Advances in Environmental Biology, 5(5): 839-846.

[44] Arora A. S., Umer, S. and Mishra, S. N. (2012). Boron and zinc response on growth in greengram under salinity. International Journal of Plant, Animal and Environmental Sciences, 2 (4):131-137.

[45] Ali, E. A. and Mahmoud, A. M. (2012).Effect of foliar spay by different salicylic acid and zinc concentrations on seed yield and yield components of mungbean in sandy soil. Asian Journal of Crop Sciences.

[46] Lateef, A. E., Tawfik, M. M., Hozyin, M., Bakry, B. A., Elewa, T. A., Farrag, A. A. and Amany (2012). Soil and foliar fertilization of mungbean (Vigna radiata (L) wilczek) under Egyptian conditions. Elixir Agriculture, 47(5):8622-8628.

[47] Upadhyay Kumar Akhilesh. (2013). Effect of sulphur and zinc nutrition on yield, uptake of nutrients and quality of lentil in alluvial soil. Annals of Plant and Soil Research.15(2): 160-163.

[48] Roy, D. P., Narwal, R. P., Malik, R. S. and Kumar, S. (2013). Impact of zinc application methods on greengram (Vigna radiata L.) productivity and zinc fortification. Journal of Environmental Biology, 35:851-854.

[49] Samreen, T., Humaira, Hamid, U. S., Saleem, U. and Javid, M. (2013). Zinc effect on growth rate, chlorophyll, protein and mineral contents of hydroponically grown mungbean plant (Vigna radiata). Arabian Journal of Chemistry.

[50] Khan Khalil, Prakash Ved. (2014). Effect of rhizobial inoculation on growth, yield, and economics of summer urdbean (Vigna mungo L.) in relation to zinc and molybdenum. J Food Leg. 27:261-263.

[51] Puniya, M. M., Shivran, A. C., Khangarot, S. S., Kuri, B. R. and Choudhary, S. P. (2014). Effect of phosphorus and zinc fertilization on productivity and nutrient uptake of mothbean. Annals of Agricultural Research, 35 (1): 58-61.

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Effect of Different Levels of N P K and Rhizobium on Soil Physico-Chemical Properties and Yield Attribute of Black Gram (Vigna Mungo L.) VAR. SHEKHAR–2

Raghu Nandan Singh Khatana1, Tarence Thomas2 and P. Smriti Rao3

1-3Soil Science and Agricultural Chemistry, SHUATS, Prayagraj 211007

ABSTRACT

A field experiment was conducted during the kharif season of 2018 in black gram (var. SHEKHAR-2) at Research farm, Department of Soil Science and Agricultural Chemistry, Naini Agricultural Institute, SHUATS, Prayagraj (U.P.). The experiment was laid out in a Randomized Block Design with nine treatment combinations, consisting of three N P K levels (0, 50 and 100%) and Rhizobium (0, 50 and 100%). The treatment T8 [100% NPK ha-1 + 100% Rhizobium] showed that plant height (41.50 cm), no. of leaves plant-1 (31.00) and pod length (10.00 cm), no. of seed pod-1 (10.10) and it also gave the highest yield (6.80 q ha-1). Also in post soil analysis, Organic carbon (0.55%), available nitrogen (344.23 kg ha-1), phosphorus (32.80 kg ha-1) and potassium (208.83 kg ha-1) respectively were found significantly higher as compared to other treatment combination.

Keywords: Black Gram; NPK Levels; Rhizobium; Soil parameters

INTRODUCTION

Black gram (Vigna mungo L.) is one of the important pulse crops grown throughout India. Proper fertilization is essential to improve the productivity of black gram. It can meet its nitrogen requirements by symbiotic fixation of atmospheric nitrogen. It is a short duration crap and adaptability to offseason, it fits well in many intensive crop rotation. Pulses are one of the second most important segments of Indian agriculture after cereals as they rich in protein and play a vital role in the human diet. In India, production of pulses is around 19.3 million tonnes with a very low average productivity of 764 kg ha-1. Pulses are least preferred by farmers because of high risk and less remunerative than cereals; consequently, the production of the pulses is sufficiently low. Among pulses, black gram has increased from 1.87 m ha in 1971–72 to 3.11 m ha during 2012-13 with a production level of 1.90 million tonnes by ESI, 2015.

Urdbean [Vigna mungo (L.) ] is among the major pulses grown throughout the country during both in summer and rainy season. It is a self-pollinated leguminous crop containing 24% protein, 60% carbohydrate, 1.3% fat, 3.2% minerals, 0.9% fiber, 154 mg calcium, 385 mg phosphorus, 9.1 mg iron and a small amount of vitamin B-complex.

Urdbean contributes about 13 percent of the total area and 10 percent production of pulses in our country. This crop is extensively grown in the states of Maharashtra (23.36%), Andhra

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Pradesh (18.50%), Uttar Pradesh (12.29%), Madhya Pradesh (11.86%), Tamil Nadu (8.64%) and Rajasthan (4.29%). It can be grown on all type of soils ranging from sandy loam to heavy clay except alkaline and saline soils. However, it does well on heavier soils such as black cotton soils which retain higher moisture for a longer time.


The experiment was conducted in the research farm of the Department of Soil Science and Agricultural Chemistry, SHUATS, Prayagraj. The experimental site is located in the sub– a tropical region with 250 28’46.14” N latitude, 810 54’49.95” E longitude and 98m above the mean sea level altitudes. The experiment was laid out in a Randomized Block Design with nine treatment combinations, consisting of three N P K levels (0, 50 and 100%) and Molybdenum (0, 50 and 100%). The Prayagraj will be situated in Southeast of Uttar Pradesh, which experiences extremely hot summer and fairly cold winter. The maximum temperature of the location reaches up to 460C – 480C and seldom falls as low as 40C – 50C. The relative humidity ranged between 20 to 94 percent. The average rainfall in this area is around 1100 mm annually. The recommended dose of fertilizers such as Nitrogen (20 kg ha-1), Phosphorus (40 kg ha-1), Potassium (20 kg ha-1) and Rhizobium (20 gm/kg seeds) respectively were applied into the field. Half dose of nitrogen and a full dose of phosphorus and potassium were applied before sowing of black gram. The Black gram Var. SHEKHAR-2 was sowing on 25th July 2018. The data were calculated with their formula.

RESULTS AND DISCUSSIONS

Effect on growth and yield attributes Among NPK and Rhizobium levels in black gram, application of 100% NPK + 100 % Rhizobium produced significantly higher growth attributes characters, i.e. plant height (41.50 cm), No. of leaves plant-1 (31.00), No. of pod plant-1 (32.50), No. of seed pod-1 (10.10), No. of nodules plant-1 (23.00), Plant Dry weight (11.90 g), Test weight (47.01 g) and Seed yield (6.80 q ha-1) respectively. The increase in nodulation and nitrogen fixation leads to more plant height and Increase in a number of leaves may be due to adequate nutrients supply which enhanced the vegetative growth of the plant and subsequently the number of leaves. Similar findings were reported by Hussain et al. (2012).

An adequate supply of NPK and Rhizobium, which in turn help in the vigorous vegetative growth of plants and subsequently increase the number of seed pod-1, No. of nodules plant-1, Plant Dry weight and Test weight through cell elongation, cell expansion, cell division, photosynthesis and turbidity of the plant cell. Similar findings were also reported by Hussain et al. (2012). Application of NPK increased supply of major assimilated as well as micronutrient to plants. Similar results were also reported by Singh et al. (2016).

EFFECT ON YIELD

On the basis of above findings it can be concluded that for obtaining higher seed yield, number of pod plant-1 and other growth and yield attributes were found to be the best treatment 100% NPK + 100% Rhizobium with black gram variety SHEKHAR-2. These findings are based on 1 season; therefore, further trials may be required for considering it for the recommendation.

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Effect of Different Levels of N P K and Rhizobium on Soil Physico-Chemical Properties 167

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Tab

le.1

: E

ffec

t of

Dif

fere

nt L

evel

s of

NP

K a

nd R

hizo

biu

m o

n th

eir

inte

ract

ion

on G

row

th a

nd Y

ield

att

ribut

es o

n B

lack

gram

(V

igna

m

ungo

L.)

Var

. S

HE

KH

AR

-2

Tre

atm

ents

Gro

wth

att

ribut

es

(65 D

AS

) Y

ield

att

ribut

es

Pla

nt

heig

ht

(cm

)

No.

of

leav

es

plan

t-1

No,

of

pod

plan

t-1

No.

of

seed

po

d-1

No.

of

nodu

les

plan

t-1

Fre

sh

wei

ght

plan

t-1 (

g)

Dry

wei

ght

plan

t-1 (

g)

Tes

t w

eigh

t pl

ant-1

(g)

See

d yi

eld

(q h

a-1)

T0

0% N

PK

+ 0

% R

35.8

0 21

.80

25.0

2 5.

70

13.0

5 12

.10

8.10

39

.20

3.50

T1

0% N

PK

+ 5

0% R

35.9

0 22

.50

25.7

3 6.

10

14.9

0 13

.90

8.60

39

.97

4.05

T2

0% N

PK

+ 1

00%

R

36.9

0 23

.90

26.2

5 6.

40

18.1

2 14

.50

9.57

41

.35

4.60

T3

50%

NP

K +

0%

R

38.7

0 25

.05

27.0

2 7.

43

19.5

0 15

.10

9.92

42

.40

5.20

T4

100%

NP

K +

0%

R

39.2

2 25

.80

27.8

0 8.

45

19.9

9 15

.98

10.1

7 42

.75

5.15

T5

50%

NP

K +

50%

R

40.4

0 27

.00

28.7

2 8.

80

20.8

0 17

.05

10.7

5 43

.60

5.35

T6

100%

NP

K +

50%

R

40.3

7 29

.00

30.0

1 9.

25

22.1

0 17

.99

10.6

7 45

.01

5.33

T7

50%

NP

K +

100

% R

39

.10

29.9

0 30

.45

9.30

22

.70

19.1

0 11

.01

45.8

5 6.

08

T8

100%

NP

K +

100

% R

41

.50

31.0

0 32

.50

10.1

0 23

.00

18.0

5 11

.90

47.0

1 6.

80

SEd

(±)

0.78

0.

56

0.53

0.

23

0.38

0.

42

0.25

0.

34

0.13

CD

(P

=0.

05)

1.66

1.

19

1.13

0.

48

0.80

0.

90

0.53

0.

72

0.28

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Condition. Int J Recent Sci Res. 7 (10), pp. 13875-13894. [7] Hussain, A., Ali, A. and Ijaz, N. R. (2012). Effect of Phosphorus With and Without Rhizobium

Inoculation on Nitrogen and Phosphorus Concentration and Uptake by Mungbean (Vigna Radiata L.). J. Agric. Res., 2012, 50 (1).

[8] Jat, S. L., Prasad, K. and Parihar, C. M. 2012.Effect of organic manuring on productivity and economics of summer mungbean. Annals Agril. Res. (New Series), 33 (1 & 2): 17-20.

[9] Kumar, J. (2008) Physico-chemical properties of the soil, under the two forest plantation stands around Varanasi (U.P.), India.

[10] Meenu (2010). Effect of zinc, molybdenum, urea and their interactions on the growth and yield of urdbean (Vigna mungo L.) Hepper.Thesis (Botany), Chaudhary Charan Singh University, Meerut, U.P. (INDIA).

[11] Patil, S. C., Jagtap, D. N. and Bhale, V. M. (2011). Effect of phosphorus and sulphur on growth and yield of moong bean. Internet J. agric.Sci., 7(2): 348-351.

[12] Saravanan, P., Singh, S. K. and Kumar, I. (2013). Effect of organic manures and chemical fertilizers on the yield and macronutrient concentrations of green gram. International Journal of Pharmaceutical Science Invention ISSN (Online): 2319 – 6718, ISSN (Print): 2319-670X.

[13] Singh R.P., Singh, Bisen, Yadav, Jay Singh, P.K., Singh, S.N., Singh, R.K. and Singh J., (2008). Integrated use of sulphur and molybdenum on growth, yield and quality of black gram (Vigna mungo L.) Legume Res., 31: 214-217.

[14] Singh, G. 2013. Effect of phosphorus application and urea spray on growth and yield of summer urdbean [(Vigna mungo (L.) Hepper] genotype.The Journal of Plant Science Research 29 (1): 125-128.

[15] Singh, R.P., Bisen, J.S., Yadav, P.K., Singh, S.N., Singh, R.K. and Singh, J. 2008. Integrated use of sulphur and molybdenum on growth, yield and quality of black gram. Legume Research 31: 214-217.

[16] Singh, R.P., S.C. Gupta and A.S. Yadav. 2008. Effect of levels and sources of phosphorus and PSB on growth and yield of black gram (Vigna mungo L.) Legume Res. 31 (2): 139-141.

[17] Takase, M., Owusu, L. K. and Sekyere, J. D. (2011) the effects of four sources of irrigation water on soil chemical and physical properties. Asian Journal of Plant Sciences; 10: 1, pp 92-96.18.

[18] Tomar, T. S., Kumar, S. and Tomar, S. 2013. Effects of plant density, nitrogen and phosphorus on black gram (Vigna mungo L. hepper). Annals Agril. Res. (New Series) 34 (4) : 374-379.

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Economics of Mustard (Brassica juncea L.) Cultivation through Integrated Nutrient Management Practices

Rama Kant Singh*1, Pankaj Kumar1, S.K. Singh1, S.B. Singh2 and R.N. Singh3

1Krishi Vigyan Kendra, Katihar2Krishi Vigyan Kendra, Gaya

3Directorate of Bihar Agricultural University, Bihar Agriculture University, Sabour, Bhagalpur


ABSTRACT

A field experiment was conducted at farmer field of Katihar district during two consecutive years of 2014-15 and 2015-16 to investigate the economics of mustard cultivation with the help of integrated nutrient management practices. The study was done in RBD with three treatments and ten replications with variety Pusa Bold to evaluate the observation regarding growth attributes and yield components of mustard. The land was prepared in early November and nutrients are applied as per treatments (T1 = farmer practices, T2 = RDF through SSP, T3 = soil test based fertilizers application and T4 = soil test based fertilizers application (75% through chemical fertilizers + 25 % through organic fertilizers), respectively. Results revealed that different fertility levels had significant effect on all growth and yield parameters i.e. number of branches, number of pods, length of plant, test weight, no of seed/pod, weight of seed, weight of straw, Biological yield, harvesting index, cast of cultivation, net return and BC Ratio. The use of soil test based fertilizers application through 75% chemical fertilizers and 25 % with organic manure resulted in significantly higher seed yield of mustard (20.93 q ha-1) followed by soil test based fertilizers application (16.90 q ha-1), nutrient application as par RDF (15.96 q ha-1) and farmers practices (13.15 q ha-1), respectively. Balance fertilization at right time with proper method and sources nutrient uses efficiency and productivity of mustard. Twenty five per cent inorganic fertilizers can be saved by use of FYM without deterioration in mustard yield.

Keywords: FYM, Nutrient Use Efficiency, Fertilizers, Mustard, Seed Yield, Net Return

INTRODUCTION

The oilseed form essential part of human diet. Besides it produces basic raw materials for agro-based industries and has large acreage covering 20.7 million ha under various oilseeds in different agro-climatic zones of this country. The average Indian consumer uses relatively low quantities of edible oil, no doubt influenced by his modest level of income. The annual per capita “disappearance” of oils and fats in 1999 was as high as 82.3 kg in Malaysia, 47 kg in USA, 45.8 in EU-15, 17.3 kg average for the world as a whole and 11.9 kg in China as against 9.9 kg in India. This has been primarily due to phenomenal increase in human population and lower rate of productivity of these crops. Rapeseed and mustard are the major Rabi oilseed crops of India and stand next to groundnut in the oilseed economy. Rapeseed and mustard are one of the most important edible oils of northern and eastern parts of India. Various nutrients and

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micronutrients are required for oilseed production, but the nutrient which plays a multiple role in providing nutrition to oilseed crops, particularly those belonging to cruciferae family. Each unit of fertilizer sulphur generates 3-5 units of edible oil, a commodity needed by every family. Sulphur can be rightly called as fourth major element of the plant because it is a constituent of three amino acids and helps in the formation of chlorophyll and synthesis of oils. Sulphur application also has marked effect on soil properties and is used as soil amendment to improve the availability of other nutrients in soil as gypsum and pyrite. Sulphur is the cheapest of the four major plant nutrients today. Between the two common sources of sulfur, a relatively large deposit of gypsum are available in India and is a cheap source of sulfur, hence could also be a better source of sulfur for oilseed crops. Khan and Hussain (1999) showed the highest seed and oil yield in mustard (Brassica juncea) cv. Pusa Bold was obtained by applying 20 kg sulfur per hectare. Organic manures are known to play a number of vital roles in soil fertility, crop productivity and production in agriculture as they are eco-friendly and can replace 25 percent chemical fertilizers that are able to get maximum crop yields. They supplement chemical fertilizers for meeting the integrated nutrient demand of the crops. The inoculants of organic manure in soil plants, promote seed germination and initial vigor of plants by producing growth promoting substances. Application of organic manure results in increased mineral and water holding capacity and uptake, root development, vegetative growth, and nitrogen fixation. Therefore, the present study deals with the Effect of Integrated Nutrient Management on soil properties and Performance of Mustard (Brassica juncea L.).


The experiment was conducted at Farmers field of Katihar district by Krishi Vigyan Kendra, Katihar, (Bihar Agricultural University Sabour, Bhagalpur) during two consecutive years of 2013-14 and 2014-15 to study the Effect of Integrated Nutrient Management on Soil Properties and Performance of Mustard (Brassica juncea L). It lies between Latitude 25’N to 26’N, Longitude 87’ to 88’E with an altitude of 32 m above MSL. The climate is sub-tropical and humid having to mean maximum and minimum temperature between 440C and 40C, respectively and the average annual rainfall of the district is about 1200 mm.

experimentAl Site And Soil AnAlySiS

The experimental soils are non-calcareous light gray flood plain belongs to the Alluvial Tract (Agro ecological zone-II) lies between three major rivers Mahananda, Kosi, and Ganga. The soil samples were collected from different farmer field before starting the experiment and after harvesting of the crop and at each sampling site, soil samples were collected from top soil and finding are presented in table 1. The soil texture varies from sandy loam to sandy clay with noncalcareous light gray flood plain belong to the alluvial tract. In October 2013 and April 2014 and October 2014 and April 2015, surface soil samples were collected with the help of Sugar with the experimental field. At each sampling point, four cores (5.0 cm diameter) were randomly taken within one meter at each other to a depth of 15 cm. About 500 g composite soil samples were obtained after combining at each point. A total of 75 % composite soil samples were air dried and pass through 2mm sieve. Organic carbon content was determined by the Walkley and Black method (1934). Available nitrogen was determined by the alkaline KMNO4 method (Subbaiah and Asija, 1956), and available phosphorous (Olsen’s method, 1954) and available potash were determined Flamphotometrically method (Tandon, 1993),

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available sulfur was determined turbidimetry method (Hunter, 1984). The pH and EC were measured in soil suspension (1:2.5) using electrode (Chopra and Kanwar, 1991).

Table 1: Effect of Different Treatment on growth Attributes of Mustard

Treatments Plant Height (cm)

Branches Plant-1

SiliquaePlant-1

Siliquae Length (cm)

Test Weight(gm)

Seeds Siliquae-1

T1 119 11.72 169 3.57 4.98 6

T2 124 12.02 170 3.77 5.02 7

T3 133 12.11 178 4.07 5.04 7

T4 156 12.32 187 4.37 5.11 8

Mean 132.25 12.04 176 3.95 5.04 7

CD(p=0.05) 3.53 0.06 2.06 0.04 0.02 0.02

experimentAl treAtmentS And deSign

The experiment was laid out in RBD with four treatments and ten replications. There were altogether 40 unit plots in the experiment. The unit plot size was 4.0m × 2.5m. The land was prepared in early November and nutrients are applied as per treatments (T1 = farmer practices (urea 25 kg, 50 kg DAP, 25 kg MOP), T2 = RDF through SSP, T3 = soil test based fertilizers application and T4 = soil test based fertilizers application (75 % through chemical fertilizers + 25 % through organic fertilizers) respectively. All the fertilizers were applied as per treatments dose in each individual plot during the final land preparation and rest nitrogenous fertilizer was applied as per different stages recommended in different treatments. Mustard Seed var Pusa Bold in were sown on 18th November 2013 and 24th November 2014 at the rate of 5 kg ha

-1 after application of treatments wise manure and fertilizers with 30 cm row spacing of to

evaluate the observation regarding growth attributes and yield components. Three irrigations were applied during crop season at branching stage 30 DAS, flowering stage 50 DAS and pod filling stage 85 DAS. The crop was harvested on 30 March 2014 and 8 April 2015. The experimental data recorded for growth parameters, yield attributes and yield was statistically analyzed by Fisher’s ‘Analysis of Variance’ technique (Fisher, 1950).


plAnt height

Results showed that plant height was significantly affected by different combined (table 1). The highest plant height 155 cm was obtained by treatment T4 (soil test based fertilizers application (75 % through chemical fertilizers + 25 % through organic fertilizers), followed by T1 (farmer practices), T2 (RDF through SSP) and T3 (soil test based fertilizers application). Comparing with farmer practice, plant height increased 4.84, 10.61 and 23.87 % by utilization of T2, T3, and T4, respectively. The reason for better growth and development in the above treatments might be due to increased availability of nitrogen and phosphorus to the plant initially through fertilizers and then through manures in the cropping season. FYM plays an important role in the better development of roots and increased microbial activity because of balanced nutritional

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environment probably both in soil rhizosphere and plant system results in better growth and development of the mustard crop. These results are in agreement with those of Singh (2007) who observed higher values of growth parameters due to the application of fertilizers and manures in combination.

numBer of SecondAry BrAncheS/ plAnt

The two years pooled data related to branch per plant have been presented in table 1. It is clear from the data recorded that the effect of different treatments was significant on a number of branches/plant and found more number of secondary branches per plant in T4 (12.32) than other treatments 12.11, 12.02 and 11.72 in T3, T2, and T1, respectively. Application of 75 % inorganic and 25 % organic fertilizers after soil test value might have increased the availability of nitrogen to the plant at early growth stages and nitrogen being an essential constituent of nucleic acid, protoplasm, and protein, play a fundamental role in metabolism, growth, development, reproduction and transmission of heritable characters, so the number of secondary branches also increased by this condition. These results were in conformity with those of Prasad and Ehsanullah (1988).

numBer of SiliQuA plAnt-1

The pooled data in table 1 showed all the treatments were significantly superior to farmers’ practice in respect to a number of siliqua plant-1. Addition of 25 % organic fertilizers with 75 % chemical fertilizers levels gave significantly higher value (187) than other treatment combinations169, 170, 178 in T1, T2 and T3, respectively. During both year, the results followed the same trend was also significantly had a higher number of siliqua over control.

numBer of SeedS SiliQuA-1

As pooled data shown in table 1 the number of seeds siliqua-1 varied from 6 to 8 and lowest and highest value given by (T1) farmer practice and (T4) soil test based fertilizers application (75 % through chemical fertilizers + 25 % through organic fertilizers gave. Addition of 25% organic fertilizers in a combination of 75 % chemical fertilizers gave higher values than other treatment combination but the differences were nonsignificant. A number of investigators have observed increases in these attributes in mustard crop viz. Tripathi et al. (2011), Chaurasia et al. (2009), Ramesh et al. (2009) and Kashved et al. (2010). The results of the present study are in agreement with the findings of the above workers.

grAin yield

The average seed yield had a significant effect on fertilizer management levels at crop harvest. The yield increased progressively and significantly with each successive treatment application. In the T4 level, the pooled seed yield was 20.93 as against 13.15, 15.96 and 16.90 q ha-1 recorded in T1, T2, and T3 levels, respectively. Thus, the difference in yield resulting from soil test based fertilizers application (75 % through chemical fertilizers + 25 % through organic fertilizers application was significant. The results are summarized in Table 2. A similar result has been reported by Kumar and Kumar (1994). The interaction between 75 % chemical fertilizers and 25 % organic fertilizers on grain yield was significant.

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Table 2: Effect of Different Treatment on Yield Attributes

Treatments Seed Yield(qt ha-1)

Straw Yield(qt ha-1)

Biological Yield(qt ha-1)

HarvestingIndex

T1 13.15 15.22 28.37 46.36

T2 15.96 17.56 33.52 47.61

T3 16.90 18.25 35.15 48.08

T4 20.93 21.32 42.25 49.54

Mean 16.74 18.09 34.82 47.90

CD(p=0.05) 1.42 1.86 2.05 ND

StrAW yield

The effect of different treatments was significant in forage yield. Application of 75% through chemical fertilizers + 25 % through organic fertilizers after soil test value recorded significantly higher straw yield than an only chemical application on the basis of the recommended dose of fertilizers and other treatments, which in turn gave significantly higher straw yield than other application of fertilizes of treatments. The increase in straw yield also may be attributed to higher plant height than more number of total branches. A similar result was also reported by Sharma (1994), Prassad (1995), Malavia et al. (1988) and Sharma (1992). This may be due to the effect of organic and inorganic fertilizers combination to increasing growth attributes and production of more dry matter. Sharma (1994) and Jat et al. (2003) also reported an increase in forage yield of mustard with increasing sulfur levels.

BiologicAl yield

The results related to biological yield showed significant differences between different treatment combinations (table 2). The results indicated that the highest biological yield was obtained when applied 75 % through chemical fertilizers and 25 % through organic fertilizers fertilizer (T4). Biological yield increased 32.85, 19.29, and 15.36 % by T4, T3, and T2 in comparing with control (T1), respectively. Such effects of different treatments might be due to the play of critical role in crop growth, involving in photosynthesis processes, respiration and other biochemical and physiological activates and thus their importance in achieving higher yields (Tripathi et al., 2010).

hArveSt index

These results show that the application organic and inorganic fertilizers after soil test value significantly increased harvest index (Table 2). On an average, application of different treatment increased harvest index by 6.86, 3.71, and 2.70 percent over the farmer practice. Whereas, T4 treatment produced maximum grain and biological yield, so increase harvest index in its treatment is absolute. The increase in the studied characters due to micronutrients may be attributed to its influences in enhancing the photosynthesis process and translocation of photosynthetic products to the seed as a result of increase enzymatic activity and other biological activities. The present trend of increase in harvesting index is in close conformity with the findings of Abraham et al. (2008) and Maheshbabu et al. (2008).

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coSt of cultivAtion

The data related to the cost of cultivation have been presented in table 3 fig. 1. It is clear from the above data that the cost of cultivation of mustard varied from Rs. 11920 to Rs. 12408 per ha. The maximum cost of cultivation was observed with treatment T4 and minimum with T1. It is possible due to the application of organic and inorganic fertilizers in combination due to that labor cast gone up but the increase the physicochemical properties of soil and availability of balance nutrients the total production increased over to control.

Fig. 1: Impat of INM on Eonomics of Mustard

groSS income

It is clear from the data presented in table 3 and fig. 1 that the gross income of mustard crop varied from Rs. 34194 to Rs. 43509 per ha. The maximum gross return was found Rs. 54415 with treatment T4 (soil test based fertilizers application (75% through chemical fertilizers + 25 % through organic fertilizers) and minimum Rs. 34194 with T1 (farmer practice). It is clear with our findings the maximum return with T4 might be due to the highest yield of biological yield per ha. It is possible due to the application of organic and inorganic fertilizer due to that the availability of nutrients is in increased and total production was also increased so that the gross return was increased.

Table 3: Effect of Different Treatment on Economics

Treatments Cost of Cultivation (Rs.)

Gross Return (Rs.)

Net Return (Rs.)

BC Ratio

T1 11920 34194.46 22274.46 2.87

T2 12150 41487.38 29337.38 3.41

T3 12305 43939.34 31634.34 3.57

T4 12408 54415.68 42007.68 4.39

Mean 12195.75 43509.22 31313.47 3.56

CD(p=0.05) 135.22 205.02 158.74 ND

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net income

It was observed from data (table 3 and fig. 1) that net income with the application of a combination of organic (25 %) and inorganic (75 %) varied from Rs. 22274 to Rs. 42007 per ha. Net income (Rs. 42007) was found maximum with the treatment T4 and minimum (Rs. 22274) with the treatment T1. Minimum income may be due to more expenditure and low biological yield.

Bc rAtio

The Benefit-Cost Ratio (BC ratio) is defined as the amount received against the profit gained on investment/ costs of one rupee. The BC ratio was computed by borrowing the methods that employed by Ramesh et al. (2009).

BC R = Nr/TC

Nr = Stands for net returns

TC = Denotes total cost

It was found from data (Table 3) that B C ratio varied from 2.87 to 4.39. It was found maximum with the treatment T4 and minimum B C ratio with treatment T1.

ACKNOWLEDGMENTS

The authors greatly appreciate the research facilities and financial support provided by Indian Council of Agricultural Research, New Delhi and BAU, Sabour, Bhagalpur and all those who cooperate and support to complete these work along with farmers.

REFERENCES[1] Abraham, T., Thenua, O.V.S., Singh, S.P. and Jacob, P. 2008. Performance of groundnut as influenced by

organic and inorganic sources of nutrients and their method of application. Legume Res. 31: 224-26.[2] Chauhan, D.R., Shasi-Paroda, Mangat Ram, Paroda, S. and Ram, M. 1996. Response of Indian mustard

(Brassica juncea L.) to biofertilizers, sulphur and nitrogen fertilization. Indian J. Agron. 41(4): 620-623.[3] Chaurasia, Anand, Singh A.B. and Namdeo, K.N. 2009. Integrated nutrient management in relation to yield

and yield attributes and oil yield of Ethiopian mustard (Brassica carinata).Crop Reearch. (Hisar). 38 (1/3): 24-28.

[4] Chopra, C.L. and Kanwar, J.S. 1991. Analytical Agricultural Chemistry, Kalyani Publication, New Delhi.[5] Fisher, R.A. 1950. Statistical Methods for Research Workers. Oliver and Boyd, Edinburg, London. pp. 57-63.[6] Gomez, K.A., Gomez A.A. 1984. Statistical procedures for agricultural research. International Rice Research

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in loamy sand soil. J. Farming Syst. Res. Dev., 8(1):108-109.[10] Kashved, S.M., Raskar, B.S. and Tamboli, B.D. 2010. Effect of integrated nitrogen management and irrigation

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[11] Khan, N. and Hussain, K. 1999. Performance of mustard varieties in relation to doses of sulphur. Adv.Plant Sci. 12(1): 115-118.

[12] Kumar, V. and Kumar, V. 1994. Effect of Azotobacter chroococum on Indian mustard grown in different soil environments. Crop Res., Hisar. 7(3): 446-450.

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[16] Prassad, J. 1995. Studies on sulphur use efficiency of mustard (B. juncea) as influenced by rate of gypsum application and levels of irrigation. M.Sc. (Ag) Thesis, RAU, Bikaner(Raj.).

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[23] Singh, B., Kumar, A., Yadav, Y.P. and Dhankhar, R.S. 2000. Response of Brassica to sulphur application. Indian J. Agron., 45(4): 752-755.

[24] Subbaiah, B.V. and Asija, G.L. 1956. A rapid method for the estimation of available nitrogenin soil. Curr. Sci., 25:259-260.

[25] Tandon, H.L.S. 1993. Methods of analysis of soil, plants, waters and fertilizers. Fertilizers Development and consultation organization, New Delhi.

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[27] Tripathi, M.K., Chaturvedi, S., Shukla, D.K. and Mahapatra B.S. 2010. Yield performance and quality in Indian mustard (Brassica juncea) as affected by integrated nutrient management. Indian Journal of Agronomy, 55 (2): 138-142.

[28] Walkley, A. and Black, I.A. 1934. An examination of the degtjareff method for determining soil organic matter and a proposed modification of the eronic acid titration methods. Oil Sci. 37:29-38.

[29] Yusuf, M. 1973. Effect of frequencies and timings of irrigation on growth, yield and quality of safflower, mustard and linseed.Ph.D. thesis, Division of Agronomy, Indian Agricultural Research institute, New Delhi.

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Economic Impact of Free-Ranging Wildlife on Major Agricultural Crops in Eastern Uttar Pradesh, India

Ramchandra*1 and Tarence Thomas2

1Department of Agricultural Economics, Sam Higginbottom University of Agriculture,

Technology and Sciences, Allahabad, Uttar Pradesh, India–211007

2Department of Soil Science, Sam Higginbottom University of Agriculture,

Technology and Sciences, Allahabad, Uttar Pradesh, India–211007


ABSTRACT

The problem associate not only in India, also in other countries, with locally over plentiful wildlife species have emerged as important management issues for reason of some species losing their natural habitat but adapting themselves to the man altered habitats. With the result that a conflict with the interests of local people. Crop assailing by locally over enormous wild populations of nilgai (Antilope cervicapra) in Uttar Pradesh, India is one of the serious problems analyzed in this article. Nilgai (Antilope cervicapra) causes comprehensive spoil to agricultural crops; especially pulses namely: pigeon pea(Cajanus cajan), gram(Cicer arietinum), pea(Pisum sativum), black gram (Phaseolus mungo), green gram (Phaseolus aurious)and cereals crops e.g. wheat (Triticum aestivum), barley (Hordeum vulgare), maize (Zea mays), jowar (Sorghum spp.), bajara (Pennisetum typhoides), paddy (Oryza sativa) seedlings and oil crops e.g. mustard (Brassica juncea), seasmum (Sesamum Indicum), lentil (Linum usitatissimum), sunflower (Helianthus annus). Nilgai gnaw mainly on tender shoots of different pulses,cereals, and oil seeds crops. The damage is much more at multi-stages of these crops, therefore; the intensive possible management strategies such as culling, fencing in nilgai and fencing of agricultural areas to minimize the problems are suggested. Chain-link fencing of a sizable Reserved Forest (RF) patch, where the animals seek daytime shelter, combined with other local protective methods in the cultivated areas of Allahabad hold the promise of reducing the pest animal populations. The experiment is likely to establish one approach for dealing with the specific problem in Uttar Pradesh, India. This paper discusses agricultural crop assailing by locally over abundant populations of nilgai (Boselaphus tragocamelus) and nilgai (Antilope cervicapra) in several districts of Uttar Pradesh and the possible management strategies that can limit or reduce the conflict. Based on these strategies, a management experiment is being conducted in four districts of Uttar Pradesh in India namely, Allahabad, Pratap Garh, Kaushambi and Fatehpur. The outcome of the study is deliberated in this manuscript. The crops damaged primary data was collected from the cultivars though personal interview and based on keeping their memory. The data was collected through a bench mark survey on pre-tested schedule during the agricultural year-2016-17.

Keywords: Nilgai; Boselaphus Tragocamelus; Population; Ranging; Wildlife; Agricultural; Crops; Pulses; Cereals

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ISBN: 978-93-88237-24-6

INTRODUCTION

Nilgai antelope (Boselaphus tragocamelus), was first appeared in 1417. The word nilgai is derived from the old French name antelope, from Medieval Latin ant(h)alopus, which is associated with Byzantine Greek word anthólops, first attested in Eustathius of Antioch (circa 336). It was a fabulous animal haunting on the banks of the Euphrates. The nilgai apparently brought from the United States to India as zoo animals before the mid-1920s and released in South Texas in 1930. In Hindi, nilgai is called nilgaw in India. A blue bull is called a nilgai or nilgaw in India, from nil meaning blue and gai meaning a bovine animal (literally ‘cow’). Nilgai terror occurs from the Kanya Kumari foothills of the Himalayan Mountains southward to Jammu & Kashmir. Nilgai antelope is found throughout most part of India. The nilgai (Boselaphus tragocamelus) is one of the most commonly seen wild animals in all over India, often seen in farmland or scrub forest. The mature male appears ox-likeand is known as the blue bull. The base of the Himalayas in the north, down to the state of Karnataka in the south, being absent only in eastern Bengal, Assam, the Malabar Coast, and regions close to the Bay of Bengal. They inhabit the Gir forest and across Rajasthan in the west to the states of Assam and West Bengal in the east. It is also present in parts of southern Nepal and eastern Pakistan. Due to extreme deforestation, nilgai is moving around our cultivated fields and damaging our crops in several states of north zone. Nilgai terror is most effective in several states especially Uttar Pradesh, Uttar Khand, Madhya Pradesh, Chhatis Garh, Bihar, Jharkhand, West Bengal, Maharashtra, Orissa etc. The average crop losses occur about 25-60 percent.

INTER-SPECIFIC RELATIONSHIP

Nilgai can be seen with a black buck in the open plains, and in the lower regions of predators of nilgai include tigers and leopards, although the latter is only capable of capturing calves, and not fully-grown adults. Like many Indian animals, nilgai is often victim to vehicular accidents, and their carcases are often seen on major highways in northern India. The main threat to this species is the loss of habitat due to human population growth. However, nilgai is the crop menace, causing large-scale damages, especially along the Gangetic belt, in the Allahabad, Pratap Garh, Kaushambi and Fatehpur districts of Uttar Pradesh, India. They have been declared as vermin in northern India. They may be legally hunted after obtaining a permit. Nevertheless, the local belief that nilgai is cattle and hence sacred, has protected them against hunting.

CENSUS ON WILDLIFE OF VARIOUS ANIMALS

The All India Estimation of Tiger, co-predators and its prey was carried out during 2015-16 in the tiger range states of the country using a modified and refined methodology. The details are given in Table-1. It is estimated that the population of Nilgai (Boselaphus tragocamelus L.) could exceed 200,000 in Uttar Pradesh, which is very low in Pakistan about 37,000 only Rahmani (2001).

IMPACT OF FREE-RANGING WILD LIFE ON CROPS

Nilgai (Boselaphus tragocamelus L.) is a highly adaptive antelope. Naturally diurnal, it goes for crop assailing at the start of sunset in evenings to at night. It is found to damage all most

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Economic Impact of Free-Ranging Wildlife on Major Agricultural Crops in Eastern Uttar Pradesh, India 179

ISBN: 978-93-88237-24-6

agricultural crops to a considerable extent. The approximations have made according to villagers, the damage is up to 70 to 80% of the total yield. The nilgai found either grazing tenders of the crops or resting on them. The damage of crops especially wheat (Triticum aestivum), barley (Hordeum vulgare), Jowar (Sorghum spp), bajra (Pennisetum glaucum), moong (Pharsalus mungo), bean (Phaseolus vulgaris), mustard (Brassica campestris) and Maize (Zea mays) etc. were recorded. Nilgai found to be capable of causing extensive damage to most agricultural crops. Damage of crops was caused not only by foraging but also through trampling, resting in a field and daily movement of the animals. In low-density nilgai areas, losses to wheat(Triticum aestivum), gram and green gram (Phaseolus mungo) crops were 45-50%, 60-65% and 40-45%, respectively. On an average damage to black gram (Vigna radiata) and pigeon pea (Cajanus cajan) was 20-35% and 40- 55 percent, respectively. Whereas in high-density nilgai areas, damage to wheat, gram, and green gram was 35-60%, 50-70% and 45-60%, respectively (Chauhan, 2011).

The impact of crops due to nilgai in four districts of Uttar Pradesh namely; Allahabad, Kaushambi, Pratap Garh and Fatehpur are depicted in the table -2. In Allahabad district Uttar Pradesh, nilgai caused severe damage to pulse crops which was recorded as pigeon pea (Cajanus cajan) was 70 percent followed by green gram 68 percent, black gram 61 per centerfield pea 58 percent, gram50 percent, and lentil 38 percent whereas, the vegetable crop like, potato (Solanum tuberosum) was damaged 59 percent followed by tomato 48 percent, cauliflower 45 percent, brinjal 42 percent, capsicum 40 percent, and lady’s finger 38 percent. Damage to wheat crop was the highest 32 percent in cereals followed by barley 25 percent, paddy 22 percent, bajra 17 percent, jowar 15 percent, and maize 11 percent. Damage to oil crops, mustard 55 percent was highest followed by linseed 50 percent, sesamum 46 percent safflower 45 percent and sunflower 42 percent.

In Uttar Pradesh district Kaushambi, nilgai caused maximum damage to paddy crop 26 percent, followed by wheat 20 percent, maize 18 percent, bajra 13 percent, and jowar 12 percent. Damaged to oil crops mustard 68 percent was highest followed by sesamum 61 percent, linseed 43 percent, sunflower 33 percent, and groundnut 19 percent and safflower 12 percent.

In district Pratap Garh of Uttar Pradesh, damage to pulse crops pigeon pea 56 percent was highest followed by gram 38 percent, pea 35 percent, green 22 percent, and black gram 20 percent. Whereas damage to vegetable crops potato 45 percent was highest followed by brinjal 38 percent, cauliflower 32 percent, tomato 30 percent, lady’s finger 28 percent and capsicum 11 percent (Ramchandra, 2015).

The cultivars are facing same problems in district Fatehpur of Uttar Pradesh. Nilgai caused severe damaged to most of the cereals, pulses and vegetable crops. The wheat crop was damaged 21 percent highest in cereal crops followed by paddy 18 percent, maize 16 percent, jowar 13 percent, and bajra 11 percent. Damage to oil crops, mustard 31 percent was highest and linseed was 8 percent. Nilgai damaged to pulse crops; pigeon pea (Cajanus cajan) was 49 percent highest followed by gram 46 percent, pea 27 percent and black gram 15 percent, whereas the vegetable crops; potato (Solanum tuberosum) was damaged 37 percent followed by tomato 36 percent, brinjal 35 percent, cauliflower 28 percent, and lady’s finger 325 percent. Therefore, most of the cultivars stop pulses production in these districts.

It is illustrated in table-4; the total population of nilgai was recorded more than 200000 in Uttar Pradesh during the year 2015-16. Therefore, it is accepted that after five-year nilgai population

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ISBN: 978-93-88237-24-6

will increase, more than two-fold, which accounted as the highest population among all the state in India. Since the population, nilgai is increasing rapidly at the rate of 15-20 percent per year in Uttar Pradesh, India (Ramchandra15).

dAmAge protection meASureS

crop protection through Agri-Silvi prActiceS

Some rural people arranged crop protection strategies in nilgai affected areas, effective crop protection plan is very necessary. Various form of fencing is little used to protect the crop under large scale. Some cultivars are generally adopting agroforestry systems to protect the crops as well as enhance the income. Poplar and brushwood fence is used in some places as effective measures against crop damaged by cattle only but it rarely restricts nilgai. Most of the cultivars practiced common protection strategy for farmers is to guard their fields by remaining vigilant during the crop season.

limitAtion in dAmAge control

Nilgai is an animal of considerable religious reverence. Most of the cultivars in the affected area appose to kill because most of the Hindu community believed that nilgai belongs to cow category, therefore they do not want to hunt or kill them. The study area of districts are Hindu dominated communities, therefore, they all are strongly against any proposal for killing, culling of nilgai or capturing them with physical force. However, in spite of all this, most farmers now seem to have reached their tolerance threshold. In case of nilgai, nationally it is an endangered species.

mAnAgement StrAtegieS

It is necessary to have sufficient information on the population and eco-behavioral aspects of problem animals to plan any strategy to mitigate the crop damage problem, the particulars of agricultural lands, their distribution, crops, and the impact on local economy. This information was gathered in a rapid survey of a few problem areas. (Chauhan and Sawarkar, 1989).

Discriminatory reduction of nilgai populations would usually be the logical control strategy. Although hunting of these animals is legally banned but realizing the seriousness of the damage problem, this statewide ban needs to be reviewed. Areas most seriously affected by the problem where such trials would be locally acceptable are required to be identified and then culling of the animals may be carried out either by experts from wildlife staffs or hunters hired by the forest department.

impriSon in corrAlS

To segregate sizable populations of nilgai, the need for enclosing the animals in certainly selected forest patches identified as their known habitats is proposed. Further experiments with chemical contraception of the fenced animals in order to reduce reproduction rate and ultimately their numbers are required. Though in problem areas of different states of India not much of forestland is available, it will hardly be possible to fence in the present nilgai populations on a sustainable basis. However, experimental trials to fence in these animals

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in the refuge areas at high densities and provide them with a feed from outside need to be tried. For driving the animals into fenced areas, the law of diminishing returns will strongly operate with each repeat operation. Erection of fence and enclosing nilgai inside will need to be a protracted process, beginning with fixing fence posts along the perimeter with least disturbance to the animals while they use the area as a daytime refuge, enabling the animals to get used to the sight and sounds of humans. Erection of the fence should gradually progress around the key use areas, attempting to enclose a high percentage of the site population. Concurrently, food must continue to be added as a lure. The closing of the fence is critical and should be done when the animals remain least active. A chain-link fence with at least 3-m height will be ideal. After confining nilgai and nilgai inside the fence, the animals will have to be allowed time to adjust their numbers and resources inside the fence. Mortality due to stress is to be expected. The situation inside the fence and status of outside populations should be monitored. Simultaneously, experiments on the suppression of the breeding activity of the fenced animals essentially need to be tried.

fencing AgriculturAl AreAS

The cost of providing protection to crops by barriers such as bio-fence, trenches, barbed wire, and chain-link fences is prohibitive. However, power fencing, which would be cheapest and effective, can be tried. Although it may be possible to protect certain valuable crops in this way, such measures may transfer the problems to other unfenced crop areas. Furthermore, the area has considerable domestic stock and it may not be easy to exclude the wild while allowing domestic grassers.

GLOBAL ECONOMIC IMPACT AT GLANCE

The impact losses of agricultural crops damaged by nilgai in following counties are given as bellow:

U.S.A: An Annual estimate of damage to agricultural producers around the US $ 4.8 billion in the USA

EUROPE: In France (2015) damage to crops by nilgai, boar and deer amounted to € 27 million in Slovenia compensation for damage by a large predator in the year -2012-13 exceeded € 710,000.

AUSTRALIA: Production losses in 2016-17 were estimated to be the US $ 24 million/year for South Australia alone. Losses to wool industry estimated at the US $ 115 million/year. Kangaroos cause huge damage to crops and compete for forage with sheep. Approx. 11 million kangaroos eliminated each year.

CHINA: Rural inhabitants of the mountain area of Simao near the Xishuang Banner. Nature Reserve claimed that the elephant’s damage reduced the community’s annual income in 2015-16 by 28 to 48 percent and the total economic losses between 2014-15 amounted to the US $ 318,600 (Zang and Wang 2015).

AFRICA: Crop damage is the most prevalent form of human-wildlife conflict across the African continent. In some semi-arid rural farming areas of Zimbabwe and Kenya, elephant damage to food crops accounts for 75 to 90 percent of all damage caused by large mammals. (Hoare and Mackie, 1993).

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INDIA: Almost entire country affected by major animal species involved is Blue Bull, Black Buck, Leopard, Snow Leopard, Tiger, Wolf, Elephant, Wild Ass, Sloth Bear, Brown Bear, Rhesus and Bonnet Macaques, and Wild Pig.

Table 1: Population of Nilgai (Boselaphus tragocamelus) and other wildlife in the year 2015-16

Local, English and Scientific Name Inside PAs Outside PAs

Tiger (Pantheratigris) 32 0

Leopard or Panther (Pantherapardus) 337 103

Sloth Bear (Melursusursinus ) 514 148

Indian wolf (Canis lupus pallipes) 356 1236

Civets (Viverridae spp.) 407 641

Antelope (Tetracerosquadricomis) 145 71

Chital (Axix axis) 1513 15344

Indian Gazelle (Gazella gazelle bennetti) 5274 33711

Hyena (Hyena hyena) 1174 1330

Jungle cat (Felischaus) 2217 993

Wild pig (Sus scrofa) 9830 1433

Black Buck (Antelope cervicapra) 1751 12950

Hares (Common Indian, Desert) 2259 9516

Langur(Presbytis entellus) 27192 9055

Desert Fox (Vulpesbucapus) 1153 5255

Mongooses (Herpestes) 2767 4434

Nilgai(Boselaphus tragocamelus) 20974 41434

Sambar (Cervus unicolor) 14090 616

Indian porcupine (Hystrixindica) 1146 1423

Geedar Jackal (Canis aureus) 5888 13810

Caracal (Felis caracal) 37 125

Table 2: Crops damaged by nilgai (Boselaphus tragocamelus) in different districts of Uttar Pradesh, India in the year-2014-15

Particulars District wise crops damaged (%)

Cereal Crops Allahabad Kaushambi Pratap Garh Fatehpur

Wheat 32 20 28 21

Barley 25 - 9 -

Jowar 15 12 10 13

Bajra 17 13 15 11

Maize 11 18 13 16

Paddy 22 26 23 18

Pulse Crops

Pigeon pea 70 56 53 49

Table 2 (Contd.)...

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Pea 58 35 42 27

Gram 50 38 45 46

Green Gram 68 22 23 17

Black Gram 61 20 14 15

Lentil 38 - - -

Oil Crops

Mustard 60 68 51 31

Linseed 55 43 20 8

Safflower 45-50 12 - -

Sunflower 42-44 33 - -

Seas mum 46-53 61 - -

Groundnut - 19 -

Vegetable Crops

Tomato 50 30 40 36

Cauliflower 45 32 26 28

Brinjal 42 38 37 35

Capsicum 40 11 - -

Okra 38 28 - 25

Potato 49 52 48 37

Table 3: Free-Ranging Wildlife Population (Km2) in a different state during the year-2005-08

State Nilgai Tiger Leopard Sloth Beer

Chital Pig Sambhar

Uttarakhand 422 1901 3683 853 2161 3214 2756

Uttar Pradesh 8375 2766 2936 3130 5537 7761 2641

Bihar 494 510 - 532 576 570 321

Andhra Pradesh 2652 14126 37609 54673 37814 58336 33159

Chhattisgarh 9250 3609 14939 20951 18540 25058 7604

Madhya Pradesh 4170 15614 34736 40959 41509 59903 33551

Maharashtra 4754 4273 4982 6557 5970 7370 5730

Orissa 711 9144 25516 43236 6040 21525 6112

Rajasthan - 356 - - - - -

Jharkhand 1230 1488 131 2640 721 6226 721

Karnataka 20749 42349 21999 43412

Kerala 6168 836 6904 2931 8809 10469

Tamil Nadu 2608 9211 14484 13224 13567 19768 15909

Assam 1164 380 - 2047 720

Arunachal Pradesh

1685 670 199-

412 353

West Bengal 2410 - - - - 491 309

...Table 2 (Contd.)

Table 3 (Contd.)...

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State Nilgai Tiger Leopard Sloth Beer

Chital Pig Sambhar

Gujarat - - - - - - -

Punjab 1212 - - - - - -

J& Kashmir - - - - - - -

Himachal Pradesh

- -- - -

- -

Tripura - - - - - - -

Meghalaya - - - - - - -

Manipur - - - - - - -

Nagaland - 4230 5629 2037 1058 4439 2632

Goa - - - - - - -

Mizoram - 785 2324 776 - 1489 1700

Sikkim - - - - - - -

Telangana

Source: Rajya Sabha Census on Wildlife of Various Animals

Table 4: State-wise total Nilgai Population during the year 2012-13

Sl. No States Population

1. Uttar Pradesh 254449

2. Maharashtra 2345

3. Bihar 5643

4. West Bengal -

5. Andhra Pradesh 23453

6. Tamil Nadu 4552

7. Madhya Pradesh 60667

8. Rajasthan 41434

9. Karnataka 6741

10. Gujarat 97004

11. Orissa -

12. Kerala -

13. Jharkhand 7428

14. Assam -

15. Punjab 10312

16. Uttar Pradesh 38774

17. Chhattisgarh 3689

18. Jammu and Kashmir -

19. Uttarakhand 14645

20. Himachal Pradesh -

21. Haryana 38774

...Table 3 (Contd.)

Table 4 (Contd.)...

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Sl. No States Population

22. Tripura -

23. Meghalaya -

24. Manipur -

25. Nagaland -

26. Goa -

27. Arunachal Pradesh -

28. Mizoram -

29. Sikkim -

30. Telangana -

Source: Internet

Table 5: Statewide agricultural crop losses by Nilgai during the year 2013-14

Sl. No States Crop Losses (%)

1. Uttar Pradesh 55-60

2. Maharashtra 23-25

3. Bihar 20-30

4. Pashchim Bengal 18-21

5. Andhra Pradesh 30-35

6. Tamil Nadu 22-26

7. Madhya Pradesh 35-40

8. Rajasthan 18-22

9. Karnataka 30-35

10. Gujarat 25-30

11. Orissa 12-14

12. Kerala -

13. Jharkhand 30-40

14. Assam -

15. Punjab 32-38

16. Uttar Pradesh 35-40

17. Chhattisgarh 34-36

18. Jammu and Kashmir -

19. Uttarakhand 23-27

20. Himachal Pradesh -

21. Tripura 20-27

22. Meghalaya -

...Table 4 (Contd.)

Table 5 (Contd.)...

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Sl. No States Crop Losses (%)

23. Manipur 18-26

24. Nagaland -

25. Goa -

26. Arunachal Pradesh 20-30

27. Mizoram -

28. Sikkim -

29. Telangana -

Average 25-32

Source: Internet

REFERENCES

[1] Chauhan, N.P.S. and Singh, Ramveer (1990)-crop damage by overabundant populations of nilgai and nilgai in Uttar Pradesh (India) and its management. In proceedings of the fourteenth vertebrate pest conference University of Nebraska - Lincoln.

[2] Clatworthy J N (1989)–A review of rangeland utilization trials in Zimbabwe, 1979 to 1985. In Rangeland potential in the SADCC Region (A.R. Maclaurin and B.V. Maasdorp, eds). Proc. Regional Workshop, 1-5 June 1987, Bulawayo Ministry of Lands, Agriculture and Rural Settlement, Harare, Zimbabwe.

[3] Cordell H K, McDonald B L, Teasley R.J., Berbstrom J C Martin J Bason J. & Leeworthy V L (1999)–Outdoor recreation participation trends. In Outdoor recreation in American life: a national assessment of demand and supply trends (H.K. Cordell, ed.). Sagamore Publishing, Champaign, 449 pp.

[4] Cubbage F W, O’Laughlin J & Bullock C S (1993) – Forest resource policy. John Wiley & Sons, Inc, New York, 562 pp.

[5] Cumming D.H. (1982).–The influence of large herbivores on savanna structure in Africa. In Ecology of tropical savannas (B. J. Huntley & B.W. Walker, eds). Ecol. Studies, 42, 217-245.

[6] Dallmeier F. (1991).–Whistling ducks as a manageable and sustainable resource in Venezuela: balancing economic costs and benefits. In Neotropical wildlife use and conservation (J.G. Robinson & K.H. Redford, eds). University of Chicago Press, Chicago, 266-287.

[7] Ramchandra (2015), impact of free ranging wildlife on agricultural economics-lecture delivered in a Summer School entitled “Management of natural resource for livelihood security organised by SHIATS 18 November -8 December, 2015.

...Table 5 (Contd.)

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Significant of Anaerobic Treatment of High Sulphate Content Tannery Effluent at Jajmau, Kanpur, Uttar Pradesh

Richa Gupta1*, Tanu Jindal1, Prateek Srivastava1, Ambrina Sardar Khan1 and Ajay Kanauji

1Amity Institute of Environmental Sciences, Amity University, Noida (U.P.)–201303, India

2Ganga Pollution Control Unit, Jal Nigam, Kanpur (U.P.)–208001, India


ABSTRACT

Tannery industries are playing an important role in economic activity around the world and the uncontrolled release of tannery effluents (treated or semi-treated) to natural water bodies causes environmental degradation and increases health risks to human beings. Tannery industries discharged their effluents on land for irrigation purposes. The treatment of tannery effluent is acomplex technological challenge because of the presence of high concentrations of organic and inorganic pollutants of both conservative and nonconservative nature. The environmental protection regulations stipulate that industries are not allowed to emit sulfide and chromium in the wastewater. Thus removal of sulfide and chromium from the wastewater is very important. These effluents contained a high concentration of Sulphate (SO4) and sulfide (H2S, HS, S) ions in different forms. Sulfide concentration is increased after treatment by conversion of sulfate into sulfide, in UASB treatment plant. In the winter season, sulfate and Sulphide is 3430 ppm and 75 ppm on L1 and 891 ppm and 186 ppm on L2 location and 672 ppm and 62 ppm on L3 location. In summer season Sulphate is 2644 ppm on L1 and 416 ppm on L3 and Sulphide is maximum on L2 location i.e. 159 ppm in the summer season. Hence In this paper, the characteristics of effluents do not permit its disposal for irrigation purposes. The effluents directly affect the groundwater as well as surface water quality and also affect the crop.

Keywords: Wastewater, Tannery Effluent, Sulphate, Anaerobic, Sulfide

INTRODUCTION

Leather processing is an important economic activity in many developing and developed countries. Since most of the developing countries are using traditional leather processing, the characteristics of effluent are similar. Tanneries in India are categorized as small (approximately 80 %), medium (approximately 15%) and large-scale [1]. The tannery is an important industry in the country. Tanning or Leather processing industries occupy the significant place in an economy as it provides massive employment opportunities to people [2]. Tanning is the chemical process that converts animal hides and skin into leather and related products [3]. The major components of the effluent include sulfide, chromium, volatile organic compounds, large quantities of solid waste, suspended solids like animal hair and trimming. These tanneries are

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mainly located in the states of Tamilnadu, Karnataka ka, Andhra Pradesh, Rajasthan, Punjab, Utter Pradesh and West Bengal [4]. The Process of tanning consumes a huge amount of water and generates a large volume of wastewater which contains various harmful chemicals and toxic trace elements. These have an adverse effect on plant growth, the health of animals and people existing in that area [5-6]. The tannery effluent produced from traditional or conventional leather processing contains a high concentration of organics (COD/BOD), Suspended Solids (S.S) and inorganic like NH4-N, SO4

2-/S2-, Cr(III) and Chlorides [7-8]. These industries are characterized as highly polluting industries which generate the high strength of wastewater that is difficult to treat [9]. Several high toxic components are found in effluent water which affects human beings, agriculture, and livestock and causes several diseases like eye diseases, skin irritations, kidney failure, and gastrointestinal problem. Industrial effluents from leather tanneries discharged untreated if allowed to percolate into the soil to groundwater for a prolonged period seriously affect soil profile and the groundwater table which is unfit for drinking, irrigation and for general consumption. It has been established that a single tannery can cause pollution of groundwater around a radius of 7 to 8 km [10-11]. These industries also cause soil, water, and surface water pollution. The maximum concentration of waste material absorbed by the bioaccumulation process in cultivated crops irrigated by tannery effluent. Most of the industries are dumping their effluent with treatment or partially treated effluent.

In India, province of Uttar Pradesh alone responsible for more than half of toxins that influencing the groundwater quality, soil profile because of irrigation with treated and partially treated wastewater. In Uttar Pradesh, Kanpur is a cluster of leather industries. Pollution becomes acute when tanneries are concentrated in clusters in a small area like Kanpur, India[12]. In Kanpur mainlyJajmau industrial area having 400 tanning industry. During the tanning process, about 300 kg of chemicals is added per ton of hides. Based on the tanning agents, tanning operations are further divided into vegetable tanning and chrome tanning. Vegetable tanning is usually done in a series of vats by using natural organic substances and chrome tanning is based on chromium salt mainly basic chromium sulfate [3]. In Jajmau, Kanpur industrial area, All industries are based on the chrome tanning process. Hence, appropriate treatment of effluent is required prior to its discharge into the environment [8]. There is CETP operating for treatment of tannery wastewater. The treated tannery effluent is being used for irrigation nearby area which is 1800 hectare. The Effluent of tannery wastewater contains high COD, BOD, TSS, and Sulphide. Sulfide is one of the major components of wastewater of tannery effluent and found in form of H2S, HS-[6]. Uncontrolled release of tannery effluents to natural water bodies causes environmental degradation and increases health risks to human beings. Sulfide is highly toxic in nature which decreases the level of oxygen and also causes the acid deposition on water. Sulfide level in effluent makes external environment corrosive by making the treatment of effluent difficult [2] and even low concentration of sulfide is toxic for a human being and affect the nervous system sometimes causes death. It causes death within 30 min at concentrations of on 800–1000 mg/l, and instant death at higher concentrations [13]. Sulfide is also corrosive in nature. The corrosive properties of sulfide are apparent. Soluble sulfide ranging from 50 –100 mg/L can be tolerated in anaerobic treatment with little or no acclimate ion [14]. In Treatment Plant if sulfide is carried to biological aerobic basin it makes it inefficient. So, it is imperative to remove sulfide before aerobic biological system [15]. Treated and partially treated wastewater is being used for irrigation purposes which has a high concentration of sulfite. The environmental protection agencies control that industries are not permitted to

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Significant of Anaerobic Treatment of High Sulphate Content Tannery Effluent at Jajmau, Kanpur, Uttar Pradesh 189

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produce sulfide in the wastewater. Hence the aim of the study to know the Significant of Anaerobic treatment of high sulfate content tannery effluent at Jajmau, Kanpur, Uttar Pradesh.

Tannery waste material also varies considerably in volume and concentration due to continuous operation and intermittent discharge Tannery waste material also varies considerably in volume and concentration due to continuous operation and intermittent discharge Tannery waste material also varies considerably in volume and concentration due to continuous operation and intermittent discharge

SCOPE AND OBJECTIVES

A number of researchers and analyst whipped away the removal of sulfide and various toxic substances from the wastewater streams, but little has been reported on the sulfide removal from the tannery wastewater. The objective of the study was:

● To check the concentration of Sulphate and sulfide from tannery wastewater including Influent.

● To analysis of Effluentwhich is being used for irrigation.

● Impact of sulfide content effluent on irrigation and water body.

ANAEROBIC TREATMENT OF SULFATE-BEARING TANNERY EFFLUENTS

Under anaerobic conditions, sulfate can act as an electron acceptor for a group of bacteria that can couple the oxidation of reduced organic or inorganic compounds to the reduction of sulfate for bioenergetics purposes. This process is known as dissimulator sulfate reduction (Sulphidogenesis) and the bacteria involved are known as the sulfate reducers or sulfate-reducing bacteria [16-18]. Anaerobic treatment of wastewater converts the organic pollutants into a small amount of sludge and a large amount of biogas (methane and carbon dioxide). The sulfide present in wastewater inhibits the anaerobic treatment [3]. There is several effects of sulfide formation in anaerobic reactors like Reduced COD removal efficiency, increases the corrosivity and less methane formation [19]. Methanogenic bacteria are inhibited by sulfide, whereas acidifying and sulfate-reducing bacteria do not inhibit. The extent of these effects depends on the experimental system used [3].


Study AreA

The district Kanpur located between 800 21” East longitudes and 260 28’’North latitude in Uttar Pradesh, India. It is situated on the bank of Ganga River. In Kanpur city, Jajmau is a famous leather industrial area. It is one of the biggest exporting centers of tanned leather. Above 400 tanneries are located at Jajmau (Kanpur). The treated and partially treated wastewater is being used more than two decades for the irrigation and for the study. Effluent channel was selected where effluent is being used for irrigation purposes.

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SAmpling SiteS, ColleCtion And AnAlySiS

The sites identified for the sampling are mainly used for agriculture purposes. Two sampling was done in the year of 2016-2017. One sampling in summer and another was in the winter season. I was selected major 03 locations for sample collection i.e.effluent channel from 36 mild UASB based tannery wastewater treatment plant (C.E.T.P.). Name of sites was Tannery effluent (L1), UASB effluent (L2) and Final Treated effluent (L3) which was diluted with STP effluent. Samples were collected with minimum aeration. For field and laboratory work, the method followed by IS 3025. Samples were collected in plastic cans which previously rinsed with triple distilled water and fixed the sulfide concentration by using zinc acetate and sodium hydroxide solution. Tannery effluent (L1) collected from equalization tank, UASB effluent (L2) collected from just after UASB reactors and Mixed effluent (L3) collected from where tannery treated effluent water mixing with STP water and using for irrigation purposes at the samples to a laboratory for further analysis. Turbidity method (UV method) was applied for analysis of sulfate concentration which referred from IS 3025 part 24 and Isometric method (titrimetric method) was followed for analysis of sulfide concentration which referred from IS 3025 Part 29.


The effluent water quality depends on the operation of the treatment system. Sulfate and sulfide were found in high concentration but sulfide is more than sulfate due to the conversion of sulfate into sulfide. The concentration is given in table no 1. Most extreme grouping of sulfate was found on tannery gushing (L1) area in winter season and sulfide is 75 ppm and in same season Sulfide is expanding in UASB emanating (L2) i.e. 186 ppm by transformation of sulfate into sulfide in anaerobic conditions by sulfate-reducing microorganisms. Hydrogen sulfide (H2S) is an inhibitor for the biological activity. Due to very favorable conditions for sulfate reduction in anaerobic reactors, it has been studied especially when the effluent is naturally enriched with sulfate forms [20] and On L3 sampling station sulphate and sulphide concentration decreases because STP treated water is mixing with tannery treated water due to this concentration of sulfate and sulfide decreasing by dilution. In the summer season, Sulphide concentration is 159 ppm on L22 site i.e.increasing after treatment and Sulphate is 2644 ppm on L1 site. Sulfide concentration is increasing in the winter season on L2 location in comparison to the summer season.

Table 1: Showing the Concentration of Sulphate and Sulphide in a Different Location of Tannery Wastewater Treatment (CETP) Plant in Summer and Winter Season

Parameter Season Sulfate (SO4), ppm Sulfide (H2S), ppm

L1 L2 L3 L1 L2 L3

Summer Season 26 44 530 416 87 15

95 6

Winter Season 34 30 891 672 75 18

66 2

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CONCLUSION

Tannery wastewater is difficult to treat due to the high concentration of BOD, COD, chromium, and sulfide. The treated tannery effluent after chromium removal is found to be suitable for stage biological treatment. Sulfate generated during the process also gets converted into sulfide during anaerobic treatment. Lower SO4 ratio of tannery effluent is an impediment in successful anaerobic treatment. In the absence of dissolved oxygen and nitrate, sulfate-reducing bacteria converts sulfate into sulfide. Sulfide inhibition control is essential for an effective anaerobic treatment of tannery effluent with the high cost of treatment with less biogas recovery. Anaerobic treatment of tannery wastewater gives better results but the formation of sulfide in anaerobic reactors restricts its application. The high sulfide concentration affects the crop and vegetable at the irrigation field and the operational cost of such technologies is high. The aerobically treated industrial waste shows, should not be used for irrigation purposes.

REFERENCES

[1] Kennedy L. (1999). Co-operating for survival: Tannery pollution and joint action in the Palar valley, India. World Development 27: 1673-1691.

[2] Kothiyal M., Kaur M. and Dhiman A. (2016). A comparative study on the removal efficiency of sulphide and cod from the Tannery effluent by using Oxygen Injection and Aeration. International Journal Environment Research, 10(4): 525-530, ISSN: 1735-6865.

[3] Midha Varsha and Dey Apurba (2008). Biological treatment of tannery wastewater for sulfide removal, International Journal of Chemical Sci., 6(2), 472-486.

[4] Lefebvre O., Vasudevan N., Torrijos M., Thanasekaran K., Moletta R. (2005). Halophilic biological treatment of tannery soak liquor in a sequencing batch reactor. Water Research 39: 1471-1480.

[5] Bhatnagar M.K., Singh R., Gupta S. and Bhatnagar P. (2013). Study of tannery effluents and its effects on sediments of river ganga in special reference to heavy metals at Jajmau, Kanpur, India. Journal of Environmental Research and Development, 8(1).

[6] Richa Gupta, Prateek Srivastava, Ambrina Sardar Khan and Ajay Kanaujia (2018). Impact of Sulphideon Irrigation, Generated from Anaerobic ally Treated Tannery Effluent at Jajmau, Kanpur, International Journal for Research in Applied Science & Engineering Technology (IJRASET), ISSN: 2321-9653; Volume 6 Issue V.

[7] UNIDO (2000). Pollutants in tannery effluents, Regional Programme for Pollution Control in the Tanning Industry in South-East Asia, The Scope for Decreasing Pollution Load in Leather Processing.

[8] Kaul S.N., Tapas N., Vyas R.D., Szpyrkowicz L. (2001). Waste management in tanneries: Experience and outlook. Journal of Indian Association of Environmental Management 28: 56-76.

[9] Durai G. and Rajasimman M. (2011). Biological Treatment of Tannery Wastewater – A Review. Journal of Environmental Science and Technology, 4 (1), 1-17.

[10] Bhaskaran T.R., Treatment and disposal of tannery Effluents, CLRI, Chennai.[11] Central Leather Research Institute report on capacity utilization and scope for modernization in

Indian tanning Industry (1990). CLRI Chennai, P. 12.[12] Beg K. R. and Ali S. (2008). Chemical Contaminants and toxicity of Ganga river sediment from up

and down stream area at Kanpur Am. J. Environ. Sci., 4(4), 362-366.[13] Aloton Ldil Arslan and Hancl Assoc.Prof. Tugba Olmez (2002). Chemical Oxidation Applications

for Industrial Waste Water. Iwa publishing, 8, 89-80.[14] Angkawisttpan N. and Manasri T. (2002). Physical Chemical Process for Waste Water Treatment

Environmental Expert, Das Waste Gas Treatment Waste Water Treatment Industries Company Service, 12, 82-95.

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[15] Sanjay R. and Vaishnav Raj K.S. (2014). Biological Treatment of Tannery Effluent. International Journal of Advances in Applied Science and Engineering (IJAEAS), 1(1), pp: 4-8.

[16] Sabumon P.C.(2016). Perspectives on Biological Treatment of Tannery Effluent, Advances in Recycling & Waste Management: Open Access, 10.4172/2475-7675.1000104.

[17] Widdel F. (1988). Microbiology and ecology of sulphate and sulphur reducing bacteria. In: Zehnder AJB (eds.) Biology of Anaerobic microorganisms. Wiley & Sons, New York, USA, pp: 469-586.

[18] Odum J.M. and Singleton R. (1992). The sulphate-reducing bacteria: Contemporary Perspectives. Springer Verlag.

[19] Hulshoff Pol L. W., Lens P. N. L., Stams A. J. M. and Lettinga G.(1998), Biodegradation, 9, 213.[20] Kalyuzhnyi S. V., Fragoso C., De.leon, Martinez J. R. (1997). Biological sulfate reduction in a

UASB reactor fed with ethanol as the electron donor. Mikrobiologiya, v. 66, n. 5, pp: 562-67.

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Morphometric Analysis and Bioefficacy of Trichogramma cordubensis Vargas & Cabello against Teak Defoliator, Hyblaea puera

Salman Khan* and Mohd. YousufForest Entomology Division, Forest Research Institute,

P.O. New Forest, Dehradun, Uttarakhand–248006, IndiaE-mail: *[email protected])

ABSTRACT

The insect plays important role in the management of the biodiversity of any country. For the identification and separation of the micro-hymenopteran insects, the morphometric tool can be utilized. Attempts were made to identify and separate out the important characters of Trichogramma cordubensis for taxonomic separation. The teak defoliator, Hyblaea puera was also successfully controlled by using T. cordubensis in both one pair and five pair experiments. The detailed observation and results are also discussed.

Keywords: Bioefficacy, Forestry, Morphometrics, Teak, Trichogramma Cordubensis

INTRODUCTION

Indian forests have high species richness and very diverse (Sharma et al., 2009). The richness in the biodiversity is primarily due to the climatic factors (Kharkwal et al., 2005). The diversity is not seen in plants and animals only but in insects too. To identify the biological resources of the country, the identification of the species is very important. The identification of large animals and insects are comparatively easier than the tiny one. The classification of smaller insects is equally important as of larger insects as both have equal importance as biodiversity is concerned. Trichogramma spp. areminute parasitic wasp belonging to the order Hymenoptera and family Trichogrammatidae. The species of genus Trichogramma are being utilized in biological control programs against agriculture and forestry pests, worldwide. Trichogramma spp. are host specific and only a few species have large host range like T. chilonis and T. japonicum. So, identification of Trichogramma spp. becomea vital component when any species is being provided/utilized to control the population of the target pest. In the present study, attempts were made to identify the Trichogramma cordubensisVargas & Cabellobased on the morphometric tool.


The culture of Trichogramma cordubensis was procured from ICAR-National Bureau of Agricultural Important Resources (NBAIR) in September 2016 with accession no. NBAII-MP-TRI-55.The procured culture was maintained in the laboratories at optimal conditions on rice moth (Corcyra cephalonica) eggs. About 12 males and 12 females were utilized/dissected for the morphometric study and slides were prepared using the methodology suggested by Hassan

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and Yousuf (2007) and Yousuf et al. (2008)using stereoscopic zoom binocular microscope (Aark International). The morphometric measurements were taken on Leitzlaborluxs (Leica, Germany)and slides were deposited to NFIC (National Forest Insect Collection, FRI Dehradun) with Accession no. 22109. Morphological characters reported by Hassan and Yousuf (2007) were taken into consideration. A total of 33 characters (including their ratios) of males and 27 characters (including their ratios) of females of T. cordubensis were considered for the analysis.


The measurements taken on the morphometrics of T. cordubensis is given in Table 1 and 2.The characterssuch as body length, head width, malar space, flagellar width, fore wings width, marginal length of fore wings, hind wings length and width, marginal length of hind wings, hind tibia lengthare larger in males in comparisons to the females. Similarly, characters such as head length, eye width, antennal club length, fore wings length, hind tibia width were greater in females. The study follows the similar results as described by García, 1986; Gibbs et al., 2004; Vargas and Cabello, 1985. Apart from this the Hassan and Yousuf (2007) have also worked on the morphometrics of T. plasseyensis along with the diagnostic characteristics. Yousuf et al. (2008) have done a similar experiment for the morphometrics of Trichogramma raoi.

Apart from the morphometrics experiment, bioefficacy of T. cordubensis was also tested against the eggs of Teak defoliator (Hyblaea puera). The 100 eggs of H. puera was provided to the 1 male and 1 female (one pair) of T. cordubensis for parasitization and data was recorded. Similarly, five males and five females of T. cordubensis were provided to the 100 eggs of H. puera. The bioefficacy of the Trichogramma cordubensis against the eggs of H. puera was shown in Table 3.

Table 1: Morphometrics of Main Characters for Males and Females of Trichogramma Cordubensis Vargas and Cabello

S. No. Characters T. cordubensis(Male)

T. cordubensis(Female)

1 Body length0.5013±0.017 0.4957±0.023

(0.4650-0.5208) (0.4743-0.5394)

2 Head length0.1888±0.011 0.1953±0.007

(0.1748-0.2116) (0.1840-0.2070)

3 Head width0.2144±0.011 0.2141±0.010

(0.1955-0.2277) (0.1932-0.2300)

4 Eye width0.0888±0.005 0.0922±0.004

(0.0805-0.0966) (0.0851-0.0966)

5 Malar space0.0564±0.002 0.0547±0.003

(0.0529-0.0598) (0.0506-0.0575)

6 Flagellar length/Antennal club length

0.1698±0.010 0.0818±0.003

(0.1503-0.1833) (0.0770-0.0880)

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7 Flagellar width/Antennal club width

0.0352±0.003 0.0326±0.004

(0.0293-0.0367) (0.0293-0.0403)

8 Flagellar hair length0.0803±0.004

------------(0.0733-0.0843)

9 Fore wings length0.5031±0.017 0.5059±0.018

(0.4743-0.5208) (0.4743-0.5301)

10 Fore wings width0.2492±0.012 0.2437±0.011

(0.2325-0.2697) (0.2325-0.2604)

11 Marginal length of fore wings

0.0301±0.003 0.0283±0.001

(0.0253-0.0345) (0.0276-0.0299)

12 Hind wings length0.4156±0.009 0.3938±0.024

(0.3979-0.4232) (0.3358-0.4140)

13 Hind wings width0.0389±0.001 0.0389±0.001

(0.0368-0.0414) (0.0368-0.0414)

14 Marginal length of hind wings

0.0559±0.003 0.0554±0.003

(0.0483-0.0575) (0.0529-0.0598)

15 Hind tibia length0.1653±0.006 0.1617±0.026

(0.1540-0.1723) (0.0880-0.1760)

16 Hind tibia width0.0238±0.002 0.0253±0.002

(0.0220-0.0257) (0.0220-0.0293)

17 Genitalia capsule length0.1449±0.004

------------(0.1380-0.1518)

18 Genitalia capsule width0.0518±0.003

------------(0.0483-0.0575)

19Distance b/w Chelate

structureto Gonoforceps

0.0170±0.001------------

(0.0161-0.0184)

20 Aedeagus length0.1297±0.005

------------(0.1196-0.1380)

21 Ovipositor length ------------0.1868±0.009

(0.1702-0.1955)

22 Setae in RS1 3-5 3-4

23 Setae in RS2 10-13 10-13

24 Setae in RM 18-24 18-23

25 Setae in RR 42-54 43-58

26 No. of flagellar hairs 28-53 ------------

Note: Mean±standard deviation (top value) and range (parentheses); S. No. 1-21 are in mm and 22-26 are in numbers.

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Table 2: Morphometrics of Ratios Characters for Males and Females of Trichogramma Cordubensis Vargas and Cabello



1 Flagellar hair length/Flagellar width

2.2936±0.218------------

(2.0000-2.6250)

2 Flagellar length/Flagellar width

4.8389±0.349------------

(4.5000-5.5000)

3 Flagellar length/Hind tibia length

1.0337±0.052------------

(0.9318-1.0909)

4 Antennal club length/Antennal club width ------------

2.5357±0.286

(2.1000-2.8750)

5 Ovipositor length/Antennal club length ------------

2.2860±0.123

(2.1097-2.4790)

6 Hind tibia length/Antennal club length ------------

1.9823±0.335

(1.0435-2.1818)

7 Fore wings length/Fore wings width

2.0207±0.063 2.0784±0.084

(1.9286-2.1154) (1.9615-2.2400)

8 Fore wings width/Marginal length of fore wings

8.3603±1.010 8.6235±0.479

(6.7391-9.9249) (7.7759-9.4348)

9 Hind wings width/Marginal length of hind wings

0.6980±0.056 0.7020±0.027

(0.6400-0.8095) (0.6538-0.7391)

10 Genitalia club length/Genitalia club width

2.8059±0.154------------

(2.6087-3.0476)

11 Genitalia club length/Hind tibia length

0.8824±0.023 ------------

(0.8541-0.9123)

12 Ovipositor length/Hind tibia length ------------

1.2013±0.325

(1.0090-2.1168)

Note: Mean±Standard Deviation (Top Value) and Range (Parentheses)

Table 3: Parasitization Percentage of Trichogramma Cordubensisagainst Hyblaea Puerain One Pair and Five Pairs

ReplicationsT. cordubensis

One pair (%) Five pairs (%)

1 13 73

2 15 77

3 17 61

4 14 68

5 14 71

Mean 14.6 70

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In one pair, the average parasitization was observed as 14.6% and in five pairs, the parasitization was 70%. A similar experiment was conducted by Ahmad (1990, 1992). In five pairs experiment, high parasitization was observed and thus, this species can be recommended for biological control programmes for manging the population of H. puera. The results depict that T. cordubensis accept the eggs of H. puera for completing its life cycle. Patil and Thontadarya (1983, 1984) tested the different species of Trichogramma against the teak skeletonizer (Eutectona machaeralis) and found significant results but they have not tested the Trichogramma spp. against H. puera. Kumar et al. (2008) have also tested the similar objective against the Clostera fulgurita eggs.

CONCLUSION

The morphometrics is the tool being utilized now a days for the identification and separation of the Trichogramma spp. apart from the molecular tools. The different characters of T. cordubensis were identified and measured to separate from other species of Trichogramma. The bioefficacy of T. cordubensis was also tested against the eggs of H. puera. The result suggests that. cordubensis can be utilized for the control of the population of teak defoliator, H. puera.

ACKNOWLEDGMENTS

We would like to thank Director, Forest Research Institute, Dehradun (Uttarakhand, INDIA) for providing the necessary research facilities. We are also greatly indebted to the authorities of NBAIR, Bangalore for providing the culture of Trichogrammacordubensis for the study.

REFERENCES

[1] Ahmad, M. (1990).Potentiality of egg parasites, Trichogramma spp., against defoliating pests of teak, Tectona grandis.LF.Annals of Entomology, 8: 119-122.

[2] Ahmad, M. (1992).Bio-efficacy of egg parasites, Trichogramma spp. against poplar defoliator, Clostera cupreata. Indian Journal of Forestry, 15(3): 198-202.

[3] García, T.C. (1986). Especies de Trichogramma (HYM.:Trichogrammatidae) parásitas de Heliothisarmigera Hub. (LEP.:Noctuidae) en Andalucía (I). Boletín de sanidad vegetal.Plagas, 12(2): 323-333.

[4] Gibbs, M., Broad, G. R. and Polaszek, A. (2004).Trichogramma gicai Pintureau&Stefanescu, 2000 (Hymenoptera: Trichogrammatidae) reared as an egg parasitoid of the Madeiran endemic butterfly, Parargexiphia(Lepidoptera: Satyridae). Bocagiana, 214: 1-5.

[5] Hassan, E. and Yousuf, M. (2007). First record of Trichogramma plasseyensis Nagaraja (Hymenoptera: Trichogrammatidae), from central India, and its morphometric & additional diagnostic characters. Indian Journal of Entomology, 69(1): 58-62.

[6] Kharkwal, G., Mehrotra, P., Rawat Y.S., Pangtey, YPS. (2005). Phytodiversity and growth form in relation to altitudinal gradient in the Central Himalayan (Kumaun) region of India. Current Science, 89(5): 873-878.

[7] Kumar, S., Kumar A. and Khan, M. A. (2008).Evaluation of different species of Trichogramma against eggs of Poplar defoliator, Clostera fulgurita Walker. Pantnagar Journal of Research, 6(2): 291-292.

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[8] Patil, B.V. and Thontadarya, T.S. (1983). Studies on the Acceptance and Biology of Different Trichogramma Spp. on the Teak Skeletonizer, Pyraustamachaeralis Walker. Indian Forester, 109(5): 292-297.

[9] Patil, B.V. and Thontadarya, T.S. (1984). Efficacy of Egg Parasite, Trichogramma Spp. in Parasitising the Eggs of the Teak Skeletonizer, Pyraustamachaeralis Walker (Lepidoptera: Pyralidae). Indian Forester, 110(4): 413-417.

[10] Sharma, C.M. Suyal, S. Gairola, S. and Ghildiyal, S.K. (2009). Species richness and diversity along an altitudinal gradient in moist temperate forest of Garhwal Himalaya. Journal of American Science, 5(5), 119-128.

[11] Vargas, P. and Cabello, T.(1985).A new species of Trichogramma [T. Cordubensis n. sp.][Hym.: Trichogrammatidae], parasitoid of Heliothis eggs in cotton crops in the SW of Spain. BioControl, 30(3): 225-230.

[12] Yousuf, M. Hassan, M.E. and Joshi, K.C. (2008). Record of Trichogramma raoi Nagaraja (Hymenoptera: Trichogrammatidae), from central India, along with additional morphometric and diagnostic characters. Journal of Tropical Forestry, 24(III & IV): 69-74.

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Selecting Sites to Save Maximum Species

Shri Niwas SinghDepartment of Genetics & Plant Breeding,

Baba Raghav Das P.G. College,Deoria–274001 (U.P.) India.

E-mail: [email protected], [email protected]

ABSTRACT

A method is given to select sites that would maximize the number of species being saved. A computer program named testall.c uses a combinatorial approach and adopts parallel processing to test all possible combinations in all groups and gives the optimal solutions. However, if there are a large number of sites then it is not possible to test all possible combinations and get solutions in real time. Therefore, it is argued to pool similar sites into clusters of sites of the manageable number and test all possible combinations. The method is shown with an example of a data set from Uttara Kannada district of Karnataka state, India. Greedy method or its variants are commonly used for reserve selection or such other problems. However, greedy methods are not foolproof. Therefore, testing all possible combinations in selecting sites for conservation becomes important and necessary if the objective is to save the maximum species.

Keywords: Conservation; Greedy Methods; Maximize; Reserve Selection; Optimal Solutions.

INTRODUCTION

Sometimes, decisions about selection of sites for conservation purposes are taken based on presence-absence of plant genetic resources at various sites. One must know the questions like 1. which species are to be conserved? 2. where are those species located? 3. how much area do we want to set aside for conservation purpose? and 4. whether the conservation area should be in one big piece or many small pieces? or the so-called SLOSS (single large or several small) debates. Since commonly used greedy algorithms of reserve selection are not foolproof, an alternative approach is suggested here. This paper deals with some of these issues and gives a novel approach to test all possible combinations for reserve selection. This combinatorial approach works well when there are a small number of sites. When there are a large number of sites (say more than 30), then sites could be classified into the cluster(s) of similar sites to pool similar sites. With this reduced number of sites (actual clusters of sites), it would be possible to test all possible combinations to save maximum species.


In a presence/absence matrix (Appendix 3.1 of Singh 1996), there are 430 plant species listed from 46 sites situated in the Uttara Kannada district of Karnataka state, India. If there are enough resources then all the 46 sampled sites could be selected to conserve all the 430 species. This could be one approach. However, if we have limited resources or we are willing to save only a certain fraction of these plant species/sites then the question arises about which combination of sites should be chosen to maximize the number of species being saved.

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The number of possible combinations of sites taking 0, 1, 2, 3, ..., 46 site(s) at a time out of 46 sites is given by the coefficients of the binomial expansion 46Cr, where r ranges from 0 to 46. In each group of combinations, there will be one or more combinations of sites which would save the maximum number of species. It is relatively easy to obtain the combination of the site(s) giving a maximum number of species when the number of sites (more importantly), as well as the number of species, are a few. However, as the number of sites increases, the number of all possible combinations to be tested increases exponentially. For n sites, the total number of possible combinations to be tested will be 2n (which is sum of the binomial coefficients) in n+1 groups (which is a number of terms in the binomial expansion). The first and the last groups will have one combination each with zero and all sites and thus with zero and all species respectively. However, it becomes very much time consuming even for computers to get the answers for the rest of the groups especially the middle ones. The time taken to get the answers for these groups will be proportional to the coefficients of binomial for respective groups. In the case of this example, 246-2 combinations will have to be tested in 45 groups.

A computer program testall.c (Appendix 3.3 of Singh 1996) tests for all possible combinations of site(s) in each group and lists the following: 1. maximum number of species being saved and the combination of site(s) giving that number, 2. minimum number of species being saved and the combination of site(s) give in that number, and 3. the average number of species that would be expected to be saved from all possible combinations. This program works with l for a small number of sites (maximum up to 20-30 or so) in a reasonable time, but as the number of sites increases, the number of possible combinations to be tested increases exponentially. Hence, it takes an enormous amount of time even for fast computers to test all possible combinations, the especially in the middle groups. Therefore, 46 sampled sites were clear, classified based on presence/absence of 430 species by complete linkage clustering and a manageable number of clusters of the site(s) were obtained by putting a cut-off point at a suitable distance. The 14 clusters thus obtained were used to prepare a presence/absence matrix of 430 species distributed over 14 clusters of the site(s) (Appendix 3.2 of Singh 1996). Now, with a small number of clusters of the site(s), it was possible to test all possible combinations (using testall.c) to find out which combination of clusters would give the maximum number of species taking 0, 1, 2, ..., 14 clusters at a time out of 14 clusters. Species-are curves were made from these results.


Fthe or 430 x 46 matrix, program testall.c works well a and gives perfectly correct results. However r, for middle groups, the results do not come in real ti, me. Therefore, only for the initial four and the last four groups, the results are given in Tables 1 the (a, b and c). The results, of the analysis after clustering 46 sites into 14 clusters of sites, are given in Tables 2 (a, b and c). These results ara e optimal solutions because it was possible to test all possible combinations since there were only 14 clusters of sites. Table 2a gives the combinations of the cluster(s) giving a maximum number of species. Table 2b gives the combinations of the cluster(s) giving a minimum number of species and Table 2c lists the average number of species that would be expected to be saved if all possible combinations are considered. The species-area curves based on Table 2 are given in Fithe figure 1. It is clear from Table 2 and Figure 1 that one can maximize the number of species being saved just by choosing the proper combinations of the cluster(s) of sites. The species-area curve represented by a maximum in Figure 1 peaks earlier

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Selecting Sites to Save Maximum Species 201

ISBN: 978-93-88237-24-6

as compared to the other possibilities showing the importance of choosing proper combinations of clusters of sites.

Table 1: Results of Testall.c for Initial Four and Last Four Groups of Combinations for 430X46 Matrix

Table 1(a): Maximum Number of Species Being Saved and the Combinations

No. of Sites Taken at a

Time Out of 46 Sites

No. of Species

Being SavedSite Combination

1 125 22

2 179 22 38

3 209 14 22 38

4 235 14 22 38 46

(For middle groups, it is not manageable).

43 430 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

24 25 26 27 28 30 32 33 34 35 37 38 39 40 41 42 43 44 45 46

44 430 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

24 25 26 27 28 29 30 32 33 34 35 37 38 39 40 41 42 43 44 45 46

45 430 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

24 25 26 27 28 29 30 31 32 33 34 35 37 38 39 40 41 42 43 44 45 46

46 430 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46

Table 1(b): Minimum Number of Species Being Saved and the Combinations of Sites Giving Those Number of Species

No. of Sites Taken at a Time out of

46 Sites

No. of Species

being SavedSite Combination

1 2 3

2 12 3 13

3 23 1 3 8

4 31 1 3 4 8


43 401 1 2 3 4 5 6 7 8 9 10 11 12 14 15 16 17 18 19 20 21 22 23

24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 43 45 46

44 409 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 43 45 46

Table 1(b) (Contd.)...

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No. of Sites Taken at a Time out of

46 Sites

No. of Species

being SavedSite Combination

45 419 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 43 44 45 46

46 430 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46

Table 1(c): Average Number of Species That would be Expected to be Saved If All Possible Combinations of Sites are Considered

No. of Sites Taken at A Time Out of 46 Sites Avg. No. of Species Being Saved

1 58.46

2 101.8

3 135.1

4 161.8

. …


. …

43 421.5

44 424.4

45 427.2

46 430

Table 2: Results of Testall.c for 430 x 14 Matrix.Table 2(a): Maximum Number of Species Being Saved and The Combinations of Sites Giving those Number of Species

No. of Sites

Species Saved Site or Cluster Combination

0 0 0

1 250 12

2 322 12 13

3 355 6 12 13

4 380 6 9 12 13

5 400 6 7 9 12 13

6 408 6 7 9 12 13 14

7 414 6 7 9 11 12 13 14

...Table 1(b) (Contd.)

Table 2(a) (Contd.)...

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No. of Sites

Species Saved Site or Cluster Combination

8 419 3 6 7 9 11 12 13 14

9 423 3 6 7 9 10 11 12 13 14

10 426 1 3 6 7 9 10 11 12 13 14

11 429 1 3 4 6 7 9 10 11 12 13 14

12 430 1 2 3 4 6 7 9 10 11 12 13 14

13 430 1 2 3 4 5 6 7 9 10 11 12 13 14

14 430 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Table 2(b): Minimum Number of Species Being Saved and the Combinations of Sites Giving Those Number of Species

Sl. No.

No. of Species Being Saved Combination of Site(S)/Cluster(S) Giving That Many Species

1 2 5

2 12 5 14

3 24 2 5 14

4 41 2 5 8 14

5 66 1 2 5 8 14

6 85 1 2 3 5 8 14

7 111 1 2 3 4 5 8 14

8 165 1 2 3 4 5 8 10 14

9 201 1 2 3 4 5 8 10 11 14

10 242 1 2 3 4 5 6 8 10 11 14

11 275 1 2 3 4 5 6 7 8 10 11 14

12 312 1 2 3 4 5 6 7 8 9 10 11 14

13 382 1 2 3 4 5 6 7 8 9 10 11 12 14

14 430 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Table 2(c): Average Number of Species That would be Expected to be Saved If All Possible Combinations are Considered

Serial No./ No. of Clusters Chosen

No. of Species Being Saved

Sl. No. No. of Species

Cluster No. No. of Species

1 83.36 1 34 12 250

2 146.4 2 13 13 224

3 195.7 3 42 6 136

...Table 2(a) (Contd.)

Table 2(c) (Contd.)...

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Serial No./ No. of Clusters Chosen

No. of Species Being Saved

Sl. No. No. of Species

Cluster No. No. of Species

4 235.3 4 54 7 124

5 268.1 5 2 11 97

6 295.8 6 136 10 83

7 319.7 7 124 9 79

8 340.7 8 19 4 54

9 359.4 9 79 3 42

10 376.2 10 83 1 34

11 391.4 11 97 8 19

12 405.3 12 250 2 13

13 418.1 13 224 14 10

14 430 14 10 5 2

Table 3: Percentage of Species being Saved and Trend in Beta Diversity for 430 x 14 Matrix

Sl. No

Maximum Minimum Average

No. of Species being Saved

Beta Diversity

% of Species being Saved


Beta Diversity

% of Species being Saved


Beta Diversity

% of species being Saved

1 250 0.224 58.14 2 0.833 0.465 83.36 0.431 19.386

2 322 0.093 74.88 12 0.5 2.791 146.4 0.252 34.053

3 355 0.066 82.56 24 0.415 5.581 195.7 0.168 45.507

4 380 0.05 88.37 41 0.379 9.535 235.3 0.122 54.721

5 400 0.02 93.02 66 0.224 15.35 268.1 0.094 62.337

6 408 0.014 94.88 85 0.234 19.77 295.8 0.075 68.784

7 414 0.012 96.28 111 0.327 25.81 319.7 0.062 74.349

8 419 0.009 97.44 165 0.179 38.37 340.7 0.052 79.23

9 423 0.007 98.37 201 0.169 46.74 359.4 0.045 83.574

10 426 0.007 99.07 242 0.12 56.28 376.2 0.039 87.479

11 429 0.002 99.77 275 0.119 63.95 391.4 0.034 91.023

12 430 0 100 312 0.183 72.56 405.3 0.031 94.263

13 430 0 100 382 0.112 88.84 418.1 0.028 97.242

14 430 0 100 430 0 100 430 0 100

...Table 2(c) (Contd.)

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0

100

200

300

400

500

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Site cluster(s)

Sp

ecie

s b

ein

g s

aved


Fig. 1: Species – Area Curves Based on Table 2

Selection of sites for conservation has been discussed under reserve design, reserve placement, and reserve selection. According to Lombard et. al. (1995) these methods of nature reserve placement could be grouped into the following four categories: 1. po,population modeling (Gilpin 1991), 2. the ap analysis (Scott et al. 1993), 3. scoring methods (Faith 1992), and 4. the iterative reserve selection algorithms (Nicholls & Margules 1993). Pressey, an et al. (1993) describe the aa advantages of iterative reserve selection algorithms. However, Underhill (1994) shows, with the example, that these algorithms might yield suboptimal solutions. Lombard et al. (1995) have also recognized that “the heuristic algorithm has do not necessarily select the minimal area required to capture all species”. They also guessed that linear pro the gramming methods might be more proficient in doing so. Since it is a matter of saving more number of species s and hence leaving more options, for posterity, it is stressed on testing all possible combinations.

It is possible, from Table 2, to compute the percentage of species being saved by saving 1, 2, 3, ..., 14 cluster(s) of sites when the combinations giving maximum and minimum number of species are being chosen as well as the average number of species being saved when all possible combinations are considered. These percentages are given in Table 3. These tables (Table 2 & 3) give the complete range of options that by saving how many clusters of the site(s) (how much area) how much percentage of species can be saved. Table 3 also gives beta diversity between previously and currently selected combinations. Beta diversity is species turn-over. It is noticeable in Table 3 that in case of proper combinations of clusters represented by maximum, the beta diversity is decreasing gradually. In the case of average also it is decreasing gradually. In the case of minimum, it is fluctuating at some stages even though, by and large, it has a decreasing trend. Figure 2 shows these trends in the behavior of beta diversity. The clues from the behavior of beta diversity might help in reducing the computation time for getting proper combinations of sites/clusters. It is also clear from Figure 1 that in case of proper combinations, the curve rises with a gradual decrease in slope.

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00.10.20.30.40.50.60.70.80.9

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Site cluster(s)

Bet

a di

vers

ity


Fig. 2: Trends in Behaviour of Beta Diversity Based on Table 3

The species-area relationship depends on how organisms of different kinds are distributed spatially. A number of researchers have strived to find uses of this relationship. These include 1. Inferring biological processes like disturbance (Lawrey 1991), competition (Leps 1990) and division of niche space. 2. Defining the minimal area of a community and delineating types of communities (Colinvaux 1993). 3. Use in island biogeography (Williamson 1988) and design of nature reserves (Bierregaard et al. 1992). 4. Estimating the biodiversity of a larger region by extrapolation (Grassle & Maciolek 1992). Some others had been interested in finding out the functional form of species-area relationship and their theoretical justification (Williamson 1981). There are debates and criticisms attached to such studies. The debate over the value of z in the standard species-area relationship S = cAz and its biological meaning makes an interesting reading (Sugihara 1981). Crawley (1986) criticized the erroneous ideas attached with the concept of minimal area and illustrated the expected shapes of species-area curves under a variety of spatial distribution of species. Similarly, a well-designed experiment to tear apart the effect of “grain, extent, and a number of samples” by Palmer & White (1994) gives much insight into the species-area relationship. Although here the main theme of this paper is the maximization of a number of species being saved and not the species-area relationship itself, yet the species-area relationship issue comes in. From this kind of data set, the number of possible species-area curves would be equal to the product of binomial coefficients. The curve represented by the maximum would be one of them and would be the top-most one. Similarly, the curve represented by minimum would also be one of them and would be the bottom-most one (Figure 1). Rest of the curves would be in between and all the curves will converge at two points. For in situ conservation purpose, one will be interested in curve represented by maximum only. In principle, one can be as bad in his/her selection as the curve represented by minimum, but it would hardly ever happen because at least one will be tempted to select sites with number of species arranged in decreasing order and the species-area curve resulting from this selection scheme will not be the one represented by minimum one. For estimating a total number of species present in a particular region based on the species-area curve by extrapolation, the curve represented by average is considered to give a good estimate. However,

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for in situ conservation purpose, this curve will be meaningless because a deterministic event of selecting a definite combination of the site(s) would happen in the process of decision making and the number of species being saved will be quite more than the average value. Finding out a combination of sites giving a maximum number of species being saved appears to be of much practical use in situ conservation but very difficult to arrive at especially when there are a large number of sites to be taken at a time. Greedy method, which has been used in earlier reserve selection algorithms, is efficient in handling large data sets. However, since greedy methods do not necessarily yield optimal solutions, it seems worthwhile putting in some research effort in the following two areas: 1. Develop a shortcut method to answer this question even for a large number of sites. Altogether a different logic needs to be used unlike the simple logic used in the above approaches. Though the approach of testing all possible combinations is foolproof, yet it is not practicable in cases of a large number of sites. The approach of pooling similar sites into clusters of similar sites and testing all possible combinations may not be desirable on certain grounds (like why to pool more similar sites etc). The greedy method is smart and fast enough even for a large number of sites but still, it is not foolproof as shown by Underhill (1994). The examples of more patchy distribution of species, where the greedy method is more likely to fail, are easy to visualize. Therefore, there is still scope to look for novel approaches to solve this problem. This is very important because just by choosing the right combinations we will be saving more number of species and hence leaving more options for our future generations though setting aside the same amount of area for conservation. The possible solutions might come from bit level programming and clues from the behavior of beta diversity. 2. Increase the computation speed of computers so as to do this job in less time even using testall.c. Clearly, the second approach poses the challenge before computer scientists.

The method discussed above could be used in decision making about the selection of sites/areas/regions for in situ conservation at any level/scale (individual, village, block, district, state, national or international). This way it would be possible to maximize the number of species being saved at all spatial scales. The sites/regions which have very few species exclusive to them could be set aside for non-conservation purposes provided that those species are rehabilitated elsewhere. However, rehabilitating elsewhere should not mean to ignore the demand of striving to conserve more variation especially in the life-supporting species of the locality/regions/states etc. The sites selected for conservation at various levels of spatial scales could be nested. In adopting this approach, however, there will be a crisis if the conservation sites selected at a lower level of spatial scale will not fit to maximize the number of species being saved when a higher level of spatial scale is considered. Then owners (individuals/communities/states etc) will have to be co-operative then only the number of species being saved can be maximized at the higher level even though sacrificing the maximization of a number of species being saved at a lower level of spatial scale for certain regions. If all the owners conserve all the species they own then also there will be no problem. This approach could also be used in ex situ conservation for maximization of a number of accessions conserved/maintained at various ex-situ conservation centers, gene banks, field gene banks, and cryo-preservation centers.

REFERENCES

[1] Bierregaard, R.O., Lovjoy, T.E., Kapos, V., Augusto dos Santos, A., & Hutchings, R.W. (1992). The biological dynamics of tropical rainforest fragments. BioScience, 42, 859-866.

[2] Colinvaux, P. (1993). Ecology 2d ed. New York: Wiley.

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[3] Crawley, M.J. (1986). The structure of Plant Communities. In Plant Ecology (Michael J. Crawley, ed.) pp. 20. Oxford: Blackwell Scientific Publications.

[4] Faith, D.P. (1992). Conservation evaluation and phylogenetic diversity. Biol. Conserv., 61, 1–10.[5] Gilpin, M.E. (1991). The genetic effective size of a metapopulation. Biological Journal of the

Linnean society, 42, 165–175.[6] Grassle, J., & Maciolek, N. (1992). Deep-sea species richness: regional and local diversity estimates

from quantitative bottom samples. American Naturalist, 139, 313–341. [7] Higgs, A.J. (1981). Island biogeography and nature reserve design. Journal of Biogeography, 8,

117–124. [8] Kershaw, K.A., & Looney, J.H.H. (1985). Quantitative and dynamic plant ecology. 3d ed. London:

Arnold. [9] Lawrey, J.D. (1991). The species-area curve as an index of disturbance in saxicolous lichen

communities. Bryologist, 94, 377–382. [10] Leps, J. (1990). Can underlying mechanisms be deduced from observed patterns? In Spatial

processes in plant communities (F. Krahulec, A.D.Q. Agnew, & J.H. Willems, eds.) pp. 1–11. Prague: Academia.

[11] Lombard, A.T., Nicholls, A.O. & August, P.V. (1995). Where should nature reserve be located in South Africa? A snake’s perspective. Conservation Biology, 9(2), 363-372.

[12] Nicholls, A.O., & Margules, C.R. (1993). An upgraded reserve selection algorithm. Biol. Conserv., 64, 165–169.

[13] Palmer, M.W., & White, P.S. (1994). Scale dependence and the species-area relationship. The American Naturalist, 144(5), 717–740.

[14] Pressey, R.L., Humphries, C.J., Margules, C.R., Vane-Wright, R.I., & Williams, P.H. (1993). Beyond opportunism: Key principles for systematic reserve selection. Trends in Ecology and Evolution, 8, 124–128.

[15] Scott, J.M., Davis, F.W., Csuti, B., Noss, R., Butterfield, B., Groves, C., Anderson, H., Caicco, S., D’Erchia, F., Edwards, T.C., Ulliman, J., & Wright, R.G. (1993). Gap analysis: A geographic approach to protection of biological diversity. Wildlife Monographs, 123, 1–41.

[16] Singh, S.N. (1996). Ecogeographical Surveying for in-situ Conservation of wild relatives of Cultivated Plants in Uttara Kannada District of Karnata State, India, Ph.D. Thesis. IISc. Bangalore. Text of the thesis is available on internet.

[17] Sugihara, G. (1981). S=cAz, z=1/4: a reply to Connor and McCoy. American Naturalist, 117, 790–793.

[18] Thomas, J.W., Forsman, E.D., Lint, J.B., Meslow, E.C., Noon, B.R. & Verner, J. (1990). A conservation strategy for the Northern Spotted Owl. Report of the interagency scientific committee to address the conservation of the Northern Spotted owl. U.S. Fish and wildlife Service, Portland, Oregon.

[19] Underhill, L.G. (1994). Optimal and suboptimal reserve selection algorithhms. Biol. Conserv., 70, 85–87.

[20] Williamson, M. (1981). Island populations. Oxford: Oxford University Press. [21] Williamson, M. (1988). Relationship of species number to area, distance and other variables. In

Analytical biogeography (A.A. Myres & P.S. Giller, eds.) pp. 91–115. New York: Chapman & Hall.

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Geospatial Scrutiny of Soil Samples Collected Nearby National Mineral Development Corporation, Nagarnar, District Bastar, Chhattisgarh, India

P. Smriti Rao1, Tarence Thomas1, Ashish David2, and Ashima Thomas3

1 Department of Soil Science and Agricultural Chemistry, Sam Higginbottom University of Agriculture,

Technology, and Sciences–211007 Allahabad, U.P., India2 Department of Soil Water and Land Conservation,

Sam Higginbottom University of Agriculture, Technology and Sciences–211007 Allahabad, U.P., India

3 Naini Agricultural Institute, Sam Higginbottom University of Agriculture, Technology and Sciences–211007 Allahabad, U.P., India

ABSTRACT

Mapping of soil properties is an important operation as it plays an important role in the knowledge about soil properties and how it can be used sustainably. The study was carried out in a Bastar district, Chhattisgarh state, India in order to map out some soil characteristics and assess their variability within the area. Samples were collected from the 4 sampling sites, Kesloor and Raikot (NH-16), Adawal and Nagarnar (NH-43) in Jagdalpur. From each site, 6 samples of soils (with three replications) from 20m, 60m and 500m (control site) distance from the edge of national highway at two soil depths, 0-20 cm, and 20-40 cm were collected respectively. The soil samples were air-dried, crushed and passed through a 2 mm sieve before analyzing it for pH, EC, Organic carbon, Iron, Copper and Lead were calculated. After the normalization of data, classical statistics were used to describe the soil properties and geo-statistical analysis was used to illustrate the spatial variability of the soil properties by using kriging interpolation techniques in a GIS environment. Results showed that the coefficient of variance for all the variables was 2.33 to 2.42 at depth 0-20cm and 2.34 to 2.41 at depth 20-40 cm. The geostatistical analysis was done by Ordinary kriging.

Keywords: Geostatistics, the Coefficient of Variance, Ordinary Kriging

INTRODUCTION

The soil is a dynamic natural body which develops as a result of pedogenic natural processes during and after weathering of rocks. It consists of mineral and organic constituents, processing definite chemical, physical, mineralogical and biological properties having a variable depth over the surface of the earth and providing a medium for plant growth (Biswas & Mukherjee, 1994). The soil is a heterogeneous, diverse and dynamic system and its properties change in time and space continuously (Rogerio, Ana,& de Quirijn, 2006). Heterogeneity may occur at a large scale (region) or at small scale (community), even in the same type of soil or in the same community (Du Feng, XuXuexuan, & Shan, 2008). Soil which is a natural resource has

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variability inherent to how the soil formation factors interact within the landscape. However, variability can occur also as a result of cultivation, land use and erosion. Salviano (1996) reported spatial variability in soil attributes as a result of land degradation due to erosion. Spatial variability of soil properties has been long known to exist and has to be taken into account every time field sampling is performed and investigation of its temporal and spatial changes is essential.

Geographical information system (GIS) technologies have great potentials in the field of soil and have opened newer possibilities for improving soil statistic system as it offers accelerated, repetitive, spatial and temporal synoptic view. It also provides a cost-effective and accurate alternative to understanding landscape dynamics. GIS is a potential tool for handling voluminous data and has the capability to support spatial statistical analysis, thus there is a great scope to improve the accuracy of soil survey through the application of GIS technologies. Therefore, assessing spatial variability distribution on nutrients in relation to site characteristics including climate, land use, landscape position and other variables is critical for predicting rates of ecosystem processes (Schimel, Kittel, & Parton, 1991), understanding how ecosystem work (Townsend, Vitousek, & Trumbare, 1995) and assessing the effects of future land use change on nutrients (Kosmas, Gerontidis, & Marathianou, 2000).

Out of the 118 elements in nature about 80 are metals, most of which are found only in trace amounts in the biosphere and in biological materials. There are at least some twenty metals like elements which give rise to well organize toxic effects in man and his ecological associates. Metals having a density of more than 6mg/m3 and atomic weight more than iron are called has heavy metals. Some metals and material and metalloids such as Zinc (Zn), copper (Cu), manganese (Mn), Nickel (Ni), cobalt (Co), chromium(Cr) molybdenum (Mb), and iron (Fe) are essential are essential for living organisms.

The contamination from automobiles are accumulated on the soil surface, move down to deep layers of soil and eventually change the soil physio-chemical properties directly or indirectly metals contamination in soil ranges from less than 1 ppm to as high as 100,000 ppm due to human activity. The roadside environment represents a complex system for heavy metals in term of accumulation transport pathways and removal processes. (Ghosh et al. 2003). Therefore, learning of the extent of heavy metals contamination on highway sites and its inflow into the plant is highly relevant to the management of sustainable urban environmental quality everywhere. Study of the heavy metals contamination on highway sights soil and its accumulation highway side plant is highly relevant in India because of high urban development associated with an exponential rise in the number of vehicles on the highways having no effective pollution control standards.

Out of 4 study areas, 2 are situated near the National mineral development corporation and 2 villages in a different direction from it. The influence of the development of NMDC on the soil physicochemical characteristics is the primary objective of the study.


Study AreA

The study was carried out in Bastar district, Chattisgarh state, India. It has its headquarters in the town of Jagdalpur. Jagdalpur has a monsoon type of hot tropical climate. Summers

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Geospatial Scrutiny of Soil Samples Collected Nearby National Mineral Development Corporation 211

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last from March to May and are hot, with the average maximum for May reaching 38.1 °C (100.6 °F). The weather cools off somewhat for the monsoon season from June to September, which features very heavy rainfall. Winters are warm and dry. Its average rainfall is 1324.3 mm. Its average temperature in summer is 33.15°C, and in winter is 20.73°C. Samples were collected from the 4 sampling sites, Kesloor and Raikot (NH-16), Adawal and Nagarnar (NH-43) in Jagdalpur. From each site, 6 samples of soils (with three replications) from 20m, 60m and 500m (control site) distance from the edge of national highway at two soil depths, 0-20 cm, and 20-40 cm were collected. The soil samples were transferred in to air tight polythene bags and will be brought to the PG laboratory of Deptt. Of Soil Science and Agricultural Chemistry, SHUATS, Allahabad.

Fig.1: Map of the Study Area of Bastar District, Chhattisgarh, India

Showing the Sample Locations

Soil AnAlySiS

The soil samples were air-dried, crushed and passed through a 2 mm sieve. Soil samples were analyzed for soil pH in both water and 0.01 M potassium chloride solution (1:1) using glass electrode pHmeter (McLean, 1982). EC was determined by using Digital Electrical conductivity method. Soil organic carbon was estimated by Walkley and Black method. Soil Iron, Copper and Lead was analyzed by Wet digestion method, taking Aqua regia (1:3 HNO3: HCl) for digestion and finding the results through AAS (Perkin Elmer A Analyst).

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STATISTICAL ANALYSIS

Statistical analysis for the work was done in two stages. Firstly, the distribution of data was described using conventional statistics such as mean, median, minimum, maximum, standard deviation (SD), skewness and kurtosisin order to recognize how data is distributed and each soil characteristics were investigated using descriptive statistics. Secondly, the geo-statistical analysis was performed using the kriging interpolation technique within the spatial analyst extension module in ArcGis 10.2 software package to determine the spatial dependency and spatial variability of soil properties. Kriging method is a statistical estimator that gives statistical weight to each observation so their linear structures have been unbiased and have minimum estimation variance (Kumke, Schoonderwaldt, & Kienel, 2005). This estimator has a high application due to minimizing of error variance with unbiased estimation (Pohlmann,1993). The experimental variogram model was constructed using the Kriging method, with data obtained from the research area. The spatial transformation was performed to determine the most appropriate model to use with the parameters of the generated maps.

The ordinary Kriging formula is as follows: (Isaaks & Srivastava, 1989; ESRİ, 2003).

where Z(Si) is the measured value at the location (ith), λi is the unknown weight for the measured value at the location (ith) and S0 is the estimation location. The unknown weight (λp) depends on the distance to the location of the prediction and the spatial relationships among the measured values.

The statistical model estimates the unmeasured values using known values. A small difference occurs between the true value Z(S0) and the predicted value, Σ_iZ(Si). Therefore, the statistical

prediction is minimized using the following formula:

The Kriging interpolation technique is made possible by transferring data into the GIS environment. In this way, the analysis in areas that have no data can be conducted. The following criteria were used to evaluate the model: the average error (ME) must be close to 0 and the square root of the estimated error of the mean standardized (RMSS) must be close to 1 (Johnston, Hoef, Krivoruchko, &Lucas, 2001). While implementing the models, the anisotropy effect was surveyed.


Soil mapping and survey is an important activity because it plays a key role in the assessment of soil properties and its use in agriculture, irrigation, and other land use. This study was carried out to assessthe spatial variability of some physical and chemical soil properties so as to determine their current situations in the study area, therefore the results can be presented as follows:

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DESCRIPTIVE STATISTICS

The summary of the descriptive statistics of soil parameters as shown in Table 1 suggest that they were all normally distributed. The coefficient of variance for all the variables was 2.33 to 2.42 at depth 0-20cm and 2.34 to 2.41 at depth 20-40 cm. All the variables show low variation according to Coefficient of variance according to the guidelines provided by Warrick, 1998 for the variability of soil properties. The lowest coefficient of variation could be as a result of the uniform conditions in the area such as little changes in slope and its direction leading to a uniformity of soil in the area(Afshar, Salehi, Mohammadi, & Mehnatkesh, 2009; Cambardella et al., 1994; Kamare, 2010). Most of the soil properties were highly positively skew at both depths i.e. pH and EC at Raikot, Kesllor, and Chokawada while %OC, Fe, Cu, and Pb were both symmetrical. These variations in chemical properties are mostly related to the different soil management practices carried out in the study area, the vehicle transportation, environmental pollution, parent material on which the soil is formed, role of the depth of ground water and irrigation water quality (Abel, Kutywayo,Chagwesha, & Chidoko, 2014; Al-Atab, 2008; Al-Juboory, Alaqid, & Al-Issawi, 1990).

Table 1: Descriptive Statistics within the Field Grid for the Variables at Depth 0–20 cm

Village Raikot (Distance fromNH at 20 m, 60 m, and 500m)

Statistics PH EC %OC Fe Cu Pb

Mean 6.30667 .42367 .89667 1585.00000 6.13333 6.33333

Median 6.25000 .40300 .91000 2088.00000 7.50000 5.00000

SD .162583 .043822 .080829 907.837541 3.647373 3.028751

Skewness 1.378 1.650 -.722 -1.728 -1.449 1.597

Village Kesloor (Distance fromNH at 20 m, 60 m, and 500m)

Mean 6.62333 .48233 .88333 2174.00000 12.93333 16.73333

Median 6.60000 .45700 .88000 2176.00000 13.50000 15.30000

SD .040415 .145662 .015275 37.040518 4.675824 2.569695

Skewness 1.732 .759 .935 -.242 -.537 1.729

Village Adawal (Distance fromNH at 20 m, 60 m, and 500m)

Mean 7.06000 .56033 1.07667 2287.33333 15.40000 25.33333

Median 7.07000 .55900 1.06000 2355.00000 13.50000 20.80000

SD .017321 .089007 .037859 135.795189 4.838388 10.279267

Skewness -1.732 .067 1.597 -1.686 1.495 1.599

Village Chokawada (Distance fromNH at 20 m, 60 m, and 500m)

Mean 6.87667 .46133 .92333 2279.66667 17.20000 41.43333

Median 6.96000 .46800 .92000 2280.00000 16.90000 26.90000

SD .153080 .042395 .025166 .577350 2.662705 25.868385

Skewness -1.724 -.690 .586 -1.732 .501 1.730

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Table 2: Descriptive Statistics within the Field Grid for the Variables at Depth 20–40 cm

Village Raikot (Distance fromNH at 20 m, 60 m, and 500m)

Statistics pH EC %OC Fe Cu Pb

Mean 6.23333 .44033 .74333 1057.00000 4.03333 1.16667

Median 6.21000 .42700 .75000 1367.00000 2.90000 .00000

SD .116762 .050342 .050332 621.027375 3.635015 2.020726

Skewness .863 1.108 -.586 -1.687 1.267 1.732

Village Kesloor (Distance fromNH at 20 m, 60 m, and 500m)

Mean 6.61333 .51867 .74000 2081.33333 11.83333 11.76667

Median 6.60000 .46200 .74000 2091.00000 11.10000 10.10000

SD .023094 .161630 .020000 21.221059 4.247744 5.012318

Skewness 1.732 1.384 .000 -1.625 .754 1.331

Village Adawal (Distance fromNH at 20 m, 60 m, and 500m)

Mean 7.00000 .63933 .90667 2060.33333 12.53333 16.26667

Median 7.06000 .64100 .92000 2087.00000 10.70000 15.90000

SD .112694 .047522 .032146 151.767366 3.980368 1.582193

Skewness -1.717 -.158 -1.545 -.766 1.633 .987

Village Chokawada (Distance fromNH at 20 m, 60 m, and 500m)

Mean 6.76667 .48933 .73333 2305.33333 30.46667 33.26667

Median 6.71000 .50200 .72000 2354.00000 26.40000 35.40000

SD .191398 .055103 .041633 84.293139 17.948909 7.433259

Skewness 1.216 -.980 1.293 -1.732 .967 -1.185

Table 3: Coefficient of Variation within the Field Grid at Depth 0-20 cm and 20-40 cm

Area Cov (Depth 0-20 cm) Cov (Depth 20-40cm)

R 20 m 2.41 2.41

R 60 m 2.42 2.43

R 500 m 2.37 2.38

K 20 m 2.39 2.39

K 60 m 2.4 2.41

K 500 m 2.41 2.41

A 20 m 2.36 2.39

A 40 m 2.4 2.39

A 500 m 2.4 2.4

C 20 m 2.33 2.36

C 60 m 2.38 2.39

C 500 m 2.39 2.34

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geoStAtiSticAl AnAlySiS

The possible spatial structure of the different soil properties was identified by calculating the semivariograms and the best model that describes these spatial structures was identified. These results are shown in Tables 4 and 5 for the two depths. The model with the best fit was applied to each parameter, the Exponential and Gaussian model was the best fit for all parameters. The nugget effect (Co), the sill (Co + C) and the range of influence for each of the parameters were noted. The spatial dependencies (Nugget/Sill ratio) were found to be related to the degree of autocorrelation between the sampling points and expressed in percentages. Table 4 shows the soil properties where variable characteristics as generated from semivariogram model. C0 is the nugget variance; C is the structural variance, and C0 + C represents the degree of spatial variability, which affected by both structural and stochastic factors (Fig. 2,3). The higher ratio indicates that the spatial variability is primarily caused by stochastic factors, such as fertilization, farming measures, cropping systems, and other human activities. The lower ratio suggests that structural factors, such as climate, parent material, topography, soil properties, and other natural factors, play a significant role in spatial variability. The spatial dependent variable was classified as strongly spatially dependent if the ratio was <25, moderately spatially dependent if the ratio is between 25 and 75% while it is classified as weak spatial dependent if it >75% (Gambardella et al., 1994; Clark, 1979; Erşahin, 1999; Robertson, 1987; Trangmar, Yost, & Uehara, 1985).

For the 0–20 cm depth, Ph, EC,%OC, Fe, Cu, and Pb had a strong spatial dependence with a ratio of 0.28, 0, 0.99, 0, 0, and 0% respectively (Table 4).

At the lower depth i.e. 20–40 cm pH, EC, %OC, Fe, Cu and Pb had a strong spatial dependence (0.214, 0, 0.99, 0.475, 0 and 0.121%) (Table 4).

Table 4: Geostatistical Parameters of the Fitted Semivariogram Models for Soil Properties and Cross-validation Statistics at 0–20 cm Depth and 20–40 cm Depth Respectively

Variable Nugget(C0)

Sill (C0+C)

Range (A)

Nugget/Sill

Model Spatial Class

RMS ME

pH 0.0069 0.241 0.3534 0.28 Exponential strong 0.152 0.038

EC 0 0.0109 0.1386 0 Exponential strong 0.099 0.0389

OC 3.81 3.825 0.1701 0.99 Exponential strong 0.058 0.255

Fe 0 230769.6 0.138 0 Exponential strong 515.79 0.057

Cu 0 22.40 0.138 0 Exponential strong 4.046 0.049

Pb 181.26 0 0.353 0 Exponential Strong 15.22 0.044

Variable Nugget(C0) Sill (C0+C) Range (A)

Nugget/Sill

Model Spatial Class

RMS ME

pH 0.030 0.11 0.252 0.215 Exponential Strong 0.207 0.016

EC 0 0.016 0.132 0 Exponential Strong 0.121 0.060

OC 1.30 1.313 0.16 0.99 Gaussian Strong 0.080 0.120

Fe 211036.30 444118.8 0.353 0.475 Exponential Strong 535.15 0.027

Cu 0 194.33 0.132 0 Exponential strong 12.69 0.057

Pb 34.64 286.12 0.353 0.121 Exponential strong 7.85 0.016

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(a) (b) (c)

(d) (e) (f)Fig. 2: Semivariogram Parameters of the Best Fitted theoretical Model to Predict Soil Properties

at 0-20 cm Depth, a. pH b. EC c. %OC d. Fe e. Cu and f. Pb

(a) (b) (c)

(d) (e) (f)Fig. 3: Semivariogram parameters of the best fitted theoretical model to predict soil properties

at 20-40 cm depth, a. pH b. EC c. %OC d. Fe e. Cu and f. Pb

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The value of nugget effect for EC, Fe, and Cu were the lowest at both depths which suggest that the random variance of variables is low in the study area, this implies that near and away samples have similar and different values respectively. Therefore, nugget effects that are small and close to zero indicate a spatial continuity between the neighboring points, this can be backed with the results of Vieira and Paz Gonzalez (2003) and Mohammad Zamani, Auubi, and Khormali (2007)

The presence of a sill on the variogram indicates second-order stationarity, i.e. the variance and covariance exist. (Geoff Bohling, 2005).

(a) (b)

Fig. 4: (a) pH at 0-20cm and (b) pH at 20-40cm

(a) (b)

Fig. 5: (a) EC at 0-20cm and (b) EC at 20-40cm

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(a) (b)

Fig. 6: (a) OC at 0-20cm and (b) OC at 20-40cm

(a) (b)

Fig. 7: (a) Fe at 0-20cm and (b) Fe at 20-40cm

(a) (b)

Fig. 8: (a) Cu at 0-20cm and (b) Cu at 20-40cm

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(a) (b)

Fig. 9: (a) Pb at 0-20cm and (b) Pb at 20-40cm

CONCLUSION

Assessing spatial variability and mapping of soil properties is an important pre-requisite for soil and crop management and also useful in identifying land degradation spots. The production of soil nutrient maps is the first step in precision agriculture because these maps will measure spatial variability and provide the basis for controlling it. It would also help in reducing the number of inputs been added to the soil in form of supplements so as not to over burden the soil which can lead to pollution thereby degrading the land. The results show that the spatial distribution and spatial dependence level of soil properties can be different even within the same local government area. It also demonstrates the effectiveness of GIS techniques in the interpretation of data. These results can be used to make recommendations of best management practices within the locality and also to improve the livelihood of smallholder farmers.

REFERENCES

[1] Abel, C., Kutywayo, D., Chagwesha, T.M., & Chidoko, P. (2014).Assessment of irrigation water quality and selected soil parameters at Mutema irrigation scheme, Zimbabwe.Journal of Water Resources and Protection, 6, 132–140.

[2] Afshar, H., Salehi, M. H., Mohammadi, J., & Mehnatkesh, A.(2009). Spatial variability of soil properties and irrigated wheat yield in quantitative suitability map, a case study: Share e Kian Area, Chaharmahaleva Bakhtiari province.Journal of Water and Soil, 23, 161–172.

[3] Al-Atab, S.M.S. (2008). Variations of soil properties and classification in some area of Basrah Governorate (PhD thesis). College of Agriculture, University of Basrah,Basrah.

[4] Al-Juboory, S.R., Alaqid, W.K. Alaqidi, & Al-Issawi, S.M. (1990).Effect of soil management practices on Chemical and physical properties of a soil from great Mussayb Project.Iraqi journal of Agriculture Sciences, 21, 107–116.

[5] Biswas, T.D., & Mukherjee, S. K. (1994). Textbook of soil science.New Delhi: Tata McGraw-Hill Publishing Company Limited.

[6] Black, C.A. (1965). Methods of soil analysis. Agronomy No. 9,Part 2. Madison, WI: American Society of Agronomy.

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[7] Brown, G., Newman, A.C.D., Rayner, J.H., Weir, A.H. (1978).The structure and chemistry of soil clay minerals In D.J.Greenland & M. H. B. Hayes (Eds.), The chemistry of soilconstituents(pp. 29178). New York, NY: Wiley.

[8] Buol, S.W., Hole, F.D., McCracken, R.J., & Southard, R.J. (1997).Soil genesis and classification (4th ed., p. 527). Ames: IowaState University Press.

[9] Cambardella, C.A., & Karlen, D. L. (1999). Spatial analysis ofsoil fertility parameters. Precision Agriculture, 1, 5–14.

[10] Cambardella, C. A., Moorman, T. B., Parkin, T. B., Karlen, D. L.,Novak, J. M., Turco, R. F., & Konopka, A. E. (1994). Field-scalevariability of soil properties in central Iowa soils. Soil Science Society of America Journal, 58, 1501–1511. http://dx.doi.org/10.2136/sssaj1994.03615995005800050033x

[11] [12] Clark, I. (1979). Practical geostatistics (p. 129). London: AppliedScience Publishers.Du Feng, L.

Z., XuXuexuan, Z. X., & Shan, L. (2008). Spatialheterogeneity of soil nutrients and aboveground biomassin abandoned old-fields of Loess Hilly region in NorthernShaanxi, China. Acta Ecologica Sinica, 28, 13–22.

[13] Erşahin, S. (1999). Alluvial soil in a field, some physical andchemical properties of the spatial variability of thedetermination. SU Journal of the Faculty of Agriculture, 13,34–41.

[14] ESRİ. (2003). The principles of geostatistical analysis (p. 54).Federal Fertilizer Department. Federal Ministry of Agriculture andRural development. (2012). Fertilizer use and management practices for crops in Nigeria (4th ed., pp. 40–41).

[15] Isaaks, E.H., & Srivastava, R. M. (1989). An introduction to appliedgeostatistics. New York, NY: Oxford University Press.

[16] Jackson M.L. (1958). Soil chemical analysis (p. 125). Englewood cliffs, NJ: Prentice Hall.[17] Johnston, K., Hoef, M., Krivoruchko, K., & Lucas, N. (2001). UsingArcGIS geostatistical analyst.

New York, NY: ESRI.[18] Kamare, R. (2010). Spatial variability of production, density andcanopy cover percentage of

Nitrariaschoberi L. in MeyghanPlaya of Arak by using geostatistical methods (M.Sc Thesis, 76pp). Tarbiat Modares University, Tehran.

[19] Kosmas, C., Gerontidis, St., & Marathianou, M. (2000). Theeffect of land use change on soils and vegetation overvarious lithological formations on Lesvos (Greece).Cantena, 40, 51–68.

[20] Kumke, T., Schoonderwaldt, A., & Kienel, U. (2005). Spatialvariability of sedimentological properties in a largeSiberian lake. Aquatic Sciences, 67, 86–96.http://dx.doi.org/10.1007/s00027-004-0734-5

[21] López-Granados, F., Jurado-Expósito, M., Atenciano, S., García-Ferrer, A., Sánchez de la Orden, M. S., & García-Torres, L.(2002). Spatial variability of agricultural soil parameters in southern Spain. Plant and Soil, 246, 97–105.http://dx.doi.org/10.1023/A:1021568415380

[22] McLean, E. O. (1982). Soil pH and lime requirement. In A. L.Page (Ed.), Methods of soil analysis part 2. Madison, WI:ASA-SSSA.

[23] Mohammad Zamani, S., Auubi, S., & Khormali, F. (2007).Investigation of spatial variability soil properties andwheat production in some of farmland of sorkhkalateh ofGolestan province. Journal of Science and TechnicalAgriculture and Natural Recourses, 11, 79–91.

[24] Pohlmann, H. (1993). Geostatistical modelling ofenvironmental data. CATENA, 20, 191–198. http://dx.doi.org/10.1016/0341-8162(93)90038-Q

[25] Robertson, G.P. (1987). Geostatistics in ecology: Interpolatingwith known variance. Ecology, 68, 744–748.http://dx.doi.org/10.2307/1938482

[26] Rogerio, C., Ana, L.B.H., & de Quirijn, J.L. (2006). Spatiotemporalvariability of soil water tension in a tropical soilin Brazil. Geoderma, 133, 231–243.

[27] Salviano, A. A.C. (1996). Variabilidade de atributos de solo ecrotalária júncea em solo degradado do município dePiracicaba–SP (p. 91). Piracicaba: Tese (Doutorado),Escola Superior de Agricultura Luiz de Queiroz,Universidade de São Paulo.

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ISBN: 978-93-88237-24-6

Terminal Heat Stress Effects on Morpho-Physiological Characters of Indian Mustard (Brassica juncea L.) Genotypes

Suman Yadav*

Department of Plant Breeding and Genetics, Dr. RPCAU, Pusa–848125, Bihar, IndiaE-mail: *[email protected]

ABSTRACT

Effect of heat stress was visualized at the terminal stage on 17 different growth traits and yield in 20 promising mustard (Brassica juncea L.) genotypes grown in a randomized complete block design with three replications in two environments viz. timely E1(16th November) and late sown E2 (13th December). Of the 45 days prior to physiological maturity, crop under E2 was exposed to the higher mean daily temperature differential of 0.9–5.60C for 28 days. Significant genotypic differences existed for all growth traits at two sowing dates, and environment had a profound impact not only on morphological traits but also on the reproductive behavior and seed filling which in turn was associated with yield reduction under terminal heat stress. Three genotypesRH0555, Pusa mustard25, and Pusa mahak registered yield reduction less than 20%in the present investigation. The highest reduction in seed yield and its components ranged from 77% for biological yield /plant to 81% for seed yield/plant. Three terminal high-temperature tolerant genotypes as indicated by their low HIS for seed yield were RH0555, Pusa mustard 25 and Pusa Mahak. Genotypes RAURD-212, RAURD14-18, RAURD 14-11, TPM-1, NPJ-197 having tolerance to a high temperature for multiple characters were identified for utilization in the breeding programme.

Keywords: High Temperature; Brassica juncea L., Seed Yield, Physiological Characters, Heat Susceptibility Index

INTRODUCTION

High temperature affects rapeseed-mustard not only at seedling but also at the pod filling stage. Due to multiple cropping systems, the sowing of Indian mustard gets delayed to the end of October to mid November due to late harvesting. Growth and development of late sown crop are more adversely affected by severe winter, foggy and frost conditions during the vegetative stage and high temperature during pod and seed filling stages. Heat stress during the post-anthesis (seed filling) negatively influences the movement of photosynthetic products to the developing sinks and inhibits the synthetic processes, thus lowering seed weight and seed yield and may alter seed quality (Bhullar and Jenner, 1985). The problem of heat stress at the flowering stage is observed in all the major mustard growing countries including China, Australia, Canada, and Europe, but heat stress at seedling and terminal stage is a unique problem to India (Salisbury and Gurung, 2011). There are many studies related to thermotolerance in oilseed brassicas at the flowering, but very little information is available

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in understanding the heat tolerance at seedling and terminal stages. Further, heat tolerance in crop plants is developmentally regulated and is known to be stage-specific phenomena, meaning tolerance at one stage of plant development may not be correlated with tolerance at the other developmental stages (Wahid et al. 2007). Therefore, the present study was undertaken with the objectives to assess the genetic variability for terminal thermotolerance in Indian mustard genotypes and to characterize the selected thermotolerant genotypes in order to discover reliable criteria for thermotolerance at terminal high-temperature stress.

mAteriAlS And methodS

The experimental materials for the present investigation comprised 20 genotypes of Indian mustard grown in a randomized complete block design with three replications during Rabi season (November-April ) 2017–2018 at the Research Farm TCA Dholi, DRPCAU, Pusa, Bihar (25. 50 N, 85. 40E and 52. 12 m MSL) in Loam soil (8. 4 pH), India. The experiment was conducted at 2 dates of sowing, viz., November 16(E1) and December 13 (E2) 2017. There were 4 rows of 5-m length for each genotype in a block. The row spacing was 45 cm and plant spacing with-in-a row was maintained at 15 cm thinning. A fertilizer dose of 40: 40:40 kg/ha (N: P2 O5: K2O) was applied at the time of sowing and 40 kg/ha N was top dressed 3-4 days after first irrigation. Standard agronomic practices were followed to raise a good crop. Observations were also recorded on 5 randomly taken plants/ replication/genotype on plant height, primary branches/plant, secondary branches/plant, length of primary mother axis, siliqua on primary branches, siliqua on secondary branches, siliqua on primary mother axis, siliqua length, seeds/siliqua, biological yield/plant, harvest index, days to first flower, vegetative phase duration, physiological maturity, post-anthesis phase duration, days to 50% flowering and test weight.

Analysis of variance using replication mean values for multiple randomized complete block design using indostat software was carried out to study the genotype, environment, and genotype x environment interaction. Heat stress effect was computed as percent change in the mean of a character under E2 over that of under E1. Heat susceptibility index (Fischer and Maurer 1978) was computed for all the characters /genotypes to characterize thermo tolerance.

RESULT

temperAture regime

The temperature under two environments differed considerably during different phonological stages of the crop. The genotypes under E1 were exposed to high temperature (27.2 ± 0.390C) as compared to those under E2 (22.4 ± 0.430C) during the seedling stage. Thereafter, temperature sharply declined from 27.20 C to 20.90 C from seedling emergence to 100%flowering and again increased to 310 C till physiological maturity under E1 (weather data 2017-18 growing period of the crop). However, under E2 it declined from 22.40C to 15.970C until initiation of flowering and thereafter gradually increased to 32.20 C till physiological maturity. After initiation of flowering, the crop under E2experienced higher maximum temperature by 3-40C than that of under E1. The mean maximum temperature was about 2.20C higher under E2 than E1 during 100 %flowering and physiological maturity, the phase of active and rapid dry matter accumulation needs. Analysis of the pattern of daily variation in minimum, maximum and mean temperature during 45 days prior to physiological maturity revealed that crop under E2

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was exposed to the higher mean daily temperature differential of 0.9–5.60C for 28 days while the mean daily temperature was higher by 0.1–3.90C for 25 days under E1. The crop under E1 was exposed to relatively cooler temperature until 30 days prior to physiological maturity.

AnAlySiS of vAriAnce

Analysis of variance revealed significant genotypic differences for all the characters studied except siliqua on primary mother axis and physiological maturity. Environment effects were highly significant for all the morpho-physiological characters.

EFFECTS

Heat (high temperature) stress during the terminal stage had substantial effects on all the characters studied, varying with the genotypes and characters. Plant height was reduced considerably under E2, ranging from 3% (RAURD-212)-25% (RGN-13) with a mean decline of 13.7% ( Table 1). Genotypes had fewer branches/plant except for the genotypes RAURD-78, DRMR 15-9, RGN-368, and Pusa mahak, which showed marginally higher primary branches/plant under heat stress (an increase of % 21-39). High temperature decreased siliquae on primary branches by up to 42% in the genotype Varuna followed by 40% in the both genotypes RAURD-212 and NPJ-201, siliqua on secondary branches by up to 45% in the genotype RAURD 212 and siliqua on primary mother axis by up to 20.11% in the genotype RAURD-78 while genotype Urvashi having the minimum reduction (Table 2). Seeds/siliqua recorded maximum reduction up to 20% in the genotype RAURD-212 and genotype DRMR 15-9 and Pusa Mahak showing no increase in seeds. The genotypes with < 10% reduction in number of seeds/ siliqua were RGN-13, DRMR4001,DRMR15-9,RGN-368,RAURD14-18,Rajendra sufalam, PRE2013-19, RH0555, TPM-1, Varuna and Urvashi. The highest decrease due to heat stress was observed for seed yield/plant, ranging from 12-81% (Table 3). The genotypes having the least reduction in seed yield under stress were RH0555 (12%), Pusa Mahak (15%) and Pusa mustard 25 (17%). Harvest index also decreased by 1% under E2 with the highest reduction of 55% for the genotype DRMR 4001. Biological yield per plant exhibited maximum reduction up to 77% in the genotype RAURD-78 and least reduction 10% in the genotype NPJ-197. The 1000-seed weight under heat stress showed a considerable decrease. The mean decline in seed test weight was 18.2% (Table 4) and genotype RGN-13, RAURD14-11, NPJ-201 and Varuna showed slightly improved seed weight under stress. Heat susceptibility index (HIS), a measure of tolerance of genotype/character to heat stress, also showed substantial variation. Large HSI values suggest greater sensitivity to the stress (Winter et al. 1988). The HIS estimates differed among the genotypes as well characters. Although, meanHIS was close to unity for most of the characters except a number of primary and secondary branches and harvest index but varied widely. Higher HIS values were observed for harvest index, a number of primary branches/plant as well as a number of secondary branches/plant, siliqua on primary mother axis, length of primary mother axis, siliqua length and seeds/siliqua (Table 2) suggesting that these characters were more prone to high temperature. The characters showing HIS values close to unity or below were plant height, siliquae on primary branches as well as on secondary branches/plant,biological yield/plant, seed yield per plant, days to first flower open, vegetative phase duration, physiological maturity, post-anthesis phase duration days to 50% flowering and 1000-seed weight indicating their relative tolerance to terminal high temperature. Genotypes showing low HSI for seed yield/plant, RH0555, (0.26), Pusa mustard 25(0.36) and

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Pusa Mahak (0.33). Genotypes RAURD-212 (plant height, days to first flower open, days to 50% flowering), TPM-1 (plant height, length of primary mother axis) RAURD 14-11(length of primary mother axis,siliqua length), RGN-368 (siliqua on primary and secondary branches, biological yield/plant, days to 50% flowering), KMR (E) 16-1 (siliqua on primary branches, biological yield/plant), NPJ-197 (siliqua on primary branches, biological yield/plant, harvest index, test weight), Pusa mustard 25( siliqua on primary branches,biological yield/plant), Pusa Mahak (siliqua on primary branches), RAURD 14-18 (siliqua on secondary branches), Varuna (siliqua length, harvest index, days to 50% flowering), Urvashi (biological yield/plant, days to first flower open, days to 50% flowering, test weight), RAURD-78 (harvest index), NPJ -201(days to 50% flowering) had tolerance to multiple cha

DISCUSSION

Terminal heat stress caused a substantial reduction in all the characters revealed that a difference 3-40C in the mean high temperature after initiation of flowering (35-40 DAS) significantly reduced the growth of the Indian mustard. The highest reduction in seed yield and its components ranged from 77% for biological yield/plant to 81% for seed yield. The findings of the present study corroborated earlier reports where reduction up to 76% in seed yield/plant, 20.9% in harvest index and 42.6% siliquae on the main branch were reported (Lallu and Dixit 2008). The reduction siliquae on main shoot and seeds/siliqua could be due to floral sterility as temperature > 270 Chas been reported to induce floral sterility in canola (Morrison and Stewart 2002) as well as development of flowers in to seedless parthenocarpic fruits &/or flower abortion on the stem due to high temperature (Young et al. 2004). Considerable reduction in seed yield under E2 in the present study could be due to less production of dry matter. The results were in agreement with those of Subrahmanyam and Rathore (1994) who observed that high temperature during reproductive stage significantly inhibited the import of photosynthates by both upper and lower pads of terminal raceme and thereby reduced sink strength. The present investigation also revealed that the top four terminal high-temperature tolerant genotypes as indicated by their low HIS for seed yield were RH0555 (0.26), Pusa mustard 25 (0.36), Pusa Mahak (0.33) RGN-368 (0.88) and TPM-1(0.81). Their tolerance was coupled with tolerance to the high temperature of plant height, primary branches/plant, 1000-seed weight, seeds/siliqua, siliquaeon primary branches. Tall genotypes with more primary branches/plant, medium old seeds, and high chlorophyll content were suggested to be ideal for late sown conditions (Kumarand Srivastava 2003). In this context, genotypes having tolerance to high temperature (lowHIS) for plant height, siliqua on primary as well as secondary branches/plant, biological yield/plant, harvest index, test weight like RAURD-212, RAID 14-11,RGN-368, KMR (E) 16-1, NPJ-197, Pusa mustard25, Pusa Mahak, RAURD 14-18 and RAURD-78 should be utilized in the breeding programme to improve seed yield under terminal heat stress.

ACKNOWLEDGMENTS

We express our sincere thanks to different All India Coordinated Research Project-Rapeseed and Mustard centres namely, DRMR, Bharatpur, Rajasthan, CCSHAU, Hisar, Haryana, BARC, Trombay, Maharastra, GBPUAT, Pantnagar, Uttarakhand, CSAUAT, Kanpur, U. P, IARI, New Delhi, ARS, RAU, Sriganganagar, Rajasthan for providing genotypes of rapeseed and mustard and encouragement due to which this research project was completed.

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REFERENCES

[1] Anonymous, 2009: Directorate of Oilseeds Development, Hyderabad. http://www.dacnet.nic.in/oilseeds/gapy (February 6, 2009).

[2] Arnon, D. I., 1949: Copper enzymes in isolated Chloroplast polyphenol oxidase in Beta Vulgaris. Physiol. 24, 1–45

[3] FAO, 2009: FAOSTAT-2007. http://www. fao.org. (June 3, 2009).[4] Fischer, R. A., and R. Maurer, 1978: Drought resistance in spring wheat cultivars: I. Grain yield

responses. Aust. J. of Agric. Res. 29, 897–907.[5] Hall, A. E., 1992: Breeding for heat tolerance. Plant Breeding Rev. 10, 129–168.[6] Kar, M., B. B. Patro, C. R. Sahoo and B. Hota, 2005: Traits related to drought resistance in cotton

hybrids. Indian J. Plant Physio. 10 (4N.S.), 377–380.[7] Kumar, N. and S. Srivastava, 2003: Plant ideotype of Indian mustard (Brassica juncea) for latesown

conditions. Indian J. Genet. 63, 355.[8] Kumar, Satyanshu, A. K. Singh, M. Kumar, S. K. Yadav, J.S. Chauhan and P.R. Kumar,

2003:Standardization of near infrared reflectance spectroscopy (NIRS) for determination ofseed oil and protein contents in rapeseed-mustard. J. Food Sci. Technol. 40, 306–309.

[9] Lallu and R. K. Dixit, 2008: High temperature effect at terminal stage in mustard genotypes. Indian J. Plant Physiol. 13 (2 NS), 151–158.

[10] Morrison, M. J. and D. W. Stewart, 2002: Heat stress during flowering in summer Brassica. CropScience 42: 797–803.

[11] Nuttall, W. F., A. P. Moulin and L. J. Townley-Smith, 1992: Yield response of canola to nitrogen, phosphorus, precipitation and temperature. Agron. J. 84, 765–768.

[12] Rao, G. U., A. Jain and K.T. Shivanna, 1992: Effect of high temperature stress on Bassica pollen: viability, germination and ability to set fruits and seeds. Ann. Bot. (London) 69, 193–198.

[13] Subrahamanyam, D. and V. S. Rathore, 1994: Effect of high temperature on CO2 assimilationand partitioning in Indian mustard. Journal Agronomy and Crop Science, 172, 188–193.

[14] Winter, S.R., J. T. Musick and K. B. Porter, 1988: Evaluation of screening techniques forbreeding drought resistance winter wheat. Crop Sci. 28, 512–516.

[15] Young, L.W., R.W. Wilen and P.C. Bonham-Smith (2004): High temperature stress of Brassicanapus during flowering reduces micro-and megagametophyte fertility, induces fruitabortion and disrupts seed production. Journal of Experimental Botany 55, 485–495.

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Speciation of Klebsiella Isolates from Various Clinical Samples and their Antibiotic Susceptibility Pattern

Talluri Rameshwari K.R.*1, Deepa S.1, Anuradha K.2† and Sumana K.3

1Division of Microbiology and Department of Water and Health, Faculty of Life Sciences, JSS Academy of Higher

Education and Research, Sri Shivarathreeshwara Nagar, Mysuru, Karnataka – 570 015

2Department of Microbiology, Mysore Medical College and Research Institute, K R Hospital, Irwin Road,

Mysuru, Karnataka – 570 001E-mail: *[email protected], †[email protected]

ABSTRACT

Klebsiella pneumoniae has become a very important cause of nosocomial infections, even replacing Escherichia coli in some centers. It causes pneumonia, UTI, other pyogenic infections, septicemia and rarely diarrhea. Biochemically variant strains are common. Many strains carry plasmids determining multiple drug resistance, so antibiotic sensitivity should invariably be done. Speciation and characterization of Klebsiella from various clinical samples and their antibiotic susceptibility pattern. The aim of this study is to isolate and sub-speciate K. pneumoniae strains and to know the antibiotic susceptibility pattern of various subspecies. 75 nonrepetitive K. pneumoniae isolates from various clinical samples, both from outpatient and inpatient were processed. They were sub speciated by using standard biochemical reactions. Antibiotic susceptibility testing was performed by Kirby Bauer disc diffusion test. Klebsiella has been associated with different types of infections and one of the most important aspects of Klebsiella is the emergence of multi-drug resistant strains particularly those involved in nosocomial diseases. Out of 75 Klebsiella 28 were isolated from exudate, 25 were isolated from sputum, 20 from blood, 2 from urine. Of the 75 isolates common subspecies was Klebsiella pneumoniae pneumonia 55(73.33%) followed by Klebsiella oxytoca 10(13.33%), Klebsiella pneumoniae ozaenae 5(6.66%), Klebsiella pneumoniae rhinoscleromatis 5(6.66%).In the present study, the antibiotics susceptibility pattern was analyzed for various antibiotics. We could notice that majority of the isolates were showing sensitivity to Ciprofloxacin (CIP) 60(80%), followed by Gentamycin (G) 49(65.33%), Cotrimoxazole (COT) 23(30.66%). The maximum resistance was found to Ampicillin (AMP) 75(100%), Amoxyclav(AMC) 75 (100%), Cefotaxime (CTX) 75(100%). Multi-Drug resistance was noted in the 25(33.33%) of the total isolates. ESBL was noted in the 14(18.66%) of total isolates. The high antibiotic resistance pattern in Klebsiella pneumoniae poses a great threat to the community.

Keywords: Samples of Exudates, Sputum, Blood, Urine

INTRODUCTION

In 1883 Friedlander isolated a capsulated bacillus from the lungs of a patient who died of pneumonia. This was named after him as Friedlander’s bacillus. Later on, this organism was

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given the generic name of Klebsiella, which is ubiquitously present and reported worldwide (A. S. Sikarwar et al., 2011). They are gram-negative bacilli which are capsulated. Klebsiella is widely distributed in nature, occurring both as commensals in the intestines of humans and as saprophytes in soil and water (Radhika B et al., 2014). The genus Klebsiella belongs to Kingdom-Bacteria, Phylum-Proteobacteria, Class-Gammaproteobacteria, Order-Enterbacterials, Family-Enterobacteriaceae, and Genus-Klebsiella. (A. S. Sikarwar et al., 2011) The Genus-Klebsiella was named by Revision in 1885 to honor the German microbiologist Edwin Klebs (1834– 1913) (Radhika B et al., 2014).

The genus Klebsiella comprises of two species, Klebsiella pneumoniae, Klebsiella oxytoca, In the Klebsiella pneumonia there is three sub-species Klebsiella pneumoniae pneumonia, Klebsiella pneumoniae ozone, and Klebsiella pneumoniae rhinoscleroma are which are usually identified and differentiated according to their biochemical reactions (Claudia Vuotto et al., 2014). Klebsiella pneumonia is a Proteobacteria, included in Enterobacteriaceae. It is a Gram-negative bacterium, Cylindrical in shape and rod-like. It is of about 2 microns in length and 0.5 microns in diameter (A. S. Sikarwar et al., 2011). Its cells have a thick coat of slime or extracellular polysaccharide which is called a “capsule”. The thickness of the capsule is approximately 160 nm in Klebsiella pneumonia (A. S. Sikarwar et al., 2011). The virulence factors playing an important role in the severity of Klebsiella infections are capsular polysaccharides, type 1 and type 3 pili, factors involved in aggregative adhesions and Siderophores. Capsules, whose subunits can be classified into 80 serological types, are essential to the virulence of Klebsiella (Malvika Singh et al., 2015).

The capsular material, forming fibrillous structures that cover the bacterial surface protects the bacterium from phagocytosis, on the one hand, and prevents the killing of the bacteria by bactericidal serum factors, on the other. Type 1 and type 3 pili (known as fimbriae), are non-flagellar, filamentous fimbrial adhesins, often detected on the bacterial surface, that consist of polymeric globular protein subunits (pilin). On the basis of their ability to agglutinate erythrocytes and depending on whether the reaction is inhibited by D-mannose, these adhesins are designated as mannose-sensitive (MSHA) or mannose-resistant hemagglutinins (MRHA), respectively (Malvika Singh et al., 2015). Strains of Klebsiella are responsible for a wide variety of diseases in humans. These bacteria have become important pathogens in nosocomial infections which have been well documented (A. S. Sikarwar et al., 2011).

Klebsiella pneumoniae has been reported as a prominent cause of infections in individuals with indwelling urinary catheters (Malvika Singh et al., 2015). A high incidence of Klebsiella pneumoniae in UTIs (from 6% to 17%) was reported in various studies carried out in specific groups of patients at risk, e.g., patients with diabetes mellitus or with neuropathic bladders (A. S. Sikarwar et al., 2011, Ahmad M. et al., 1999). The bacteremia associated with intravascular catheters, an epidemiological study on bloodstream infections revealed that Staphylococcus aureus was the most common species (30%), followed by Klebsiella pneumoniae (10%) (Ahmad M. et al., 1999).

The discovery of antimicrobial agents had a major impact on the rate of survival from infections. Bacterial infections caused by Klebsiella spps., are often treated with beta-lactam antibiotics or alternatively with aminoglycosides or fluoroquinolones but the prevalence of strains resistant to

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this selected antibiotics have been reported. However, the changing patterns of antimicrobial resistance caused a demand for new antimicrobial agents. Antimicrobial resistance is known to have a very serious impact in clinical and public health. (Claudia Vuotto et al., 2014, Ahmad M. et al., 1999). Recently, the World Health Organization warned the community that multidrug-resistant bacteria are emerging worldwide, which is a big challenge to healthcare. Multidrug-resistant bacteria cause serious nosocomial and community-acquired infections that are hard to eradicate by using available antibiotics (A. S. Sikarwar et al., 2011, Claudia Vuotto et al., 2014). Moreover, extensive use of broad-spectrum antibiotics in hospitalized patients has led to both increased carriage of Klebsiella and the development of multidrug-resistant strains that produce extended-spectrum beta-lactamase (ESBL) (Radhika B et al., 2014). Epidemic and endemic nosocomial infections caused by Klebsiella species are leading causes of morbidity and mortality (A. S. Sikarwar et al., 2011, Radhika B et al., 2014).

Klebsiella is a notorious organism which can cause mild to severe life-threatening infections both in the community and hospital settings and responsible for high mortality and morbidity and is often multidrug resistant, resistant even to carbapenems. Hence we have taken up this study to isolate and speciate Klebsiella from various clinical samples and to assess their antibiotic resistance patterns (Ahmad M. et al., 1999).

METHODS AND MATERIAL

prepArAtion And SAmple collection of the Study

A total of 75 samples of Exudate, Sputum, Blood, and Urine which were collected from the patients with the symptoms of fever, vomiting, wounded patient, nausea etc., and sent to the Microbiology laboratory which yielded the growth of Klebsiella species were included in the study for further speciation.

Inclusion Criteria: Klebsiella species isolated from various clinical samples.

Exclusion Criteria: Klebsiella species from feces were excluded.

SamPle ProceSSing

Samples received at Microbiology laboratory, MMCRI were checked for proper labeling and were taken for culture and sensitivity.

The processing of clinical samples was done as follows:

• Microscopy

• Culture and Identification of Klebsiella

• Speciation of Klebsiella

• Antibiotic susceptibility pattern

• Detection of ESBL

• Detection of Multi-Drug Resistance

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BActeriAl iSolAtion

1. Microscopy: Direct Smear Examination: Gram stain was performed for all the samples of Exudate, Sputum. Where blood and urine which was observed with the wet mount. Gram’s stain was done to note for the presence of inflammatory cells, epithelial cells and bacteria for exudates and sputum samples. Gram-negative bacilli which are short and stout morphologically resembling Klebsiella species were included in the study.

2. Culture - Various samples were inoculated on Mac-Conkey agar and Blood agar as per the standard methods. The samples were aseptically inoculated onto the culture plates, incubated aerobically at 37o C for 24 hours. Pink colored lactose fermenting mucoid colonies on Mac-Conkey and corresponding growth on Blood agar were taken, from which a gram stain was done to identify the organisms resembling Klebsiella (GNB). Preliminary identification was done by gram stain of the colony as per follows.

3. Oxidase test: Oxidase test is used to determine the presence of bacterial cytochrome oxidase enzyme using the oxidization of the substrate “tetramethyl-p-phenylenediamine dihydrochloride” to indophenol a dark purple colored end product. A positive test (presence of oxidase) indicated by the development of a dark purple color. No color development indicates a negative test and the absence of the enzyme.

4. Catalase test: Nutrient agar slants were inoculated with the organisms and were incubated at 30oC for 24 Hrs. After incubation, the tubes were flooded with one ml of three percent hydrogen peroxide and observed for the production of gas bubbles. The occurrence of gas bubbles confirms catalase activity.

5. Motility Test: It was done to help differentiate species of bacteria that are motile from non-motile. Hanging Drop preparation was done where Klebsiella is a non-motile organism.

BIOCHEMICAL TESTS

For the speciation of Klebsiella, the following Biochemical tests were done:

• Indole test

• Methyl red test

• Voges prouskers test

• Citrate test

• Triple sugar iron test

• Urease test

• Sugar fermentation test-(glucose, lactose, mannitol, maltose, malonate)

• Lysine decarboxylase test

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ANTIBIOTIC SUSCEPTIBILITY TEST

Antibiotic Susceptibility Testing for the obtained isolates was done by Kirby-Bauer Disc diffusion method as per CLSI guidelines (Claudia Vuotto et al., 2014). Organisms were grown in BHI broth and inoculated to peptone water and incubated for 3 to 4 hours and the inoculated on Mueller Hinton agar plates by sterile swabs and then antibiotic discs were placed on media and pressed gently followed by overnight incubation for 18-24 hours at 37ºC. The results were interpreted according to the standards and recommendations of CLSI guidelines.

The antibiotic discs were procured from Himedia & were used. On the basis of resistance to an antibiotic, strains were categorized into three groups i.e. susceptible(S), resistant (R) and moderately susceptible (MS).

Sl. No. Drug Disc Potency (Microgram)

1. Ampicillin (AMP) 25 mcg /disc

2. Amoxyclav (AMC) 30mcg/disc

3. Gentamycin (G) 30mcg/disc

4. Cefotoxime (CTX) 30mcg/disc

5. Ciprofloxacin (CIP) 30mcg/disc

6. Cotrimoxazole (COT) 25mcg/disc

7. Ceftazidime(CAZ) 30mcg/disc

8. Ceftazidime+Clavulinate(CAC) 30/10mcg/disc

eSBl detection

ESBL detection was carried out according to the Clinical and Laboratory Standards Institute (CLSI) criteria (Radhika B et al., 2014). ESBL is detected by placing the Ceftazidime (30mcg) and Ceftazidime+Clavulanate (30/10mcg) with 15mm distance between the disks. Zone of inhibition of Ceftazidime+Clavulanate if 7mm more compared to Ceftazidime, has considered as positive.

multi-drug reSiStAnce

The isolate which is resistance for more than three categories of antibiotics were considered to be multidrug resistance organism. Klebsiella which shows resistance to more than three antibiotic categories was considered as multidrug resistance.

reSultS

The present study was conducted in the Department of Microbiology, Mysore Medical College and Research Institute, K R Hospital, Mysore. This study was undertaken over a period from February 2016 to April 2016. A total of 75 clinical samples yielding Klebsiella isolates were included in the study.

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Out of 75 Klebsiella pneumonia, 28 (37.33%) were isolated from exudate, 25 (33.33%) were isolated from sputum, 20(26.66%) from blood samples & 2(2.66%) from urine.

Out of 75 isolates studied, maximum number of cases 23(30.66%) were seen in the age group of more than 60 yrs, minimum number of cases were seen in 40-49 yrs 15(20.83%), 50-59 and 30-39 yrs (13.88%), less than one year 12(16.0%) and less number of cases were seen in the age group 20-29 yrs 12(16.0%), followed by 1-9yrs 4(5.33%)and 10-19 yrs 2(2.66%).

Table 1: Distribution of Klebsiella Species with Respect to Age

Ages (Yrs) N (%)

<1yr 12(16.0%)

1-9 yrs 4(5.33%)

10-19yrs 2(2.66%)

20-29yrs 12(16.0%)

30-39yrs 7(9.33%)

40-49yrs 9(12.0%)

50-59yrs 6(8.0%)

>60yrs 23(30.66%)

Total 75(100%)

Fig. 1: Distribution of Klebsiella Species with Respect to Age

The study group comprised of males 40(53.33%) and females 35(46.66%). The maximum number of cases is observed in the male and minimum numbers of cases were seen in a female.

Table II: Distribution of Klebsiella Species in Relation to Sex (Gender)

Sex N (%)

Male 40(53.33%)

Female 35(46.66%)

Total 75(100%)

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Fig. 2: Distribution of Klebsiella Species in Relation to Sex (Gender)

Out of 75 cases studied, 56(74.66%) were inpatients and 19(25.33%) outpatients. The maximum number of cases is observed in the inpatients and a minimum number of cases was seen in outpatients.

Table III: Inpatient and Outpatient Details

Type N (%)

Inpatient 56(74.66%)

Outpatient 19(25.33%)

Total 75(100%)

Fig. 3: Inpatient and Outpatient Details

Among 75 Klebsiella isolated, Pus samples constitute the maximum number of specimens accounting for Exudate 28(37.33%) followed by blood samples 20(26.66%), urine samples 2(2.66%), and sputum 25(33.33%) respectively.

Table IV: Distribution of Klebsiella Species from Various Clinical Samples

Specimens N (%)

Exudate 28(37.33%)

Blood 20(26.66%)

Urine 2(2.66%)

Sputum 25(33.33%)

Total 75(100%)

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Fig. 4: Distribution of Klebsiella Species from Various Clinical Samples

Out of 75 samples of Klebsiella, the Klebsiella pneumoniae is 55(73.33%), Klebsiella ozaenae is 5(6.66%), Klebsiella rhinoscleromatis is 5(6.66%), and Klebsiella oxytoca is 10(13.33%). The maximum number is Klebsiella pneumoniae is 40(53.33%), and the minimum number is Klebsiella rhinoscleromatis is 5(6.66%) and Klebsiella ozaenae is 5(6.66%).

Table V: Percentage of Different Species of Klebsiella Among the Clinical Isolates

Species N (%)

Klebsiella pneumonia 55(73.33%)

Klebsiella pneumonia ozaenae 5(6.66%)

Klebsiella pneumonia rhinoscleromatis 5(6.66%)

Klebsiella oxytoca 10(13.33%)

Total 75(100%)

Fig. 5: Percentage of Different Species of Klebsiella Among the Clinical Isolates

Out of the total 75 isolates, the isolates were showing sensitivity to Ciprofloxacin (CIP) 60(80%), followed by Gentamycin (G) 49(65.33%), Cotrimoxazole (COT) 23(30.66%). The maximum resistance was found to Ampicillin (AMP) 75(100%), Amoxyclav (AMC) 75(100%), Cefotaxime (CTX) 75(100%).

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Table VI: Antibiotic Sensitivity of Klebsiella Isolates

Sl. No Drug Disc Potency

(microgram)

Inhibition Zone Diameter to Nearest Whole Millimeter

Sensitive (mm)

Moderate Sensitive (mm)

Resistance (mm)

1 Ampicillin (AMP) 25mcg /disc 0 0 75(100%)

2 Amoxyclav (AMC) 30mcg/disc 0 0 75(100%)

3 Gentamycin (G) 30mcg/disc 49(65.33%) 4(5.33%) 22(29.33%)

4 Cefotoxime (CTX) 30mcg/disc 0 0 75(100%)

5 Ciprofloxacin (CIP) 30mcg/disc 60(80%) 5(6.66%) 10(13.33%)

6 Cotrimoxazole (COT) 25mcg/disc 23(30.66%) 2(2.66%) 50(66.6%)

7 Ceftazidime (CAZ) 30mcg/disc 0 0 75(100%)

8 Ceftazidime+Clavulinate (CAC) 30/10mcg/disc 0 0 75(100%)

ESBL Detection: Out of 75 samples, the 14(18.66%) of ESBL is positive and 61(81.33%) is negative.

Table VII: The Distribution Percentage of ESBL Production Among the Klebsiella Isolates

ESBL

Positive N%

Negative N%

Klebsiella 14 61

Percentage 18.66% 81.33%

Total 75 (100%) 75(100%)

Fig. 6: The Distribution Percentage of ESBL Production Among the Klebsiella Isolates

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Multi-Drug Resistant: Total number of MDR producers among isolated organism. Out of 75 samples, the 25(33.33%) of MDR is positive and 50(66.66%) is negative.

Table VIII: The Distribution of a Multi Drug Resistance Among Klebsiella Isolates

MDR

Positive N%

Negative N%

Klebsiella 25 50

Percentage 33.33% 66.66%

Total 75 (100%) 75(100%)

Fig. 7: The Distribution of a Multi Drug Resistance Among Klebsiella Isolates

DISCUSSION

In the present study, we have isolated 75 non repetitive isolates of Klebsiella from various clinical samples and have characterized them to subspecies and we have analyzed their antibiotic susceptibility pattern. A total of 75 clinical isolates of Klebsiella were included in our study of which 28 (37.33%) were isolated from Exudates, 25 (33.33%) were isolated from sputum, 20(26.66%) from blood samples & 2(2.66%) from urine. In our study Klebsiella was maximum seen in the age group above 60 years i.e 23(30.66%), followed by < 1 year age group i.e. 12(16.0%) and 20-29years 12(16.0%). The study group comprised of males 40(53.33%) and females 35(46.66%) & male to female ratio is 1:1.1.

Radhika B et al., from Visakhapatnam, 2014 have reported Klebsiella out of 100 isolates, 45% were isolated from sputum, 21% were isolated from pus, 20% from urine & 3% from blood samples. In another study by J. H. Darrell et al., who have isolated Klebsiella from a total of 60 samples, 23 (38.33%) urine samples, 14(18.66%) sputum samples, 7 (11.66%) exudates

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samples. In a similar study of the Iroha I. Romanus et al., (2011), non-repetitive clinical samples, out of 390 samples which include 126(32.30%) urine sample, 68(17.43%) high vaginal swab, 90(23.07%) wound swab and 106(27.17%) sputum samples were collected. All these studies have depicted Klebsiella tube commonly isolated from sputum & urine samples, in contrast, we have isolated Klebsiella more from exudates followed by sputum. As we have studied a few samples and also Klebsiella is a known hospital pathogen, we might have isolated more of the isolates from pus & exudates. It is a known fact that Klebsiella is a cause of hospital-acquired pneumonia from which our sputum samples have yielded them. Nosocomial bloodstream infections are common once the patient is admitted to the hospital for more than 72 hours. We have got 20% of Klebsiella isolates causing blood stream infections. In the present study, we have evaluated a test panel comprising 6 biochemical tests on 75 strains of Klebsiella and sub speciation was been done. Among them, Klebsiella Pneumonia pneumonia that is 55(73.33%), Klebsiella pneumonia ozaenae 5(6.66%), Klebsiella pneumonia rhinoscleromatis 5(6.66%) & Klebsiella oxytoca 10(13.33%).

In the study of Radhika B et al., from Visakhapatnam, (2014) who have reported Klebsiella pneumonia 45(45%), Klebsiella pneumonia ozaenae 17(17%), and Klebsiella pneumonia rhinoscleromatis 8(8%) which is in comparison with our study. Another similar study by D. O Acheampong et al., (2008), Klebsiella pneumoniae was the commonest (74.4%), followed by Klebsiella oxytoca (24.1%). There were 2 Klebsiella rhinoscleromatis isolates (1%) and Klebsiella ozaenae had only one isolate (0.5%). Most of the studies have isolated Klebsiella pnemoniae subspecies pneumoniae as the common isolate in concordance with our study. Klebsiella pnemoniae subspecies pneumonia is well known in causing various pathogenic mechanisms to establish infections in humans, also it is present as commensal in the gut & a circulating nosocomial pathogen in the hospital environment. As we have got samples from inpatients, we have got more percentage of this subspecies to cause infection.

In the present study, the antibiotics susceptibility pattern was analyzed for various antibiotics. We could notice that majority of the isolates were showing sensitivity to Ciprofloxacin (CIP) 60(80%), followed by Gentamycin (G) 49(65.33%), Cotrimoxazole (COT) 23(30.66%). The maximum resistance was found to Ampicillin (AMP) 75(100%), Amoxyclav (AMC) 75(100%), Cefotaxime (CTX) 75(100%). Multi-Drug resistance was noted in the 25(33.33%) of the total isolates. ESBL was noted in the 14(18.66%) of the total isolate (A. S. Sikarwar et al., 2011). In the study of Jain & Mondal (2008), of the 100 clinical isolates of Klebsiella spp. 58 were ESBL positive after the confirmatory test. In the study of A. S. Sikarwar et al., (2011) the contained strains which were resistant to semisynthetic penicillins, ampicillin, carbenicillin (76-100%) and to co-trimoxazole (76%). Radhika B et al., from Visakhapatnam, 2014 have reported 100% resistance to ceftazidime, 23.5% resistant to gentamycin, 93.3% resistant to co-trimoxizole and 80% resistant to amoxyclav (Malvika Singh et al., 2015). In the study of the Amita Jain & Rajesh Mondal (2008), they showed that 58 of the 100 isolates tested were ESBL positive.

A study on multi-drug resistant on Klebsiella pneumoniae by Amita Jain & Rajesh Mondal (2008), has described MDR phenotype has resistant to amino glycosides (Genatmycin), Fluoroquinolones (Ciprofloxacin) and Beta-lactams (A, Ac, Ce, AMC) and to Co-trimoxazole. The study done by Vikas Manchanda et al., (2005) have reported, 195 Klebsiella species of which 60% were resistant to Amoxicillin, Gentamycin, Cefotaxime, 54% were MDR. Infection caused by MDR Klebsiella and ESBL producing Klebsiella are more complicated and difficult

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to treat. Patients in the hospital are more prone for Nosocomial infection caused by this MDR Klebsiella.

Usually Klebsiella infections are treated by mono therapy or broad-spectrum antibiotics. Plasmid-mediated drug resistance to broad-spectrum antibiotics is very common among Klebsiella. Being plasmid mediated, this resistance can be transferred horizontally from one bacterium to another. The prevalence of ESBL producing bacteria is an increase in globally and this of major clinical concern. It is an alarming state for us to know about prompt identification isolation drug resistance detection and treatment of the infection caused by Klebsiella. Therefore identifying the organisms with proper antibiotic susceptibility report is very essential before we start the treatment of the patient. So that we can decrease the mortality and morbidity in the patient.

CONCLUSION

Our study has shown that Klebsiella pneumonia is the commonest isolate with a higher percentage of MDR and ESBL. The study depicts that Klebsiella pneumonia is difficult to treat pathogen with Multi antibiotics resistance. Therefore identifying the organisms with proper antibiotic susceptibility report is very essential before we start the treatment of the patient.

ACKNOWLEDGMENT

This study was carried out in Mysore Medical College and Research Institute, K R Hospital Mysuru - 570001, We are equally thankful to the top management and staff of K R Hospital for all their support throughout this work.

REFERENCES

[1] Archana S. Sikarwar and H. V. Batra, Identification of Klebsiella Pneumoniae by Capsular Polysaccharide Polyclonal Antibodies. International Journal of Chemical Engineering and Applications, April 2011 Vol. 2, No. 2. Page No: 210–215

[2] Amita Jain & Rajesh Mondal, Detection of extended spectrum b-lactamase production in clinical isolates of Klebsiella spp. Indian Journal of Medical Research 127, April 2008, Page No: 344–350.

[3] Claudia Vuotto, Francesca Longo, Maria Pia Balice, Gianfranco Donelli and Pietro E. Varaldo, Antibiotic Resistance Related to Biofilm Formation in Klebsiella pneumonia. Journal of Public Health Medical Research 2014 (3). Page No: 743–758.

[4] D. O Acheampong, L. K Boamponsem and P. K Feglo, Occurrence and species distribution of Klebsiella Isolates: A case study at Komfo Anokye teaching hospital (Kath) in Ghana. Advances in Applied Science Research, 2011, 2 (4): Page No: 187–190.

[5] Hansen, D. S., R. Skov, J. V. Benedi, V. Sperling, and H. J.Kolmos. 2002. Klebsiella typing: Pulsed-field gel electrophoresis (PFGE) in comparison with O: K-serotyping. Clin. Microbiol. Infect. 8(7): Page No: 397–404.

[6] Iroha I. Romanus and Oji Anthonia Egwu, Analysis of Antibiotic susceptibility of Klebsiella pneumonia Isolated from different clinical specimen in Egunu State. Canadian Journal of pure and Applied Sciences October 2011 Vol. 5 (3), Page No: 1609–1614.

[7] J. H. Darrell and A. D. F. Hurdle, Identification and clinical significance of Klebsiella species in chest infections. Journal clinical Pathology (1964), Vol. 17. Page No: 617–620.

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[8] Malvika Singh, Barnali Kakati, R.K.Agarwal and Aarti Kotwal, Detection of Klebsiella pneumoniae carbapenemases (KPCs) among ESBL /MBL producing clinical isolates of Klebsiella pneumonia. International Journal of Current Microbiology and Applied Science 2015; 4(4): Page No: 726–73.

[9] Radhika. B, Jyothipadmaja I, Subspeciation and antibacterial susceptibility testing of Klebsiella pneumoniae. Journal of Public Health Medical Research 2014; 2(2): Page No: 39–42.

[10] Vikas Manchanda, N.P. Singh, R. Goyal, A. Kumar & S.S. Thukral* Phenotypic characteristics of clinical isolates of Klebsiella pneumonia & evaluation of available phenotypic techniques for detection of extended spectrum beta-lactamases. Indian J Med Res 122, October 2005, Page No: 330–337

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Bihar Higher Education Challenges

Abha MishraM.J.M. Mahila College Katihar

Bihar was recognized as the god father of education. It was the birth place of two principal universities, Nalanda and Vikramshila. The educational infrastructure and methods of the Bihar education were of a very high quality.

The present condition of Bihar education is very depressing. Presently, Bihar education ranks lowest in the literacy rate among the Indian cities. This is very disturbing. The central government as well as the state government, have taken lots of projects in hand to restore the prevailing condition of the Bihar education.

Studies have been shown that lack of adequate infrastructure, in-complete teachers, most of them with fake degrees and grossly small teaching knowledge. The quality of higher education is an equally serious problem. In this area, the 11th plan recognized three areas for interventions: physical infrastructure, academic reform and ensuring ad adequate faculty.

Education takes a back seat as freebies become the prime motivation of attending school. Irregular session, irrelevant and outdated syllabus, politicization and criminalization of the campus. These things made Bihar pitiful poor state. Bihar has lost its pre-eminent position and higher education is almost stagnant in the status.

The current status of higher education in the state is characterized by low enrollment particularly among girls, low completion rate and poor qualitative as well as quantitative infrastructure. Quality education is for any for Bihar. Bihar neglected higher education, the need to go into the root causes of the problems and to find an effective solution.

If we see the scenario of Primary education of Bihar, 62% Primary student do not complete education, according to this 2015 human resource development ministry education profile of those out of school, 55% children were never enrolled and 25% dropped out of school. There are not enough classrooms, teachers, lowest per student expenditure on elementary education. Bihar spends a lower proportion of its elementary education budget on teacher salaries, training, and inputs than Maharashtra, Andra Pradesh, and Rajasthan.

Reading levels of Bihar government primary schools decline over five years, according to the Annuals status of Education Report-Trends over time report (2006–14).

METHODS

In this study 20 college teachers survey has been taken. These teachers are permanent teachers in the various college of Bihar Universities. Last 10 years they are working as a teacher in Bihar. One question asked about challenges of higher education in Bihar. That was an open-ended question. Their responses have been analyzed.

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RESULTS

98% result shows that teacher’s availability is very less.90% teachers wanted to modification in the syllabus. Accountability for authority has been found as a challenge in 70% of teachers. 75% attendance should necessary for the students said 60% of teachers. 97% teachers wanted to adequate infrastructure.

By spending a lower proportion of the elementary education budget on teachers, Bihar spends more money on other things such as midday meals and providing incentives to attract children to schools and college such as free text books, uniforms.

This whole process can be explained by the theory of motivational cycle. Need or necessity is any lack or deficiency which is felt by the organism to be inimical to his welfare (Chaplin 1973). The need produces a drive, which is a state of tension that motivates the organism to act to reduce the tension. The body returns to a more balanced state. Once the need is satisfied. There are two types of needs physiological and social. In the case of Bihar, the government gives the student meal, fellowships, and different kind of incentives but students could not realize their need. If there is no need realization then they never are motivated.

SUGGESTIONS

1. Higher Education must change and adapt to economic and social needs.

2. Universities must continue their mission to educate, train and carry out research through an approach characterized by ethics, autonomy, responsibility, and anticipation.

3. New teaching, learning approaches that enable, the development of critical and creative thinking should be integrated.

4. Teaching and learning must be more active, connected to real life, and designed with student and their unique qualities in mind.

5. Performance related pay (or incentive pay) for teachers can play an important role in improving the quality of education.

6. Bihar education system should be privatized.

7. If India wants to be a developed country then it should be necessary for our education system should be strengthened.

8. University management should be transparent and accountable both for students and teachers.

CONCLUSION

Much more needs to be done in the state of Bihar in terms of improving infrastructure, investing in more teachers and improving their qualities.

By 2020 India will have the world’s largest working population but India spend Analysis revealed that India is unprepared to educate and train its young population.

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Degradation and Decolourisation of Anaerobically Treated Distillery Effluent in Two-Stage Sequential Treatment by Bacteria and Constructed Wetland

Vineet Kumar1,2*, Gaurav Saxena1, Chhatarpal Singh1 and Ram Chandra1

1Department of Microbiology, Babasaheb Bhimrao Ambedkar (A Central) University, Vidya Vihar, Raebareli Road,

Lucknow, Uttar Pradesh–226025, India2Department of Microbiology, Dr. Shakuntala Misra

National Rehabilitation University, Lucknow, Uttar Pradesh–226017, India


ABSTRACT

Sugarcane molasses-based anaerobically digested distillery effluent is a threat to the environment for its safe disposal due to complexation of several recalcitrant organic and inorganic pollutants. This study deals with the degradation and decolourisation of anaerobically digested distillery effluent in two-stage sequential treatment by bacteria and constructed wetland planted with Phragmites communis. In the first step, the distillery effluent was treated in a bioreactor by previously developed bacterial consortium comprising Klebsiella pneumoniae, Salmonella enterica, Enterobacter aerogenes, and Enterobacter cloaceae resulted in 71% decolorisation of effluent. Further, the bacterial treated distillery effluent was integrated with a constructed wetland to achieved maximum decolorisation (98%) of distillery effluent. Further, HPLC and GC-MS analysis have shown that most of the pollutants detected in untreated distillery effluent were diminished from bacterial and constructed wetland treated anaerobically digested distillery effluent.

Keywords: Phragmites Communis, Recalcitrant Organic Pollutants, GC-MS Analysis, Post-Methanated Distillery Effluent, Constructed Wetland

INTRODUCTION

Sugarcane-molasses based distillery effluent is a threat to the environment for its safe disposal due to the presence of recalcitrant organic compounds and various heavy metals viz. Fe, Cu, Mn, Pb, Zn, Cd, and Ni, along with melanoidins (Chandra et al., 2012; Chandra et al., 2018a). It has also been reported that melanoidins have net negative charges; therefore, various heavy metals (Cu2+, Cr3+, Fe3+, Zn2+, and Pb2+ etc.) bind with melanoidins to form large organo-metallic complex molecules resulted enhances the vulnerability of organo-metallic complex towards its toxicity in the environment. (Migo et al., 1997; Hatano and Yamatsu, 2018). In India, there are more than 397 distilleries producing approximately 3.25 × 1010 liter of alcohol and generating 40.90 × 1015 liters of effluent annually (AIDA, 2016). This reflects the magnitude of the environmental pollution caused by the waste generated from the distillery sector all over India. The conventional aerobic–anaerobic secondary treatment approaches such as

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activated sludge, anaerobic digestion processes have been found ineffective to eliminate the color of distillery effluent due to the recalcitrant nature of melanoidins which contribute the hight total dissolved solid (TDS) and presence of other complex refractory organic pollutants (Chandra et al., 2018b). In addition, the various physicochemical methods such as nanofiltration, flocculation, adsorption, chemical precipitation or coagulation, ozone oxidation, and UV/H2O2 treatment has been reported for removal and decolorisation of distillery effluent (Liang et al., 2009a,b). But, these techniques are not applicable at large scale due to high operation cost, high chemical consumption and generation of huge amount of toxic sludge and other secondary pollutants. In recent year, natural treatment with microbial decolorization process of effluent is drawing the attention of workers world over, because they are an eco-friendly and cost-effective substitute to chemical methods. The growing acceptance of microorganisms for decolorization of distillery effluent is due to facts that some microorganisms have a specific ligninolytic enzymatic system capable of breaking a large number of C=C, C=O and C≡N bonds present in melanoidins (Miyata et al., 2000). But, the decolorization of distillery effluent using pure or mixed microbial culture was achieved only up to a certain extent. Considering the advantages and the disadvantages of different treatment technologies, no single technology can be used for the complete treatment of distillery effluent. Hence, there is a need to establish a comprehensive treatment approach involving sequential treatment technologies. Therefore, integrated biological treatment methods have been practiced by coupling or integrating two or more biological processes for the treatment of complex industrial wastewaters. Two step treatment by using integrated bacteria and constructed wetland (CW) treatment process to be a novel and promising approach for bioremediation of industrial wastewater (Chandra et al., 2012). Hence, this study deals with the two-stage sequential treatment of PMDE by a previously developed bacterial consortium in a bioreactor under shaking conditions followed by a constructed wetland planted with Phragmites communis and characterization of metabolites produced during the bacterial and wetland plant rhizosphere treatment of distillery effluent through gas chromatography-mass spectrometry (GC–MS) analysis.


deScription of the WetlAnd plAnt treAtment SyStem And experimentAl deSign

The pilot scale horizontal subsurface flow-constructed wetland (HSSF-CW) plant treatment system was constructed in the surface area of 14 m2 (20 m length and 7 m width), located at Babasaheb Bhimrao Ambedkar University, Lucknow, Uttar Pradesh; where in 5 × 18 m area; a zig-zag cemented channel was constructed to prevent the seepage. Upstream channel depth and width were kept at 50 and 40 cm, respectively, while the downstream dept and width were kept at 58 and 40 cm, respectively, thereby maintaining a 0.8% slope that promoted hydraulic flow. The HSSF-CW bed was filled with 55 mm diameter pebbles (lower layer), 20 mm coarse gravel (middle layer), and 1-2 mm sand particles layers (upper layer), each layer being 8.0 cm deep, as in the designed according to the Swindell and Jackson (1990) and the EPA design manual (EPA 1998). Young plant of P. communis was collected from wetland area contaminated with distillery effluent and these plants planted in HSSF-CW at a density of 12 plant m-2.

BActeriAl treAtment of pmde At optimized conditionS

The bacterial treatment of distillery effluent was carried out in an open bioreactor containing 350 lit of 10% diluted PMDE with color range 48000 co.pt amended with modified GPM broth. The

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Degradation and Decolourisation of Anaerobically Treated Distillery Effluent in Two-Stage Sequential 243

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bioreactor was inoculated with overnight grown fresh culture of four identified bacterial strains, i.e., Klebsiella pneumoniae, Salmonella enterica, Enterobacter aerogenes, and Enterobacter cloaceae previously isolated from distillery sludge sample in our laboratory to degrade synthetic and natural melanoidins in optimized conditions (Kumar and Chandra, 2018; Chandra et al., 2018a). The cultures were incubated at 180 rpm for 168 h with continuous aeration. The sample was collected at every 24 h interval during incubation and centrifuged at 10,000 ×g for 10 min at 4 °C for measurement of decolorization efficiency.

treAtment of BActeriAl pretreAted diStillery effluent With hSSf-cW

The bacterial treated anaerobically digested distillery effluent was allowed to pass into the planted area of zig-zag shaped HSSF-CW plant treatment system with 50 × 40 cm upstream depth and width and 58 × 40 cm down stream depth and upstream flow rate of 2 L min-1 and a downstream flow rate of 1.5 L min-1. The bacterial treated distillery effluent was circulated through HSSF-CW plant treatment system up to 168 h for utilization and mineralization of biotransformed products by P. communist roots and its rhizospheric microbial communities. The sample was collected at every 24 h interval during incubation (168 h) and centrifuged at 10,000 ×g for 10 min at 4 °C for measurement of decolorization efficiency.

phySico-chemicAl AnAlySiS of the pmde

The physicochemical analysis was carried out for untreated, bacterial treated, as well as HSSF-CW, treated distillery effluent. The physico-chemical analysis covered: color, pH, biological oxygen demand (BOD), chemical oxygen demand (COD), total dissolved solid (TDS), phenol, sulfate, phosphate, and heavy metals. All the analysis was carried out according to Standard Methods for the Examination of Water and Wastewater (APHA, 2012).

detection And chArActerizAtion of vAriouS metABoliteS produced during the degrAdAtion And decolorizAtion of diStillery effluent By gc-mS AnAlySiS

A fraction (150 mL) of untreated, bacterial treated, as well as CW, treated distillery effluent samples were centrifuged at 6500 ×g for 10 min at 4 °C in a microfuge to separate suspended particles and bacterial biomass from control and treated samples, respectively. The organic compounds were extracted from the above samples using the ethyl acetate in solid phase extraction method as reported earlier (Chandra et al. 2017a). The organic solvent phase was obtained from each sample dehydrated over anhydrous Na2SO4 and dried under a stream of nitrogen gas. The dry residues were dissolved in 2.0 mL methanol. The sample in methanol was filtered through 0.22-µm syringe filters and used for further GC–MS analysis (Chandra and Kumar 2017).

cAlculAtion And StAtiSticAl dAtA AnAlySiS

To avoid any experimental errors, each experiment was performed in triplicate. The removal efficiency for different physicochemical parameters was calculated based on the inflow and outflow concentrations according to the formula as given below:Removal efficiency (%) = Cin-Cout/ Cin × 100

where Cin and Cout are the influent and effluent concentrations (mg L-1), respectively.

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The standard deviation (SD) was calculated using Microsoft Excel (ver. 2007, Microsoft®, USA) and results presented as the mean ± SD value. The mean value of various physicochemical parameters of untreated and treated distillery effluent was assessed Student’s ‘t’ test using SPSS software package (version 22.0; SPSS Inc., Chicago, IL, USA).

reSultS And diScuSSion

BActeriAl decolorizAtion of AnAeroBicAlly digeSted diStillery effluent in the BioreActor

A bacterial consortium comprising K. pneumoniae, S. enterica, E. aerogenes, and E. cloaceae was decolorized distillery effluent up to 71% at the optimized condition of nutrient and different parameters after 168 h of incubation. But, after 168 h of incubation, the bacterial consortium was unable to decolorized PMDE higher than 71 %. This might be due to a higher concentration of toxic organic and inorganic compounds present in distillery effluent which inhibit the bacterial growth. During bacterial treatment along with color and other pollution parameter i.e. BOD, COD, TDS, were also reduced after 168 h of incubation (Table 1).

phySico-chemicAl AnAlySiS of AnAeroBicAlly digeSted diStillery effluent

The physico-chemical characteristics of anaerobically digested distillery effluent collected before and after bacterial and HSSF-CW treatment are tabulated in Table 1. The physico-chemical characteristics of untreated PMDE showed the color intensity and concentration of BOD, COD, TDS, phosphate, sulfate, and various heavy metals were found higher. However, in contrary to untreated distillery effluent, the bacterial degraded sample obtained from bioreactor after 168 h incubation showed a reduction of various physic-ochemical parameters as shown in Table 1. This indicated the biodegradation and biotransformation of various organic and inorganic contents by the potential bacterial consortium. Moreover, the HSSF-CW treated effluent sample has also shown a reduction of color, pH, BOD COD, TDS, phosphate, sulfate, and various heavy metals as shown in Table 1. In CW, the organic matter is consumed and reduced by bacteria and other microbes both aerobically and anaerobically. Therefore, all the values of BOD, COD, phenol, sulfate, and heavy metals were reduced after CW plant treatment (Table 1).

Table 1 Physico-chemical Analysis of Anaerobically Digested Distillery Effluent

S.No. Parameters Untreated (Control) Bacterial treated (168 h)

Constructed Wetland Treated (168 h) % Reduction

1. C.I. 48000±210.10 24000±141.47*** 7142±45.11*** 85.12

2. pH 8.1±0.30 7.4±0.28*** 4.1±0.12 4.04

3. BOD 5500±266.5 2345±96.14*** 450±78.45*** 91.81

4. COD 10864±391.10 7760±372.48*** 555±11.45*** 92.84

5. TDS 10764±409.03 6232.0±255.12*** 315.85±13.12*** 94.93

6. Sulfate 15247.5±609.9 6792.0±474.84 758.54±123.74*** 88.83

7. Phosphate 5.36±0.168 2.45±0.01*** 0.46±0.01*** 91.41

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8. Heavy Metals

A Fe 41.50±1.57 29.88±3.52*** 0.84±0.001*** 97.16

B Zn 1.12±0.00 0.91±0.00*** 0.10±0.00*** 89.01

C Ni 0.25±0.00 0.15±0.00*** 0.02±0.00*** 86.66

D Mn 23.54±0.70 14.28±0.00*** 2.45±0.00*** 82.84

E Pb 0.18±0.00 0.07±0.00*** 0.001±0.00*** 98.57

F Cu 1.24±0.00 0.80±0.00*** 0.002±0.00 99.75

All the values are in (mg L-1) and means of three replicate (n=3)±SD except pH and C.I.: color intensity (Pt-Co); BDL: Below detection limit; (Student’s t test: *non-significant (p<0.05), **less significant p<0.01, ***highly significant (p<0.001)

gc-mS AnAlySiS

In GC–MS analysis of ethyl acetate extracted untreated distillery effluent showed the existence of different types of organic pollutants, most of which were biotransformed and biodegraded during bacterial and CW treatment (Fig. 1 & Table 2). However, the analysis of bacteria treated distillery effluent has shown the existence of various organic compounds (Fig. 1b). These compounds were completely absent in an untreated distillery effluent sample, they are the degraded products of MRPs and few as new metabolites. The GC-MS analysis of CW treated distillery effluent revealed one major peak at different RT: 27.32 (Fig. 1c), which corresponded to o-trimethylsilyl-cannabinol. Several minor peaks were also noted at RT: 8.12, 9.87, 15.44, 20.50, 22.63, 26.41, 30.26, 35.09, and 37.11, corresponding to D-lactic acid-DITMS; propanoic acid, 3-[(TMS)oxy]- TMS ester; tetradecane; dodecenoic acid, TMS ester; 7-ethyl-3-methyl-8-(propylsulfany)-3,7-dihydro-1H-purine-2,6-dione; ethanol, 2-(octadecycloxy); 1-monolinoleoyglycerol TMS ester; 2-monostearin TMS ether; and dotriacontane, respectively. The disappearance of most of the organic compounds from bacteria and CW rhizosphere treated distillery effluent could be related to color removal associated with bacterial degradation of organic and inorganic pollutants.

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Fig. 1: GC-MS Analysis of Untreated and Treated Anaerobically Digested Distillery Effluent Samples Extracted with Ethyl Acetate; (a) Control

(b) Bacterial Treated (c) Constructed Wetland Treated

Table 2 Organic Compounds Identified by GC–MS Analysis in Ethyl Acetate Extract of Anaerobically Digested Distillery Effluent

S. No. Name of Compound RT C BT CWT

1. Acetamide, 2,2,2-trifluoro-N-methyl-(TMS) 8.07 + + -

2. D-Lactic acid-DITMS 8.12 - - +

3. 2-Butanol, tert-butyldimethylsilyl ether 8.25 + - -

4. β-Eudesmol, TMS ether 8.25 - + -

5. Ethanedioic acid, bis(TMS)ester 9.03 + - -

6. Pyridine, 3-trimethylsiloxy 9.73 + - -

7. Propanoic acid, 3-[(TMS)oxy]- TMS ester 9.87 - + +

8. Phenylethanolamine TMS 11.72 - + -

9. 3-Hydroxy-6-methypyridine 1TMS 11.92 + - -

10. Octanoic acid, TMS ester 12.46 - + -

11. Benzeneacetic acid, TMS ester 13.15 - + -

12. Pyrrole-2-carboxylic acid, N-TMS-, TMS ester 14.27 - + -

13. Nonanoic acid, TMS ester 14.57 - + -

14. Tetradecane 15.44 - + +

15. Benzenepropanoic acid, TMS ester 15.75 + - -

16. Benzeneacetic acid, α,4-bis[(TMS)oxy], TMS ester 17.49 + - -

17. Emetan, 1’,2-didehydro-6’,7’,10,11-tetramethoxy 18.02 + - -

18. Palimitic acid, 2(tetradecycloxy)ethyl ester 19.31 - + -

19. 1-Hexadecanol, 2-methyl 19.32 + - -

20. Hexadecen, 1-ol, trans-9 19.38 - + -

21. Hexadecane 19.55 + + -

22. 5-Hydroxy-2,2-dimethyl-5,6-bis(2-oxo-1-propyl)-1-cyclohexanone 19.71 + - -

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23. 2-Propenoic acid, oxybis(methyl-2,1-ethanediyl)ester 21.24 + - -

24. Benzoic acid, 2,5-bis(TM Soxy)-TMS ester 21.93 + - -

25. Dotriacontane 22.32 - + -

26. 1,2-Propanediol, 3-(octadecycloxy)-diacetate 22.59 + - -

27. 7-Ethyl-3-methyl-8-(propylsulfany)-3,7-dihydro-1H-purine-2,6-dione 22.63 - + +

28. Anthacene 22.93 + - -

29. Pentatriacontane 23.08 - + -

30. Eicosane 23.22 - + -

31. β-D-Glucopyranoside, methyl 2,3-bis-O-(TMS)-, cyclic methylboronate 23.89 + + -

32. O-Trimethylsilyl-Cannabinol 27.32 - - +

33. Ethanol, 2-(octadecycloxy) 26.41 - + +

34. Eicosane 26.53 - + -

35. Octatriacontyl pentafluoropropionate 29.47 - + -

36. 17-Pentatriacontene 29.48 + - -

37. Docosane 29.56 - + -

38. 1-Monolinoleoyglycerol TMS ester 30.26 - - +

39. cis-10-Nonadecenoic acid, TMS ester 31.16 - + -

40. Pyrrolo [1,2-a]pyrazine-1,4-dione, hexahydro-3-(phenylmethyl) 31.70 + - -

41. 2-monostearin TMS ether 35.09 - + +

42. Dotriacontane 37.11 - - +

+: present; −: absent; C: control; BT: bacterial treated; CWT: constructed wetland treated; RT: retention time (in min)

CONCLUSION

This study has revealed that untreated distillery effluent carries a high concentration of BOD, COD etc. along with various toxic metals, which were reduced significantly after bacteria and CW plant treatment process. Further, the HPLC and GC-MS analysis have shown that most of the compounds detected in untreated anaerobically digested distillery effluent were diminished from bacterial and CW treated samples. The disappearance of compounds from bacteria and wetland plant treated sample could be related to degradation and color removal from PMDE.

ACKNOWLEDGMENTS

This work is the result of Ph.D. work of the first author. The financial assistance from University Grants Commission (UGC), New Delhi to Vineet Kumar (Letter No. F1-17.1/2012-13/RGNF-2012-13-SC-UTT-30458) is highly acknowledged.

REFERENCES

[1] AIDA (All India Distillers’ Associations), 2016. Annual report. New Delhi, http://www.aidaindia.org/annual-report.html

[2] APHA (American Public Health Association), 2012. Standard method for examination of water and wastewater. 22nd ed. APHA, AWWA and WEF, Washington, DC

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[3] Chandra, R., Bharagava, R.N., Kapley, A., Purohit, H.J., 2012. Characterization of Phragmites cummunis rhizosphere bacterial communities and metabolic products during the two stage sequential treatment of post methanated distillery effluent by bacteria and wetland plants. Bioresour. Technol. 103, 78-86.

[4] Chandra, R., Kumar, V., 2017a. Detection of Bacillus and Stenotrophomonas species growing in an organic acid and endocrine-disrupting chemicals rich environment of distillery spent wash and its phytotoxicity. Environ. Monit. Assess. 189, 26

[5] Chandra, R., Kumar, V., 2017b. Detection of androgenic-mutagenic compounds and potential autochthonous bacterial communities during in situ bioremediation of post methanated distillery sludge. Front Microbiol 8, 88

[6] Chandra, R., Kumar, V., Tripathi, S., 2018a. Evaluation of molasses-melanoidin decolourisation by potential bacterial consortium discharged in distillery effluent. 3 Biotech. 8, 187

[7] Chandra, R., Kumar, V., Tripathi, S., Sharma, P., 2018b. Heavy metal phytoextraction potential of native weeds and grasses from endocrine-disrupting chemicals rich complex distillery sludge and their histological observations during in situ phytoremediation. Ecol Eng 111, 143–156

[8] EPA, Environmental Protection Agency (1998) Design manual constructed wetlands and aquatic plant system for municipal wastewater treatment. US Environmental Protection Agency, Office of Research and Development, Cincinnati, Ohio.

[9] Hatano, K., Yamatsu, T., 2018. Molasses melanoidin-like products enhance phytoextraction of lead through three Brassica species. Int. J. Phytoreme. DOI 0.1080/15226514.2017.1393397.

[10] Kumar, V., Chandra, R., 2018. Characterisation of manganese peroxidase and laccase producing bacteria capable for degradation of sucrose glutamic acid-Maillard products at different nutritional and environmental conditions. World J Microbiol Biotechnol 34, 82.

[11] Liang, Z., Wang, Y., Zhou, Y., Liu, H., Wu, Z., 2009a. Variables affecting melanoidins removal from molasses wastewater by coagulation/flocculation. Sep Purif Technol 68(3), 382–389

[12] Liang, Z., Wang, Y., Zhou, Y., Liu, H., 2009b. Coagulation removal of melanoidins from biologically treated molasses wastewater using ferric chloride. Chem Eng J 152(1), 88–94

[13] Migo, V.P., Del Rosario, E.J., Matsumura, M., 1997. Flocculation of melanoidins induced by inorganic ions. J. Ferment. Bioeng. 83, 287–291

[14] Miyata, N., Mori, T., Iwahori, K., Fujita, M., 2000. Microbial decolourization of melanoidin-containing wastewaters: Combined use of activated sludge and the fungus Coriolus hirsutus. J Biosci Bioeng 89, 145-150.

[15] Swindell, C.E., Jackson, J.A., 1990. Constructed wetlands design and operation to maximize nutrient removal capabilities. In: Copper, P.F., Findlater, B.C. (Eds.), Constructed Wetlands in Water Pollution Control. (Advances in Water Pollution Control No. 11). Pergamon Press, Oxford. pp. 107–114.

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Effect of Different Planting Pattern and Nitrogen Management on Growth and Yield in Pearlmillet (Pennisetum Glaucum L.)+Greengram (Vigna Radiata L.) Intercropping System

Virpal Kaur1, Rachana2 Prasad Mithare3 and Rajesh Singh1

Department of Agronomy, Allahabad School of Agricultural, Sam Higginbottom University of Agriculture Technology & Sciences,

Allahabad- 211007, (Uttar Pradesh) India.Department of ILFC, KVAFSU, Bidar-Karnataka.

E-mail: [email protected], [email protected]

ABSTRACT

A field experiment was conducted during kharif season of 2015 at the Crop Research Farm (CRF) Department of Agronomy, Allahabad School of Agricultural, Sam Higginbottom University of Agriculture Technology and Sciences, Allahabad to study the effect of planting patterns and nitrogen management in Pearlmillet (Pennisetum glaucum L.) and green gram (Vigna radiata L.) intercropping system. The experiment was laid down in a randomized block design (RBD)with fifteen treatments and replicated thrice. The results revealed that Treatment T10{Paired row system (Pearlmillet + Greengram) + 50% RDN + Azospirillum + Azotobacter (Seed inoculation)}significantly increased following parameters viz, Maximum plant height (250.03 cm), number of tillers plant–1 (2.67), CGR (63.04 g m-2day-1), RGR (0.269 g g-1 day-1), LER (2.20), Aggressivity index (0.008), Gross return (85905.0 Rs. ha-1), Net return (54503.86 Rs. ha-1) and B:C ratio (1.73).Similarly Treatment T15 {Paired row system (Pearlmillet Sole) + 100% RDN}has significantly increased following parameters viz, Highest dry weight (104.30 g), Leaf area (104.23 cm 2), Spike length (31.63cm), Test weight (8.61 g), Grain yield (3.26 t ha-1), Stover yield (7.12 t ha-1) and Harvest Index (33.20 %). While lowest attributes among the treatments are recorded in treatment T2, T5and T15 respectively.

Keywords: Intercropping, Nitrogen Management, Planting Patterns, Azotobacter, Azospirillum, Paired Row

INTRODUCTION

Pearlmillet is the fourth most important cereal and widely grown in India because of its tolerance to drought, high temperature, and low soil fertility. Pearlmillet grain is the staple diet and nutritious source of vitamins, minerals, and protein, while Pearlmillet stover is a valuable livestock feed. At present, it is occupying 9.4 million ha area with a total production of 10.1 million tonnes Khambalkar et al., 2012 (1). Pearlmillet is grown mainly in Rajasthan, Maharashtra, Gujarat, Uttar Pradesh, Haryana, Karnataka, Tamil Nadu, and Andhra Pradesh.

In Rajasthan, it accounts for nearly 50 % of the area and one-third of the total production of the country. Pearlmillet is the most droughts tolerant of all domesticated cereals, and soon after

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its domestication, it became widely distributed across the semi-arid tropics of Africa and Asia. Pearlmillet is a short duration crop well adapted to less and erratic rainfall conditionsMeena and Gautam 2005 (2). Among agronomic management practices, selection of suitable planting method and nutrient management are essential to make the best use of limited available water. At present productivity level, Pearlmillet removes about 72kg NPK ha-1, whereas only 10-12kg ha-1 of these nutrients are being supplied through fertilizersRathore et al., 2006 (3). Application of nitrogenous fertilizer has played a key role in increasing food grains production in the country and will continue to do so in future Prasad et al., 2011 (4). Bio-fertilizers play an important role in increasing the availability of nutrients as well as enhancing productivity in a sustainable manner. Azotobacter and Azospirillum are free-living bacteria for N fixation in soils. On an average, the former can fix 20-40 kg N ha-1, whereas, the later can fix 20 kg N ha-1year-1 besides promoting a release of growth promoting substances. Singh et al., 2013 (5)Azotobacter belong to family Azotobacteriaceae, it is aerobic, free-living, and heterotrophic in nature. Azotobacter is present in neutral or alkaline soils. In addition to their nitrogen-fixing ability of about 20-40 kg ha-1, they also produce growth-regulating substances. Thus it is mainly recommended for maize, sugarcane, sorghum, pearl millet etc.

Green gram is scientifically known as Vigna radiata (L.) and commonly known as moong in India. Greengram seeds are highly nutrition’s with protein (23-24%), carbohydrates (60%), minerals, amino acids, and vitamins. Green gram plays an important role in maintaining and improving the fertility status of the soil, as they have the ability to fix atmospheric N (20-25 kgha-1) symbiotically in soil through root nodules. Being a short duration crop and having wide adaptability, it is generally grown as an intercrop, mixed crop and sole crop in Kharif as well as in summer season where adequate irrigation facilities are available Patel et al., 2013 (6). The United Nations, declared 2016 as International Year of Pulses (IYP) to heighten public awareness of the nutritional benefit of pulses as part of sustainable food production aimed at food security and nutrition. India is the largest producer and consumer of pulse contributes 25% of global production, 27% of world consumption and importer 14% of pulses in the world. The area under pulse has increased from 19 m ha–1 in 1950-51 to 25 m ha–1 in 2013-14, indicating an increase of 31 percent whereas production of pulse during the same period has increased from 8.41 million ha–1 to 19.27 million ha–1 an increase of over 100% GOI 2015 (7). In 2014-15 17.20 million tones and estimate production for 2015-16 about 18.32 million tons. Intercropping provides an efficient utilization of environmental resources, reduces risk to the cost of production, provides greater financial stability for farmers, decreases pest damages, suppresses weeds growth more than monocultures, improves soil fertility through nitrogen fixation and improves forage yield and qualityCommodity Profile: DES, DAC&FW, & DoC 2015 (8).


A field experiment was conducted during Kharif season of 2015 at the Crop Research Farm (CRF) Department of Agronomy, Allahabad School of Agricultural, Sam Higginbottom University of Agriculture Technology and Sciences, Allahabad. The experiment site lies between 25-27° N latitude, 8.5°E Longitude and 98 meters altitude. The climate is characterized by the alternate hot rainy season from late June to early September with a mean temperature of 38°C. The soil was sandy loam in texture and having a pH (7.5), EC (0.27 dSm-1), organic carbon (0.39 %), available N (190.3 kg ha–1), P (22.5 kg ha–1), K (87 kg ha–1) during the experimental

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Effect of Different Planting Pattern and Nitrogen Management on Growth and Yield 251

ISBN: 978-93-88237-24-6

year. The experiment was laid down in randomized block design (RBD)with Different Planting Pattern in Pearlmillet + Greengram Intercropping (P1: Uniform Row System and P2: Paired Row System) and Nitrogen Management in Pearlmillet + Greengram Intercropping System (N1: RDN, N2: 50 % RDN, N3: 50 % RDN + Azospirillum, N4: 50% RDN + Azotobacter, N5: 50% RDN + Azotobacter + Azospirillum) with fifteen treatments and replicated thrice. The Pearlmillet variety (Narmada-6022) and mungbean variety (PDM-139 SAMRAT) was sown 60 cm (Uniform Row System) whereas 90/30 cm (Paired Row System) and plant to plant 10 cm respectively. The sowing was done on 29 July 2015 using (5 kg ha-1 Pearlmillet and 20 kg ha-1 Greengram). The crop was thinned after complete germination to maintain a plant to plant spacing of 10 cm apart. A common dose of Phosphorus and Potassium at 50:40 kg ha–1 was applied through di-ammonium phosphate and Murate of potash, respectively. Whereas Nitrogen was applied as per treatment combination and incorporated in the soil, irrigation was given to ensure microbial activities to hasten the availability of nutrients to crop. Irrigation was scheduled at 10 days interval during vegetative growth & total of 3 irrigations were applied at critical stages of the crop. However other normal cultural practices were followed timely as; weeding at 25 DAS was done respectively. One quadrate (1 m2) was harvested in every plot for the determination of results and data was subjected to statistical analysis separately by using analysis of variance technique. In order to determine protein in seeds Kjeldahl’s digestion and distillation procedure was followed to determine nitrogen in seeds. Then the protein content of the grain was determined by multiplying the nitrogen content of grain by 6.25. The treatment consistedT1:-U.R (Pearlmillet + Greengram) + RDN, T2:-U.R. (Pearlmillet + Greengram) + 50% RDN, T3:-U.R. (Pearlmillet + Greengram) + 50% RDN+ Azospirillum, T4:- U.R. (Pearlmillet + Greengram) + 50% RDN+ Azotobacter, T5:-U.R. (Pearlmillet + Greengram) + 50% RDN+ Azospirillum + Azotobacter, T6:-P.R. (Pearlmillet + Greengram) + RDN, T7:-P.R. (Pearlmillet + Greengram) + 50% RDN, T8:-P.R (Pearlmillet + Greengram) + 50% RDN+ Azospirillum, T9:-P.R. (Pearlmillet + Greengram) + 50% RDN+ Azotobacter, T10:-P.R. (Pearlmillet + Greengram) + 50% RDN+ Azospirillum + Azotobacter, T11:-Greengram Sole, T12:-U.R. (PearlmilletSole) + 50% RDN, T13:-U.R. (PearlmilletSole) + 100% RDN, T14:-P.R. (PearlmilletSole) + 50% RDN, T15:-P.R. (PearlmilletSole) + 100% RDN.The difference among treatment means was compared by using the least significant difference test at 5% probability levels.


groWth AttriButeS of peArlmillet

The observations regarding growth attributes of Pearlmillet viz, Plant height (cm), Dry weight (g), No. of tillers plant-1, Crop growth rate (g m-2day-1), Relative growth rate (g g-1day-1) and Leaf area (cm2)were influenced by different planting pattern and nitrogen management and this beneficial effect was seen during kharif seasons and also may be due to synchronized availability of essential plants nutrients to the crop especially NPK for a longer period during its growth stages. The results revealed that maximum plant height (250.03 cm), number of tillers plant–1 (2.67), CGR (63.04 g m-2day-1) and RGR (0.269 g g-1 day-1) were recorded in Treatment T10{Paired row system (Pearlmillet + Greengram) + 50% RDN + Azospirillum + Azotobacter (Seed inoculation)}. Whereas highest dry weight (104.30 g) and Leaf area (104.23 cm 2) were recorded in Treatment T15 {Paired row system (Pearlmillet Sole) + 100 % RDN}. The lowest

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growth attributes among the treatments are recorded in treatment T2, T5and T15 respectively (Table 1) and (Fig 1). The probable reasons for recording higher plant height under paired row system in intercropping might be due to better sunlight receptivity due to wider spacing between two paired rows, in addition to increased nitrogen availability by atmospheric nitrogen fixation in the root rhizosphere by seed inoculation with Azotobacter and Azospillum culture. The closer results have been reported by Naserietal., 2013 (9). Biofertilizers promote growth by increasing the availability of primary nutrients or growth stimulus to the target crop to increase dry weight when applied to seed, plant surfaces, or soil Muraleedharanetal.2010 (10). The findings of Bashan et al., 2004 (11)revels that inoculation of wheat with A. brasilense significantly increased plant dry weight, number of tillers per plant, spikelet fertility and grain yield. Similar results have been reported by Rathore et al., 2008 (12)Paired row (PR)system of planting recorded the maximum improvement in growth parameters which was significantly superior to UR system of planting.

yield AttriButeS of peArlmillet

The observations regarding yield attributes of Pearlmillet viz, Spike length (cm), Test weight (g), Grain yield (t ha-1), Stover yield (t ha-1) and Harvest index (%)were influenced by different planting pattern and nitrogen management and this beneficial effect was seen during kharif seasons and also may be due to synchronized availability of essential plants nutrients to the crop especially NPK for a longer period during its reproductive stages. The results revealed that highest Spike length (31.63cm), Test weight (8.61 g), Grain yield (3.26 t ha-1), Stover yield (7.12 t ha-1) and Harvest Index (33.20 %) was recorded in Treatment T15 {Paired row system (Pearlmillet Sole) + 100 % RDN}. The lowest growth attributes among the treatments are recorded in treatment T2, T5and T15 respectively (Table 2) and (Fig 2). The probable reasons for recording higher spike length may be attributed to increased uptake of nitrogen by the plants, which were made available through nitrogen fixation by the microorganisms. The 8.5% increase in height of corn which was observed in seed inoculation by Azotobacter, which was reported by Zahir et al., 1998(13).Similarly, highest test weight, grain yield, stover yield, and harvest index under paired row system in the intercropping system might be due to better sunlight receptivity due to wider spacing between two paired rows in addition to increased nitrogen availability by atmospheric nitrogen fixation in the root rhizosphere by seed inoculation with Azotobacter and Azospillum culture. Rathore et al., 2006 (3)reported that modified planting patterns (PR and PR+ Intercropping system) brought about a significant improvement in grain and stover yields of Pearlmillet over UR system of planting. The research trial conducted by Wani et al., 2007 (14) indicated that Pearl millet and Sorghum crop inoculated with Azotobacter and Azospirillum which are grown as dryland crops showed 11-12% increased yields due to inoculations.

groWth And yield AttriButeS of greengrAm (intercrop)

The observations regarding growth attributes of green gram intercrop viz, Plant height (cm) and dry weight (g). The results revealed that maximum plant height (74.71 cm) and dry weight (10.24 g) was recorded in Treatment T11 {Greengram Sole}, but under intercropping system the maximum plant height(72.34 cm) and dry weight (10.05 cm) was recorded in treatmentT10 {P.R. (Pearlmillet + Greengram) + 50% RDN+ seed inoculation with Azospirillum +

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Azotobacter} and T11 {P.R.( Pearlmillet + Greengram) + RDN}. While the lowest attributes were recorded in treatment T1, T3, and T5. Similarly, the observation regarding yield attributes of green gram in intercropping system viz, Number of pods plant-1, Number of grains pod-1, Test Weight (g) and Grain yield (t ha-1). The results revealed that maximum yield attributes were recorded in treatment T11 {Greengram Sole}, but under the intercropping system, the maximum number of pods plant-1 (27.48) was recorded in treatment T8 {P.R (Pearlmillet + Greengram) + 50 % RDN + Azospirillum}. While other yield attributes Viz Number of grains pod-1, Test Weight (g) and Grain yield (t ha-1) were recorded statistically non-significant among the treatments. Similar findings are reported by Morales et al.,2000 (15) and Sharma et al., 2014 (16). (Table 3) and (Fig 3).

INTERCROPPING ATTRIBUTES

lAnd eQuivAlent rAtio (ler)

The observation regardingLERbeing presented in the (Table 4) and (Fig 4).The highestLER(2.20) was recorded under treatment T10 {P.R. (Pearlmillet + Greengram) + 50% RDN+ Azospirillum + Azotobacter}. While lowest LER(1.43) was recorded under treatmentT1{U.R (Pearlmillet + Greengram) + RDN}.

AggreSSivity index

The observation regarding Aggressivity index being presented in the (Table 4) and (Fig 4).The highest Aggressivity index (0.008) was recorded under treatment T10 {P.R. (Pearlmillet + Greengram) + 50 % RDN + Azospirillum + Azotobacter}. While lowest Aggressivity index (-0.001) was recorded under treatment T1 {U.R (Pearlmillet + Greengram) + RDN}.

economicS

The observation regarding effect of different planting pattern and nitrogen management on economics. Thehighest gross return (85905.00 ` ha-1), net return (54503.86 ` ha-1) and B: C ratio (1.73) was observed in treatment T10 {P.R. (Pearlmillet + Greengram) + 50 % RDN + Azospirillum + Azotobacter}, while lowest gross return (28782.50 ` ha-1), net return (2482.32 ` ha-1) and B: C ratio (0.09) was recorded in treatment T12 {U.R ( Pearlmillet Sole ) + 50 % RDN} respectively (Table 5) and (Fig 5).

CONCLUSION

The data pertaining to the different treatments, it may be concluded that for obtaining higher profit from kharifPearlmillet and green gram intercropping. Pearlmillet should be sown in a paired row and fertilized with 50 kg N ha-1 along with seed inoculation with Azotobacter and Azospirillum, which significantly increased the plant height, dry weight, number of tillers plant-1, test weight and grain yield of the Pearlmillet crop in addition to a better yield of green gram. Since the findings are based on the research done in one season it may be repeated for conformation.

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ACKNOWLEDGMENTS

The author acknowledges the Department of Agronomy, Allahabad School of Agricultural, Sam Higginbottom University of Agriculture Technology & Sciences, Allahabad (Uttar Pradesh) for providing financial support to carry out the research work.

Table 1: Effect of Different Planting Pattern and Nitrogen Management on Growth Attributes of Pearlmillet

Treatments Plant Height (cm)60 DAS

Dry weight (g)60 DAS

No. of Tillers Plant-1

60 DAS

CGR(g m-2

day-1)45-60 DAS

RGR(g g-1day-1)45-60 DAS

Leaf Area (cm2)60 DAS

T1 U.R.(Pearlmillet + Greengram) + RDN

235.90 101.63 2.20 62.7008 0.2637 101.13

T2 U.R.(Pearlmillet + Greengram) + 50 % RDN

206.67 97.92 1.87 58.0138 0.2688 97.30

T3 U.R.(Pearlmillet + Greengram) + 50% RDN + Azospirillum

230.20 99.63 1.73 59.8279 0.2657 100.63

T4 U.R.(Pearlmillet + Greengram) + 50% RDN+ Azotobacter

230.60 100.78 1.93 60.9904 0.2670 100.73

T5 U.R.(Pearlmillet + Greengram) + 50% RDN+ Azospirillum + Azotobacter

233.27 101.33 2.00 54.6818 0.2597 101.40

T6 P.R.( Pearlmillet + Greengram) + RDN

239.90 102.03 2.20 62.9008 0.2632 102.67

T7 P.R.( Pearlmillet + Greengram) + 50% RDN

227.27 99.87 2.07 57.6066 0.2690 99.70

T8 P.R.( Pearlmillet + Greengram) + 50% RDN+ Azospirillum

234.80 98.70 2.13 61.7901 0.2678 102.57

T9 P.R.( Pearlmillet + Greengram) + 50% RDN+ Azotobacter

239.90 101.00 2.20 57.4955 0.2631 101.43

T10 P.R.( Pearlmillet + Greengram) + 50% RDN+ Azospirillum + Azotobacter

250.03 103.33 2.67 63.0488 0.2692 101.60

T12 U.R.( Pearlmillet Sole ) + 100% RDN

224.30 96.33 1.87 53.2750 0.2535 98.87

T13 P.R.( Pearlmillet Sole ) + 50% RDN

240.47 102.83 2.20 54.6078 0.2605 102.40

T14 P.R.( Pearlmillet Sole ) + 100% RDN

224.20 97.60 2.13 49.8319 0.2596 100.43

T15 U.R.( Pearlmillet + Greengram) + RDN

244.70 104.30 2.40 55.2742 0.2580 104.23

F-testSEd(±)

CD (P=0.05)

S7.2014.81

S0.982.02

NS0.26--

S1.783.67

S0.00190.0041

S0.691.42

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Table 2: Effect of Different Planting Pattern and Nitrogen Management on Yield Attributes of Pearlmillet

Treatments Spike Length (cm)

Test weight (g)

Grain Yield (t ha-1)

Stover Yield(t ha-1)

Harvest Index (%)

T1 U.R.(Pearlmillet + Greengram) + RDN 28.93 7.35 2.15 6.97 29.85

T2 U.R.(Pearlmillet + Greengram) + 50 % RDN 24.73 6.19 1.98 5.45 26.79

T3 U.R.(Pearlmillet + Greengram) + 50% RDN + Azospirillum

27.47 7.79 2.00 5.98 27.97

T4 U.R.(Pearlmillet + Greengram) + 50% RDN+ Azotobacter

27.07 7.40 2.12 5.55 27.40

T5 U.R.(Pearlmillet + Greengram) + 50% RDN+ Azospirillum + Azotobacter

28.63 7.28 1.92 7.05 23.28

T6 P.R.( Pearlmillet + Greengram) + RDN 28.73 7.44 2.25 7.12 26.47

T7 P.R.( Pearlmillet + Greengram) + 50% RDN 25.07 6.30 1.90 5.82 24.26


28.33 7.50 2.19 6.35 26.90


27.83 7.67 2.41 6.53 30.21


28.97 8.10 2.96 6.97 34.70

T12 U.R.( Pearlmillet Sole ) + 100% RDN 26.73 7.14 2.05 5.29 28.43

T13 P.R.( Pearlmillet Sole ) + 50% RDN 29.37 8.16 3.08 7.06 33.14

T14 P.R.( Pearlmillet Sole ) + 100% RDN 26.53 6.52 2.14 5.23 28.01

T15 U.R.( Pearlmillet + Greengram) + RDN 31.63 8.61 3.26 7.12 33.20

F-test S S S S NS

SEd(±) 1.28 0.66 0.42 0.54 4.12

CD (P=0.05) 2.64 1.35 0.87 1.11 --

Table 3: Effect of Different Planting Pattern and Nitrogen Management on Growth and Yield Attributes of Greengram (Intercropping)


Dry weight (g)

Number of Pods Plant-1

Number of Grains Pod-1

Test weight (g)

Grain Yield(t ha-1)

T1 U.R.( Pearlmillet + Greengram) + RDN

62.26 9.41 26.37 11.55 32.88 0.84

T2 U.R.( Pearlmillet + Greengram) + 50% RDN

66.75 9.51 24.97 11.60 33.56 0.80

T3 U.R.( Pearlmillet + Greengram) + 50% RDN+ Azospirillum

66.38 9.48 25.69 11.48 31.59 0.87

T4 U.R.( Pearlmillet + Greengram) + 50% RDN+ Azotobacter

66.75 10.02 25.70 11.78 32.12 0.81

T5 U.R.( Pearlmillet + Greengram) + 50% RDN+ Azospirillum + Azotobacter

69.79 9.49 24.72 11.42 33.67 0.86

Table 3 (Contd.)...

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Dry weight (g)

Number of Pods Plant-1

Number of Grains Pod-1

Test weight (g)

Grain Yield(t ha-1)

T6 P.R.( Pearlmillet + Greengram) + RDN

70.36 10.05 26.90 11.90 33.64 0.94

T7 P.R.( Pearlmillet + Greengram) + 50% RDN

69.22 9.71 26.78 12.02 33.80 0.84


68.04 9.75 27.48 12.64 34.30 0.92


68.68 9.96 26.34 12.38 33.48 0.86


72.34 9.69 26.65 13.30 34.55 0.93

T11 Greengram Sole 74.71 10.24 29.66 13.52 34.82 1.13

F-test S S NS NS NS NS

SEd(±) 1.16 0.15 0.87 0.67 1.42 0.08

CD (P=0.05) 2.41 0.33 -- -- -- --

Table 4: Effect of Different Planting Pattern and Nitrogen Management on Intercropping Attributes

Treatments LER Aggressivity Index

T1 U.R.(Pearlmillet + Greengram) + RDN 1.43 -0.001

T2 U.R.(Pearlmillet + Greengram) + 50 % RDN 1.66 0.005

T3 U.R.(Pearlmillet + Greengram) + 50% RDN + Azospirillum 1.73 0.004

T4 U.R.(Pearlmillet + Greengram) + 50% RDN+ Azotobacter 1.74 0.006

T5 U.R.(Pearlmillet + Greengram) + 50% RDN+ Azospirillum + Azotobacter 1.69 0.003

T6 P.R.( Pearlmillet + Greengram) + RDN 1.52 -0.002

T7 P.R.( Pearlmillet + Greengram) + 50% RDN 1.62 0.002

T8 P.R.( Pearlmillet + Greengram) + 50% RDN+ Azospirillum 1.83 0.003

T9 P.R.( Pearlmillet + Greengram) + 50% RDN+ Azotobacter 1.88 0.003

T10 P.R.( Pearlmillet + Greengram) + 50% RDN+ Azospirillum + Azotobacter 2.20 0.008

F-test -- --

SEd(±) -- --

CD (P=0.05) -- --

Table 5: Effect of Different Planting Pattern and Nitrogen Management on Economics

Treatments Gross returns(`ha-1)

Net returns(`ha-1)

Benefit cost ratio (B:C)

T1 Uniform Row System + RDN 70957.50 39404.51 1.24

T2 Uniform Row System + 50% RDN 66250.00 35348.86 1.14

T3 Uniform Row System + 50% RDN + Azospirillum 70070.00 38918.86 1.24

T4 Uniform Row System + 50% RDN + Azotobacter 68640.00 37488.86 1.20

...Table 3 (Contd.)

Table 5 (Contd.)...

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T5 Uniform Row System + 50% RDN + Azospirillum + Azotobacter

69225.00 37823.86 1.20

T6 Paired Row System + RDN 77242.50 45689.51 1.44

T7 Paired Row System + 50% RDN 67320.00 36418.86 1.17

T8 Paired Row System + 50 % RDN + Azospirillum 75167.50 44016.36 1.41

T9 Paired Row System + 50% RDN + Azotobacter 75342.50 44191.36 1.42

T10 Paired Row System + 50% RDN + Azospirillum + Azotobacter

85905.00 54503.86 1.73

T11 Greengram Sole 54035.00 26584.90 0.96

T12 Uniform Row System+ Pearlmillet Sole 50% RDN 28782.50 2482.32 0.09

T13 Uniform Row System + Pearlmillet sole 100%RDN 42800.00 15847.68 0.58

T14 Paired Row System + Pearlmillet Sole 50% RDN 29900.00 3599.82 0.13

T15 Paired Row System + Pearlmillet Sole 100%RDN 45125.00 18172.68 0.67

Fig.1: Effect of Different Planting Pattern and Nitrogen Management on Growth Attributes of Pearlmillet

Fig.2: Effect of Different Planting Pattern and Nitrogen Management on Yield Attributes of Pearlmille

...Table 5 (Contd.)

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Fig.3: Effect of Different Planting Pattern and Nitrogen Management on Growth and Yield Attributes of Greengram (Intercropping)

Fig.4: Effect of Different Planting Pattern and Nitrogen Management on Intercropping Attributes

Fig.5: Effect of Different Planting Pattern and Nitrogen Management on Economics

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REFERENCES

[1] Khambalkar, P.A.,Tomar, P.S. and Verma S.K. (2012) Long – term effects of integrated nutrient management on productivity and soil fertility in Pearlmillet (PennisetumglaucumL.) – mustard (Brassica juncea) cropping sequence. Indian Journal of Agronomy. 57(3): 222–228.

[2] Meena, R., and Gautam, R.C. (2005) Effect of Integrated Nutrient Management on Productivity, Nutrient Uptake and Moisture Use Functions of Pearlmillet (Pennisetum glaucum).Indian Journal of Agronomy, 50 (4):305–307.

[3] Rathore, V.S., Singh, P. and Guatam, R.C. (2006). Productivity and water-use efficiency of rainfed Pearlmillet (Pennisetum glaucum) as influenced by planting patterns and integrated nutrient management. Indian Journal of Agronomy, 51(1):46-48.

[4] Prasad. R. 2011. Nitrogen and food grain production in India. Indian Journal of Fertilizer. 7 (12): 66-76.

[5] Singh, R., Gupta, A.K., Ram. T., Choudhary. G.L. and Sheoran A.C. (2013) Effect of Integrated nitrogen management on transplanted Pearlmillet (Pennisetum glaucum) under rained condition. Indian journal of Agronomy, 58 (1):81–85.

[6] Patel, H.R., Patel, H.F. and Bhale, V.M. (2013). Response of kharif greengram (Vigna radiata L.) to sulphur and phosphorus fertilizers with and without biofertilizers application. The Bioscan, 8 (1):149–152.

[7] GOI (2015).Agriculture statistics at a glance: published by Ministry of Agriculture, Govt. of India. Http://www. Nabard.org.in.

[8] Commodity Profile (2015). Department of economics and dtatistics (DES), Department of agriculture, Cooperatation & FW (DAC & FW), and Department of Commerce (DOC) Published by Ministry of Agriculture, Government of India.

[9] Naseri, M., Singh S.H. and Choudary Mukesh (2013).Effect of integrated nutrient management on yield and nutrient uptake in barley. Indian Journal of Agronomy. 58 (4): 543–47.

[10] Muraleedharan. H., Seshadri, S. and Perumal, K. (2010). Biofertilizer (Phosphobacter), Shri Murrugapa Chettiar Research Centre.

[11] Bashan, Y., Holguin, G. and de-Bashan, L.E (2004).Azospirillum- plant relationships: physiological, molecular, agricultural, and environmental advances. Can. J, Microbiol: 521–577.

[12] Rathore, B.S., Rana, V.S. and Nanwal, R.K.(2008) Effect of plant density and fertility levels on growth and yield of Pearlmillet (PennisetumglaucumL.) hybrids under limited irrigation conditions in semi-arid environment. Indian Journal of Agricultural Sciences. 78(1): 667–670.

[13] Zahir, A., Arshad, Z. andFrankenberger, W.F. (2004). Plant growth promoting rhizobacteria: applications and perspectives in agriculture. Advances in Agronomy. 81:97–168.

[14] Wani, S.P., Chandrapalaiah, S., Zambre, M.A. and Lee, K.K. (2007). Association between nitrogen-fixing bacteria and pearl millet plant, response, mechanisms and resistance. Plant Soil. 110: 284–302.

[15] Morales, A. S. and Carangal, C.V. (2000). Effect of Rhizobium inoculation and nitrogen fertilization on nodulation, grain yield and other yield attributes of mungbean (vigna radiata L.).

[16] Sharma and Sharma.S(2014). Effect of nitrogen and sulphur nutrition on yield parameters and protein composition in soybean (Glycine max L). J. of Applied & Natrual Sciences.6 (2): 402–408.

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Ergonomic Evaluation in Weeding Operation Conducted by Hand Hoe (Khurpa) and Wheel Hoe of Wheat Crop for Female Respondents

Vishnu Ji Awasthi1, Ashok Tripathi1, Rahul Chaudhary1 and Mirtunjay Pandey2

1Farm Machinery and Power Engineering, VSEAT, Sam Higginbottom University of Agriculture,

Technology and Sciences, Allahabad–211 007, UP, India.2Farm Machinery and Power Engineering,

Faculty of Agricultural Engineering, Bidhan Chandra Krishi Vishwavidyalaya, Mohanpur,

Nadia–741252, West Bengal, India.

ABSTRACT

The current research study was conducted with the intent to determine the anthropometrical, physical, physiological characteristics and resulting postural discomfort of female operators during weeding operation which was carried out by the two implements hand hoe and wheel hoe. The research was conducted in the farm of the Sam Higginbottom University of Agriculture, Technology and Sciences, Naini, Allahabad. The subjects on which the research was applied was first tested on anthropometrical basis followed by the physical and physiological parameters while accomplishing weeding operation conducted by implements- hand hoe (khurpa) and wheel hoe. The variations were measured before and after the commencement of weeding activity by mentioned implements for a duration of 20 minutes. For the physical characteristics of the respondents, the average BMI of a female was 21.92 Kg/m² and lies in the normal range of 18.5-25. The average LBM and BMR value noticed was 32.19 and 606.96 respectively. The VO2max and AWL was 30.16 mL/Kg min and 10.56 respectively. Assessment of physiological parameters includes the measurement of average resting and working heart rate, average resting and working blood pressure (both systolic and diastolic), EER, OCR and CCW. The average resting heart rate of female respondents was 92 bpm. The average working heart rate during weeding activity in case of hand hoe and wheel hoe was 102.83 and 109.67 (bpm) respectively. The difference in resting and working heart rates was recorded as (a.) by hand hoe 12.16 bpm, (b.) wheel hoe 16.16 bpm. The average EER and OCR values were 8.02kJ/min and 0.8 L/min in case of hand hoe and for wheel hoe it was 8.78 kJ/min and 1.1 L/min respectively. The CCW values in case of wheel hoe and hand hoe 243.2 and 316.7 (beats) for female respondents.

Keyword: Basal Metabolic Rate (BMR), Lean Body Mass (LBM), Heart Rate, Energy Expenditure Rate (EER), Oxygen Consumption Rate (OCR), Cardiac Cost of Work (CCW)

INTRODUCTION

Agriculture provides the basic means of livelihood for the majority of Indian families. The workers use various types of tools, equipments and machinery for their day to day activities in the agricultural fields. Use of proper tools provides promising and encouraging results and hence it becomes utmost necessary to consider the human factor in the design of farm tools to

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enhance the operating efficiencies, working comfort and thereby improving the productivity of workers. Ergonomically designed equipment’s/tools enhance the human operating efficiencies and comfort during its operation. With the growing feminization of farm labour due to male rural to urban migration, women are forced to carry out work previously done by men. Consequently, women are increasing their workload and taking care of a wider scope of agricultural tasks, but the degree to which they have access to improved technologies need special consideration (Agarwal S. 2007). In view of this, an effort has been made to access the ergonomics involved in various postures of farm workers who are using traditional farm tools in their day today weeding activities. In India, most of the operation involves the utilization of mechanization which is being performed by male operators. But the female operators/ workers are mostly involved in manual operations such as sowing of seeds (broadcasting, weeding, harvesting, threshing, and winnowing). Ensuring effective safety and ease of operators is the prime function of ergonomics. This can be achieved by measuring and estimating the anthropometric dimensions and the physiological responses with respect to the working environment (during farm operations). Ease of performing an operation affects the output of the worker. Ergonomic evaluation is a tool to evaluate the energy expenditure of work, their physiological cost, and suitability of the method for farm workers and how long they can work continue without getting fatigue (Kumar A. et al.,2013). The criteria for choosing hand hoe and the wheel hoe for accomplishing weeding operation is that these equipment are easily manipulated and utilized by female operators in comparison to other bulky hoe weeder and both the equipments involves different working posture i.e hand hoe (khurpa) involves squatting working posture of human operators. These are traditional weeding and inter-culture tools commonly used by the male and female operators. Tewari et al. (1991) stated that the performance of the weeder is interpreted in terms of weeding efficiency and the grade of work relates to a rating of the workload while worker’ comfort is the subjective assessment of operating posture. These equipments involve manual method which in turn requires workers. Wheel hoe has a high work rate of about 0.05ha/hr while that of hand hoe (khurpa) has 0.01ha/hr. These are easily accessible by the female workers in the country. Both of these weeding equipments are portable and are easily manipulated by both male and female workers. In most of the rural areas of the country, weeding operation by hand hoe and wheel hoe is predominantly carried by the female operators. It is important to assure safety and comfort during operation form ergonomic point of view. Ease of performing an operation affects the output of the worker. Ergonomic evaluation is a tool to evaluate the energy expenditure of work, their physiological cost and suitability of the method for farm workers and how long they can work continue without getting fatigue (Kumar A. et al., 2013). The assessment of anthropometrical, physiological and body postural discomfort of the operators is the bottom line in the ergonomic evaluation so as to compare the variations resulting during weeding operation.


The study was conducted at Department of Farm Machinery & Power Engineering, Vaugh Institute of Agricultural Engineering and Technology, Sam Higginbottom University of Agriculture, Science and Technology Allahabad.

The details of materials, procedures followed, and techniques adopted during the course of present investigation have been elaborated in this chapter under the following headings.

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EXPERIMENTAL SETUP

Table 1: The Concise Outlook of the Experimental Plan

A Brief Outlook of the Experimental Plan

Farm operation Weeding

Number of operations 1

Implements used Hand and wheel hoe

Number of implements 2

Total number of operators 6

Total number of treatments 6

Total number of replications 3

Duration of weeding activity 20 min

Number of anthropometric dimensions 16

Number of assessments of physical characteristics 7

Number of assessments of physiological parameters 7

The area under weeding operation 30x40 m²

Area of the row(strip) under weeding operation 0.5x30m²

ANOVA – Type Completely randomized design

MATERIAL: (A) FOR MEASUREMENT OF ANTHROPOMETRIC DIMENSIONS OF THE FEMALE RESPONDENTS

Steel Scale–It is employed for measuring the small dimensions (small body parts) including palm length, knee height, bideltoid length etc. It measures length in inches and cm.

Measuring tape–Also known as a retractable flexible rule or tape measure. It is an important measuring instrument employed for determining and measuring height, elbow height, arm reach, hand length, foot length and other anthropometric parameters of the subjects.

APPLICATIONS/ USAGE IN THE CURRENT STUDY

1. For measuring anthropometric dimensions

2. For determining the area involved in the weeding operation

Anthropometer–It was employed to measure the anthropometric dimensions of the subjects including vertical arm reach, bideltoid breadth, illiocrystable height, and olecranon height.

FOR THE MEASUREMENT OF PHYSICAL AND PHYSIOLOGICAL PARAMETERS OF THE SELECTED SUBJECTS: -

(a) Weighing Scale—It is an instrument used in the current study measuring the weight of female subjects of different ages in the current research study. By knowing the

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weight of the subjects, it is easy to determine the body mass index (BMI). It measures weight in kg.

(b) The electronic sphygmomanometer—The instrument is employed in the study on account of its flexibility in measuring systolic and diastolic pressure by sociometric detection. It measures the pulse rate accurately simultaneously with the blood pressure in mm of Hg.

-Measures pulse rate in per minute

EQUIPMENT EMPLOYED FOR WEEDING ACTIVITY WHICH IS TAKEN INTO CONSIDERATION

(a) Hand hoe: Hand hoe used in weeding operation is khurpa. It is a traditional weeding and inter-culture tool. It essentially consists of a blade attached to a ferrule. The blade is used to uproot the weeds. It consists of a wooden handle to manipulate it according to its necessity. It is usually operated by the rural labors to perform the weeding operation. The work rate of hand hoe is about 0.01ha/hr.

Fig.1: (a)-Hand hoe (khurpa) Fig.1:(b)- Wheel hoe

(b) Wheel hoe: It is a manually operated weeder mostly used by both male and female operators owing to its high work rate of 0.05ha/h. It consists of a single sharp tyne blade and a single wheel to move hoe to the desired direction. It is operated in a standing posture which renders the operator more mobile.

Table 2: Specifications and Working Features of the Mentioned Weeding Implements

S.No Hand hoe (khurpa) Wheel hoe

1 Overall length (mm) 330 Overall length (mm) 1680

2 Width of cutting edge (mm) 120 Working width (mm) 110-190

3 Length of the blade with tang (mm) 220 Length of the tyne (mm) 60

4 Weight (kg) 1.1 Weight (kg) 7.3

5 Working depth (mm) 10-25 Working depth (mm) 15-25

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Fig. 2: (a) Weighing Scale Fig. 2:(b) Electronic Sphygmomanometer

METHOD (IN ORDER TO IMPLEMENT THE EXPERIMENTAL PLAN)

The work was conducted in Agricultural farms, SHUATS, Allahabad. The anthropometric data of the female operators were measured during the study. Weeding operation was carried out by hand hoe i.e. khurpa and wheel hoe at the desired site prescribed in the field of the wheat crop with a row to row spacing 0.95m. Six female subjects in the age group of 25 to 50 years were selected. Both the operators are chosen at random for weeding operation. The female subjects were chosen randomly to perform the operation by hand hoe and wheel hoe. Different replications (3 replications) were taken for the subjects during their performance by the listed hoes. These replications are performed on different days and each trial by each subject for each implement was 20min duration.

The subjects were selected on the basis of a range of various age to conduct the evaluation of the performance from the ergonomic point of view. The past history of the respondents was considered with the intent to obtain the sonorous results in the present research study. The subject was made well acquainted with the experimental protocol to achieve their full co-operation and to maintain the uniformity in the measurement. Proper co-ordination and a sort of collaboration were achieved with the subject.

Fig.3: (a) and (b)-Weeding Operation Carried out by (a) Hand hoe and (b)Wheel hoe

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Firstly, all the anthropometric measurement is taken including height, weight and other body parameters of different ages of the subject. Afterward, they were allowed to perform the weeding operation by employing the mentioned hoes for a duration of 20min. Before the commencement of the weeding operation. The physiological parameters of the subject were taken such as heart rate (maximum and minimum) heart rate and resting and working blood pressure (both Systolic and Diastolic) were measured at one-minute intervals after five minutes from the beginning of work. After that other variable whose values depend on above-enlisted parameters including OCR, EER and CCW were calculated. The same procedure was repeated to get three sets of

Fig.4 The Measurement of Physical and Physiological Parameters

reading and the average of the three sets was used to achieve the rigorous readings. After measuring the physiological parameters before the commencement of the operation, the subject was allowed to perform the desired task for a duration of 20minutes, thereafter, the same variables are measured to get the variation underperforming the desired operation for both the subject (first for female than for male).

The whole procedure was repeated for the next days to take out at least three replications (trials)

PHYSICAL PARAMETERS INVOLVED IN THE STUDY FOR FEMALE SUBJECTS

1. BMI—The BMI is defined as the body mass divided by the square of the body height.

The relation of BMI is given as:

BMI = Weight/ (Height)²

2. LBM—Lean body mass is a component of body composition, calculated by subtracting body fat weight from total body weight.

Estimation - LBM is usually estimated using the relation given by Hume, R (Jul 1966).

For Female – LBM = (0.29569*W) + (0.41813*H) – 43.2933

3. Weight—The quantity of matter contained by the body is weight. Body weight of male and female subjects (in Kg) of different ages is measured by employing a calibrated weighing scale.

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4. Stature—Stature is the vertical distance (in cm) from the standing surface to the vertex of the head when the subject stands erect and looks straight forward.

5. BMR—Basal Metabolic Rate is the number of calories required to keep your body functioning at rest, also known as the metabolism. It is related to body mass, age, weight, and height. It is also affected by gender. By Harris Benedict Equations, BMR for a female is represented by the following equations:

For female - BMR= 655.1 + (9.6 x Weight) + (1.8 x Height) - (4.7 x Age)

VO2max- Also known as maximal oxygen consumption, maximal oxygen uptake, peak oxygen uptake or maximal aerobic capacity. It is the maximum rate of O2 consumption measured during any physical operation (here implies the weeding operation). The name is derived from V- volume, O2- oxygen and max- maximum. VO2max is expressed in liters of oxygen per minute (L/min). It can also be expressed in mL/kg min

VO2max is determined in the research study by utilizing the Uth- Sorensen- Overgaard- Pedersen estimation, the equation is based on maximum and resting heart rates and proposed by a group of researchers from Denmark. It is given by:

VO2max ≈ (HRmax / HRrest) x 15.3 mL/kg minute

This equation for VO2max is applicable only for the subjects having ages between 21 to 51 only.

6. AWL—AWL stands for the acceptable work load. It is equal to 35% of the VO2max of the subjects (for young Indian worker).

7. Maximum heart rate—In the concerned research, it was determined by utilizing the formula derived by Maritz et al. (1961)

HRm = 220-Age (years)

8. Energy Expenditure Rate (EER)—EER is determined and estimated using the following formula proposed by Verghese et. al (1944) in studying the EER of the workers.

EER = 0.159 X Average heart rate - 8.72 (KJ/min)

9. Oxygen Consumption Rate (OCR)—Computed from the heart rate values (previously measured of the operator subject. OCR is represented by the equation (Singh et al, 2008) enumerated as follows:

OCR (L/min) = 0.0114 X HR - 0.68

10. Cardiac cost of work (CCW)—CCW is determined by employing the following relation: CCW = AHR * Duration of activity AHR = Average Heart Rate (beats/min) Duration of activity = 20minutes (weeding activity is performed for a duration of 20min in the study work) and AHR = Average working heart rate - Average resting heart rate

CCW = AHR x Duration of activity AH

Determining the data pertaining to anthropometric dimensions/ parameters:

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Table 3: Anthropometric and Strength Data of Female Respondents

S.No Anthropometric & Strength Data Age of Female Operators

1 Weight(kg) 25 30 35 40 45 50

2 Height (cm) 44 46 46 55 62 30

3 Elbow height(cm) 158 143 153 138 148 143

4 Olecranon height(cm) 101 91 98 85 96 94

5 Illiocrystable height(cm) 95 81 97 84 92 91

6 Illiospinal height(cm) 88 79 88 79 87 87

7 Knee height(cm) 125 122 143 118 123 125

8 Arm reach(cm) 43 43 48 41 43 40

9 Vertical reach(cm) 72 66 67 63 63 67

10 Hand length(cm) 190 182 187 187 193 182

11 Head length(cm) 63 64 66 62 64 66

12 Foot length(cm) 19 17 18 18 19 18

13 Biacromial breadth(cm) 23 22 24 21 24 23

14 Bideltoid breadth(cm) 31 29 38 47 39 28

15 Acromial height(cm) 39 33 33 42 33 36

16 Eye height(cm) 123 118 127 102 122 121

RESULTS AND DISCUSSIONSThe results obtained from the present investigation as well as relevant discussion have been summarized in this chapter. The factors taken under consideration in this concern research study are analyzed and the inferences have been drawn pertinent to various physical and physiological parameters.

Regarding assessment of the physical properties of the female subjects: -

The BMI values calculated for female subjects of age 25, 30, 35, 40, 45 and 50 were 17.63, 22.49,19.65,28.88, 28.31 and 14.67 respectively. The average value of BMI for the respondents was found to be 21.92. Hence, we conclude that the values of BMI for the female subjects lie within the normal range between 18.5-25 (WHO 2006). Only the female subject of age 45 was found to be underweighted i.e. BMI of 14.67.

Table (4) Assessment of Physical Characteristics of the Female Operators

S.no Physical characteristics Age (years) Average

1 Age (years) 25 30 35 40 45 50

2 Height (cm) 158 143 153 138 148 143 147.17

3 Weight (kg) 44 46 46 55 62 30 47.17

4 BMI (kg/m²) 17.63 22.49 19.65 28.88 28.31 14.67 21.94

5 LBM 35.78 30.1 34.28 30.67 36.92 25.37 32.19

6 BMR 654.81 623.51 618.01 653.91 715.61 375.91 606.96

7 VO2max (ml/Kg.min) 27.88 28.18 28.49 28.83 25.57 26.58 27.59

8 AWL 11.14 11.32 11.92 10.31 9.79 8.86 10.56

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The calculated value of LBM of various ages 25,30,35,40,45 and 50 for subjects were 35.78, 30.10, 34.28, 30.67, 36.92, 25.37 and 32.19 respectively. The average LBM value of the respondents was 32.19 respectively for different ages 25-50 years. From the estimated values of LBM, the percentage of LBM in the body weights for female subjects of aforesaid ages was 81%, 65%, 75%, 56%,60%, and 85% respectively. Also, for female subjects of ages 25 and 30 have an average percentage of LBM above 80, so they are considered to be healthy and physically fit. While for female subjects of ages 30,35,40 and 45 have percentage less than the specified limits, so they are considered to be unhealthy and unfit when it comes to physical characteristics (National Academy of Sports Medicine 2006).

From the analysis, the values pertaining BMR for the respondents of above-enlisted ages were 654.81, 623.51, 618.01, 653.91, 715.61 and 375.91 respectively. The average BMR value calculated was 606.96.

The VO2max values the respondents lies between 25 and 35 mL/Kg Min. The average VO2max was 31.82 (VO2max, 28 for women of age between 20-29 is considered fair–Astrand - 1960). It is concluded that in the range of 30-39 mL/kg min, the female subject has an average value of VO2max. As the age progresses, the female subjects have quite fair VO2max. The acceptable work load for Indian worker is about 35% of VO2max. Hence, for the mentioned values of VO2max, the AWL of the respondents having age 25,30,35,40,45 and 50 was 11.4, 11.32, 11.92, 10.31, 9.79 and 8.86 respectively. The average value of AWL for the operator was 10.56.

regArding the ASSeSSment of phySiologicAl propertieS of the femAle SuBJectS

The values of average resting heart rate of subjects having age 25, 30, 35, 40, 45 and 50 were analyzed as 87, 85, 89, 92, 95 and 96 respectively. During weeding activity by hand hoe, the average of all the respondents was 90.67 bpm. While, in the case of wheel hoe, the value of average resting heart rate was 93 bpm. Similar results were obtained by Bini Sam et. al. (2013). For the female respondents of the above-enlisted range of age, the average working heart rate values were recorded as 96, 98, 101, 105, 106 and 111(bpm) respectively under weeding operation conducted by hand hoe and 102, 103, 107, 111, 114 and 121(bpm) respectively when accomplishing weeding work by means of wheel hoe. The result obtained is quite similar to that of Saha et. al. (1979) and Verma S. et al. (2011). The results depict that heart rate values lie within the acceptable limits.

Table 5: The Assessment of Physiological Responses of The Female Respondents Employing Hand and Wheel Hoe

a Weeding activity by hand hoe (khurpa)

Physiological parameters Age (years)

25 30 35 40 45 50 Avg.

1 Average resting heart rate (AR) (beats/min) 87 85 89 92 95 96 90.67

2 Average working heart rate (AW) 96 98 105 105 106 111 102.83

3 Average heart rate (AHR) (beats/min) 9 13 12 13 11 15 12.16

4 Average resting blood pressure (SR)(mm of Hg) 106 113 112 119 120 118 117

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5 Average working blood pressure (SW) 115 121 126 128 131 136 122.5

6 Average resting blood pressure (DR) 73 80 91 85 82 82 82.17

7 Average working blood pressure (DW) 79 85 92 89 96 95 89.33

8 Energy Expenditure Rate (kJ/min) 7.6 7.7 7.8 8.0 8.1 8.9 8.02

9 Oxygen Consumption Rate (L/min) 0.6 0.6 0.7 0.9 0.9 1.1 0.8

10 Cardiac Cost of Work(beats) 180 260 240 260 220 300 243.2

(b) Weeding Activity by Wheel Hoe

Physiological parameters Age (years)

25 30 35 40 45 50 Avg.

1 Average resting heart rate (AR) (beats/min) 89 86 91 96 98 99 93

2 Average working heart rate (AW) 102 103 107 111 114 121 109.66

3 Average heart rate (AHR) 13 17 15 15 16 19 16.16

4 Average resting blood pressure (SR)(mm of Hg) 109 129 120 120 120 108 117.7

5 Average working blood pressure (SW) 118 133 123 127 122 117 123.3

6 Average resting blood pressure (DR) 74 82 94 85 82 81 83

7 Average working blood pressure (DW) 81 86 97 89 95 86 89

8 Energy Expenditure Rate (kJ/min) 7.9 8.0 8.3 8.9 9.5 10.1 8.78

9 Oxygen Consumption Rate (L/min) 0.7 0.8 1.0 1.1 1.2 1.4 1.1

10 Cardiac Cost of Work(beats) 260 340 300 300 320 380 316.7

The mean value of the average working heart rate during weeding task by hand hoe and wheel hoe was calculated as 102.83 and 109.66 (bpm) respectively. Therefore, the subjects were more comfortable and quite familiar while accomplishing operation by hand hoe as it involves a light work load rather than by wheel hoe involving moderate work (Verghese et. al(1944).

The average difference of working and resting heart rates accomplishing weeding activity by hand hoe and wheel hoe was 12.16 and 16.16 respectively. The difference in the value might

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be due to readability and ease to carry the task by hand hoe more effectively than that by wheel hoe and a moderate effort needed to manipulate the wheel hoe in the salt clay soil.

The values of average blood pressure (systolic) of the female respondents of the aforementioned ages were recorded as 115, 131, 122, 113, 123 and 131 (mm of Hg) respectively during the course of the duration of 20 minutes by hand hoe. For wheel hoe, the measured values for the same duration were found to be 118, 133, 123, 112, 122 and 136 (mm of Hg) for females respectively. The mean value of average working blood pressure (systolic) for the female subjects undergoing weeding work by hand hoe and wheel hoe was 121.33 and 120.83 (mm of Hg) respectively. Therefore, it may be concluded that female respondents were more compatible while accomplishing operation by hand hoe rather than by wheel hoe. This may be due to thigh and knee problems encountered during standing posture in performing wheel hoe.

The EER values of the given ages under weeding operation by hand hoe were tabulated as 7.6, 7.7, 7.8, 8.0, 8.1 and 8.9 (kJ/ min) respectively and conducting weeding operation by utilizing wheel hoe, the values of EER were 7.9, 8.0, 8.3, 8.9, 9.5 and 10.1 respectively. Therefore, the average value of EER for female respondents during weeding activity conducted by hand and wheel hoe were 8.02 and 8.78 (kJ/ min) respectively. The validation of the calculated result satisfies the similar results by Nag et.al. (1980) and Verma S. et al. (2011). Hence, it is concluded that the subjects consume the maximum amount of energy in carrying weeding operation by wheel hoe than by hand hoe (khurpa). This might be due to the additional effort needed by the shoulder and arm to push the implement to uproot the weeds in the standing position. Also, handling problems were encountered owing to fatigue in arm and shoulder in case of wheel hoe.

For the above-enlisted ages, the OCR values under weeding operation by hand hoe were tabulated as 0.61, 0.65, 0.72, 0.91, 0.94 and 1.10(L/min) respectively and conducting weeding operation by utilizing wheel hoe, the values were 0.7, 0.8, 1.0, 1.1, 1.2 and 1.4 (L/min) respectively. Therefore, the average value of OCR of the respondents during weeding activity conducted by hand and wheel hoe were 0.80 and 1.1(L/ min) respectively. The OCR value was increased when the work is conducted by wheel hoe. The female subjects required more oxygen consumption while accomplishing work by wheel hoe as the activity involves moderately heavy physical work. This might be due to the large effort required to pull the wheel hoe and handling problems encountered owing to fatigue in arm and shoulder.

The CCW values calculated for hand hoe and wheel hoe were 180, 260, 240, 260, 220 and 300 (beats) and 260, 340, 300, 300, 320 and 380respectively. Therefore, the average value of CCW for the subjects during weeding operation conducted by hand and wheel hoe were 243.2 and 316.7 (beats) respectively. The cardiac cost of work was maximum when the subject carried out the work by wheel hoe rather than by hand hoe. Similar results were observed in the study conducted by Verma S. et al. (2011).

The body discomfort arising by hand hoe (khurpa) were fatigue in knee and shoulder while it was arm, knee, wrist, and shoulder in case of wheel hoe. This might be due to the easy adaptability and consistency in accomplishing the activity in sitting position in case of hand hoe rather than the difficulty in manipulating the wheel hoein standing posture owing to their past history relating to their health. The discomfort most prevalent among the respondents was at arm and shoulder and was reckoned maximum while employing wheel hoe in the salt clayey soil.

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Table 6: Enlisting the body Discomfort of the Female RespondentsAge By Hand hoe By Wheel hoe

25 Shoulder Arm, shoulder

30 - Arm

35 Neck, shoulder Knee, shoulder

40 - Shoulder

45 Knee Arm, shoulder

50 Right knee, shoulder Right knee, arm, wrist

CONCLUSION

The study regarding assessing of anthropometrical, physical and physiological parameters of the female respondents during weeding operation by hand hoe and wheel hoe was successfully accomplished. Variations in the physical and physiological characteristics are encountered. Therefore, the concern research study has the following inferences which are enumerated below: -

The physiological parameters including resting and working heart rates, blood pressure, energy expenditure rate, oxygen consumption rate and cardiac cost of work of the concerned subject were assessed and the respondents exhibit significant variations during their involvement in the operation conducted by hand hoe and wheel hoe. The subjects undergo light physical work in case of hand hoe and moderately heavy physical work in wheel hoe. The subjects were more compatible by hand hoe than by wheel hoe which might be due to their consistency and easy adaptability with the former implement in hard soil conditions. The latter implement required more effort on the shoulders of the subjects in the prevailing soil conditions which resulted in body discomfort and an increase in the physiological variables.

REFERENCES

[1] Agarwal S. (2007). Gender involvement in Farm Mechanization Issues forExtension and Research, NRC for women in Agriculture, Bhubneshwar, India, GiteVol II.

[2] Kumar A., Haribabu B., and A. Srinivasa Rao. (2013). Ergonomical evaluation of manually operated weeder under wet land condition, 8(6): 249-255 Astrand. ACTA PhysiolScand 49 (Suppl); VO2max Norms 169:1960. Reprinted with permission from Blackwell Scientific Publications LTD.

[3] Martitz, J.S., Morrison, J.F., Peter, J., Strydom, N.B. and Whyndham, C.H. (1961). A practical method of estimating individual’s maximal oxygen uptake. Ergonomics, 4: 97.

[4] Nag, P.K. and Dutt, P. (1979). Effectiveness of some simple agricultural weeders with reference to physiological responses. J. Human Ergology, 8 (1): 13-21.

[5] Nag, P.K. and Dutt, P. (1979). Cardio-respiratory efficiency in some agricultural work. Appl. Ergonomics, 11 (2): 81-84.

[6] Saha, P.N. (1976). The practical use of some physiological research methods for assessment of work stress. J. Indian Assoc. Physiotherapists, 4: 9-13.

[7] Sam B. (2015). Ergonomic evaluation of paddy seeder and rotary with female operators. Farming Systems Research Station, Kerala Agricultural University, Sadanandapuram, Kottarakkara, Kerala, India

[8] Tiwari, V.K., Datta, R.K. and Murthy, A.S.R. (1991). Evaluation of three manually operated weeding devices. Applied Ergonomics, 22: 111-116.

[9] Varghese, M.A., Saha, P.N. and Atreya, N. (1994). A rapid appraisal of occupational workload from a modified scale of perceived exertion. Ergonomics, 37 (3): 485-491.

[10] Uth, N., Sorensen, H., Overgaard, K., Pendersen, P.K.,2005. Estimation of VO2max from the ratio between HRmax and HRmin- the heart rate ratio method. Eur. J Appl. Physiol., January;93(4): 508-9.

[11] World Health Organization (2006)“BMI Classification”.Global Database on Body Mass Index.

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Synthesis of Iron Oxide Nanoparticles using Leaf Extract of Ocimum sanctum for Wastewater Treatment

Surya Pratap Goutam1,*, Diptarka Roy1 and Gaurav Saxena2

1Advanced Materials Research Laboratory, Department of Applied Physics (DAP),

Babasaheb Bhimrao Ambedkar (Central) University, Lucknow–226 025, Uttar Pradesh, India

2Laboratory for Bioremediation and Metagenomics Research (LBMR), Department of Environmental Microbiology (DEM), Babasaheb Bhimrao Ambedkar (Central) University,

Vidya Vihar, Raebareli Road, Lucknow–226 025, Uttar Pradesh, IndiaE-mail: *[email protected]

ABSTRACT

The present investigation envisions the use of convenient, cheap and reliable preparative route for the fabrication of iron oxide nanoparticles (NPs) and their characterization through the reduction of ferric chloride for wastewater treatment. Iron oxide nanoparticles were synthesized by green method using nontoxic fresh leaf extract of Ocimum sanctum (Tulsi). Characterization of synthesized material has been done using different techniques such as scanning electron microscopy (SEM) and EDS and transmission electron microscopy (TEM). Morphological study indicates the spherical nature of the synthesized iron oxide nanoparticles. Further, the synthesized iron oxide NPs applied in wastewater treatment and showed 72.60% COD removal from municipal wastewater in a parabolic trough reactor during photocatalytic treatment. Thus, the synthesized iron oxide NPs could be utilized in wastewater treatment.

Keywords: Green Synthesis, Iron Oxide Nanoparticles, Ocimum sanctum, Wastewater Treatment

INTRODUCTION

Nanoparticles are being viewed as basic building blocks of nanoscience and nanotechnology. Most important and distinctive feature of nanoparticles is that, they display larger surface area to volume ratio and size-dependent properties (Salata 2004). Owing to their unusual and improved properties based on specific characteristics such as size, distribution and morphology, nanomaterials have extensive effect in areas of physics, chemical science, electronics, optics, materials science and biomedical science and many more (Shah et al., 2014; Duanet al., 2013; Lisiecki et al., 1996). Iron oxides have considerably attracted scientific community because of their multivalent oxidation forms (Hafeli et al., 1997) as wustite (FeO), magnetite (Fe3O4), magnetite (γ-Fe2O3) and hematite (α-Fe2O3) in atmosphere with various potential applications in spintronics, agricultural, magnetic refrigeration, gassensing, ferrofluids, catalysts (Lisiecki et al., 1996; Hafeli et al., 1997; Hsu et al., 2008; Guoa et al., 2012) and in many biomedical applications such as tissue repair, targeted drug delivery, hyperthermia, cellular therapy and

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Synthesis of Iron Oxide Nanoparticles using Leaf Extract of Ocimum sanctum for Wastewater Treatment 273

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magnetic resonance imaging (Guoa et al.,2012; Dobosz et al., 2014). Higher surface area of iron oxide at nano range increased their effectiveness, catalytic reactivity and other important properties due to their increased surface energy. Iron oxide nanoparticles play a crucial role in environmental remediation cycles and easily oxidized because of its high catalytic reactivity (Kim et al., 2001). It removes both of organic and inorganic pollutants from polluted water (Saha and Bhunia 2013; Salam et al., 2012).

Conventional methods (physical and chemical) are more popular for nanoparticles synthesis but the use of expensive and often toxic compounds, complicated synthetic steps, high reaction temperatures and pressure etc. limits their applications. Due to toxic effects of conventional methods, we have focused on an attractive alternative to the traditional techniques using a green, safe, and cost effective and ecofriendly technology based on biological systems such as plants, bacteria, fungus and other organisms. Nanoparticles synthesis using plant extracts is often termed as green synthesis that is compatible with the green chemistry principles. In biosynthesis, metal ions are reduced into their nanoparticles by biomolecules (alkaloids, flavonoids, phenols, tannins, quinines, terpenoids etc.) (Sun et al., 2000). Currently, there are several methods described in literature for the synthesis of iron oxide nanoparticles of different compositions, which include chemical, physical and hybrid method.

Ocimum sanctum plant is cultivated for medicine purposes and its essential oil (Fig. 1). It is also used as an herbal tea, commonly used in Ayurveda (Warrier 1995). Although production of iron nanoparticles using plant extracts has been reported, this technology needs further improvement in order to obtain stable nanoparticles of controlled size and morphology, which would be advantageous to large-scale synthesis of iron nanoparticles for environmental remediation and hazardous waste treatment applications.This study aims to synthesize iron oxide nanoparticles by green Ocimum sanctum leaves extracts, their characterization and application in wastewater treatment.

Fig. 1: Image of Plant Ocimum sanctum (Tulsi)


mAteriAlS And chArActerizAtion techniQueS

Ferric chloride and sodium hydroxide from Fisher Scientific (U.K.) were used in the experiments for the synthesis of iron oxide nanoparticles. Municipal wastewater collected from local drain in nearby area. Further, surface morphology and composition of the synthesized nanoparticles were examined with powder scanning electron microscopy (SEM), Transmission electron

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Microscopy (TEM) and energy-dispersive spectrometry (EDS). SEM images were captured on a LEO 435 VP instrument operated at 25 kV; EDS was carried out by JEOL JXA-8100 EPMA. Transmission Electron Microscopy (TEM) was performed by high resolution HRTEM-200 KV, TECNAI G2, S-TWIN, FEI, Holland.

prepArAtion of leAf extrAct

For the preparation of the Ocimum sanctum leaf extract, 5 g of fresh, sparkling leaves were collected. The leaves were cut into fine pieces and heated with 50 ml of double distilled water at the temperature 80 °C for 1 hour. After completion of heating process, the aqueous solution was filtrated to collect the leaf extract (Goutam et al., 2018).

plAnt mediAted SyntheSiS of iron oxide nAnopArticleS

To synthesize iron oxide nanoparticles, firstly 0.1 M aqueous solution of ferric chloride (FeCl3) was prepared. Then Ocimum sanctum leaf extract was added with the aqueous solution of ferric chloride. The mixture was kept under constant stirring at room temperature for 2 hours. It was to be noted that the colour of brownish aqueous solution of FeCl3 was changed in dark after the addition of leaf extract due to reduction of iron ions. After completion of that reaction procedure, to get precipitate 15 ml of 0.5 M NaOH solution was added drop wise. The precipitate was collected using Whatman filter paper and dried at room temperature for two days, then annealed at temperature 500 °C for 5 hours in a Muffle furnace (Balamurughan et al., 2014; Iravani 2011). There after the sample was gently rubbed with the help of a mortar and pastel to get the iron oxide nanoparticles in powder form (Fig. 2).

Fig. 2: Diagram for the Synthesis Process of Iron Oxide Nanoparticles using Ocimum sanctum (Tulsi) Leaves

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WASTEWATER TREATMENT

The green synthesized iron oxide NPs were further applied in municipal wastewater treatment focusing the chemical oxygen demand (COD) removal. COD removal before and after photocatalytic treatment was determined as per protocol stated in “Standard Methods for Examination of Water and Wastewater” (APHA 2012). The wastewater treatment process was accomplished in a self designed and fabricated parabolic trough reactor (PTR) up to six hrs. The figure, dimensions and details of PTR used in the photocatalytic treatment can be found in Goutam et al. (2018).


Results of morphological and structural studies using SEM depicted in Fig. 3. In these images, the formation of spherical identities were observed. Size of the some spherical identities is in the order of few micrometers to nanometer. There was a agglomeration observed in the iron oxide nanoparticles to some extent agglomerated due to the interaction between magnetic nanoparticles.

Fig. 3: SEM Images of Synthesized Iron Oxide Nanoparticles

The chemical compositions of synthesized sample were examined by EDS spectra and display in Fig. 4. The spectra revealed the composition of the sample and confirm presence of iron (Fe) and Oxygen (O) in the sample.

Fig. 4: EDS Spectra of Synthesized Iron Oxide Nanoparticles

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TEM images showed morphology and size distribution of synthesized iron oxide nanoparticles as shown in Fig. 5. The TEM image confirmed the nanoscale dimension of the synthesized particles. The size, shape and heterogeneous distribution of particles may be attributed to the experimental parameters such as the reaction temperature, the pH value etc., and their relative rates of nucleation and growth processes and also to the extent of agglomeration due to the higher activity of iron.

Fig. 5: TEM Image of Synthesized Iron Oxide Nanoparticles

Further, the synthesized iron oxide NPs were applied in municipal wastewater treatment in a PTR and wastewater treatment was mainly analyzed in terms of COD removal. The COD removal efficiency before and after photocatalytic treatment was determined according to the following equation:

COD Removal Efficiency (%) = Ci-Cf/Ci × 100 (1)

Where Ci is the initial concentration of COD in municipal wastewater before the photocatalytic treatment and Cf is the residual concentration of COD in municipal wastewater after the photocatalytic treatment.

COD value in the municipal wastewater sample collected from a local drain was found to be 412 mg/L. However, after photocatalytic treatment with green synthesized iron oxide NPs, the COD was found to be 112.88 mg/L. Large surface area might be the responsible cause for the adsorption of pollutants from municipal wastewater and thus, represent 72.60% COD removal from municipal wastewater within six hrs. Overall, the green synthesized iron oxide NPs clearly showed the potential for wastewater treatment.

CONCLUSION

In conclusion, synthesis of iron oxide nanoparticles using Ocimum sanctum is cost effective, environment-friendly and an efficient alternative at large scale. Among the diverse synthetic approaches, the plant photochemical with antioxidant property is accountable for the preparation of iron oxide nanoparticles. TEM image confirms the nanoscale dimension of the synthesized particles. Application of green synthesized iron oxide NPs removed 72.60% COD removal from municipal wastewater; thus, represent a clean-green solution for wastewater management.

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ACKNOWLEDGMENTS

Authors are extremely grateful to University Grant Commission (UGC), Government of India (GOI), New Delhi, India for financial support.

REFERENCES

[1] Salata O.V., 2004. Applications of nanoparticles in biology and medicine. J Nanobiotechnology. 2(1):3.

[2] Shah S., Dasgupta S., Chakraborty M., Vadakkekara R., Hajoori M., 2014. Green Synthesis of Iron Oxide Nanoparticles Using Plant extracts, International journal of Biological & Pharmaceutical Research. 5(6):549-552.

[3] Duan S., Wang R., 2013. Bimetallic nanostructures with magnetic and noble metals and their physicochemical applications, Progress in Natural Science: Materials International. 23 (2):113-126.

[4] LisieckiI., Billoudet F., Pileni M. P., 1996. Control of the Shape and the Size of Copper Metallic Particles. J. Phys. Chem.100, 4160-4166.

[5] Hafeli U., Schütt W., Teller J., Zborowski M., 1997. Scientific and clinical application of magnetic carriers, Plenum press, New York, ISBN-978-1-4419-3283-9.

[6] Hsu L.C., Li Y.Y., Lo C.G., Huang C.W., Chern G., 2008. Thermal growth and magnetic characterization of á-Fe2O3 nanowires, J. Phys. D: Appl. Phys. 41 185003-185007.

[7] Guoa J., Wang R., Tjiu W.W., Pan J., Liu T., 2012. Synthesis of Fe nanoparticles@graphene composites for environmental applications. J. Hazard. Mater. 225-226, 63-73.

[8] Dobosz B., Krzyminiewski R., Schroeder G., Kurczewska J., 2014. Electron paramagnetic resonance as an effective method for a characterization of functionalized iron oxide, Journal of Physics and Chemistry of Solids75, 594-598.

[9] Kim D.K., Zhang Y., Voit W., Rao K.V., Kehr J., Bjelke B., Mohamed M., 2001. Superparamagnetic iron oxide nanoparticles for bio-medical applications. Scr. Mater. 44, 1713-1717.

[10] Saha S.., Bhunia A.K., 2013. Synthesis of Fe2O3 Nanoparticles and Study of its Structural, Optical Properties, Journal of Physical Sciences.17,191-195.

[11] Salam H.A., Rajiv P. Kamaraj M., Jagadeeswaran P., Gunalan S. Sivaraj R., 2012. Plants: Green route for nanoparticle synthesis. Int. J. Biol. Sci. 1, 85-90.

[12] Sun S.H., Murray C.B., Weller D., Folks L., Moser A., 2000. Mono-disperse Fe-Pt nanoparticles and ferromagnetic Fe-Pt nanocrystals superlattices. Science, 287, 1989-1992.

[13] Warrier P. K., 1995. Indian Medicinal Plants. Orient Longman. p. 168. ISBN 0-86311-551-9.[14] Goutam S.P., Saxena G., Singh V., Yadav A.K., Bharagava R.N., Thapa K.B., 2018. Green synthesis

of TiO2 nanoparticles using leaf extract of Jatropha curcas L. for photocatalytic degradation of tannery wastewater. Chemical Engineering Journal 336, 386-396.

[15] Balamurughan M.G., Mohanraj S., Kodhaiyolii S., Pugalenthi V., 2014. Ocimum sanctum leaf extract mediated green synthesis of iron oxide nanoparticles: spectroscopic and microscopic studies, Journal of Chemical and Pharmaceutical Sciences, ISSN: 0974-2115.

[16] Iravani S., 2011. Green synthesis of metal nanoparticles using plants, Green Chemistry, 13, 2638-2650.

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Isolation and Characterization of Bacteria Capable for COD Removal from Tannery Wastewater: A Bioremediation Study

Gaurav Saxena1,*, Chhatarpal Singh1, Vineet Kumar2 and Ram Naresh Bharagava1

1Department of Microbiology (DM), Babasaheb Bhimrao Ambedkar (Central) University,

Vidya Vihar, Raebareli Road, Lucknow–226 025, Uttar Pradesh, India1,2Department of Microbiology,

Dr. Shakuntala Mishra National Rehabilitation University, Mohaan Road, Lucknow–226 017, Uttar Pradesh, India


ABSTRACT

Industrial effluents are considered to be the major sources of environmental pollution. These also create severe toxic effects in living beings and thus, their proper treatment and management is matter of concern in present days. Currently, physico-chemical approaches are being applied for the treatment and management of industrial effluents, but are costly, environmentally destructive, and use a huge quantity of chemicals that may itself cause secondary pollution. Thus, there is an urgent need of some ecofriendly solutions to manage such high strength industrial effluents. However, microbes can play an important role in the degradation and detoxification of industrial effluents. In the present investigation, a gram-negative bacterial strain GS12 was isolated from secondary treated tannery effluent of a common effluent treatment plant (CETP) of tannery industries, located at Unnao, India. The isolated bacterial strain GS12 was further characterized based on the morphological and biochemical tests and identified as Bacillus sp.Further, the isolated bacterium was employed for the degradation of tannery effluent in the optimized conditions and biodegradation was assessed in terms of chemical oxygen demand (COD) removal from wastewater. A maximum COD removal upto 71.82% was recorded after the bacterial treatment at optimized conditions, representing an excellent bioremediation potential. In conclusion, the isolated bacterium, Bacillus sp.can be employed at large scale for the bioremediation of TWW not only for pollution prevention, but also public health safety.

INTRODUCTION

Leather industries (LIs) play an important role in the national economy of many developing countries. Regrettably, LIs are also the major pollution causing industries in the world. LIs are mainly concerned with the production finished leather or leather products. During leather production process, a variety of highly toxic chemicals such as heavy metals especially, chromium (Cr), phenolics and a variety of highly toxic and recalcitrant pollutants, are beings used in tanning process and often discharged along with wastewater into the environment where they create serious ecotoxicological effects in the environment and the toxicity in living beings upon exposure (Goutam et al. 2018; Bharagava et al., 2017a; Gautam et al. 2017; Saxena et al., 2016; Saxena and Bharagava 2015).

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TWW causes serious soil and water pollution. It (Bharagava et al., 2016) (a) cause a huge foaming problem on surface waters; (b) inhibit the nitrification process; (c) blocks sunlight penetration due to its dark brown color, and thus, reduces the photosynthetic activity and oxygenation of receiving water bodies and hence, becomes detrimental to aquatic life; (d) causes depletion in dissolved oxygen that encourages the anaerobic condition, which leads to the putrefying odour of receiving water bodies; (e) causes eutrophication of water bodies and thus adversely affecting the ecological functioning of aquatic resources; (f) causes salinisation of soil (acidification, reduce soil fertility) and water due to its highly saline nature (salt concentration); (g) causes ground water pollution due to leaching of highly toxic chromium (Cr) to the deeper layer of soil; (h) causes the deficiency of some micronutrients in soil such as zinc (Zn), copper (Cu) and iron (Fe) etc.; and (i) alters the structure of soil microbial communities and reduces their growth and finally retards the bioremediation process due to its high chromium content.

TWW also cause serious toxicity in living beings. It has been reported to (a) cause genotoxicity and mutagenicity in fish, Oreochromis niloticus (Matsumoto et al., 2006); (b) disturb protein metabolism in fresh water teleost, Cirrhinus mrigala (Ham.) (Afaq and Rana (2009); (c) cause hematotoxicity in the fresh water fish, Labeo rohita (Hamilton) (Praveena et al., 2013); (d) interfere metabolic processes by altering the activity of oxidative enzymes in different organs of guppy fish, Poecilia reticulate (Aich et al., 2011; 2015); (e) disrupts the several physiological and cytological processes in plants (Saxena et al., 2016); (f) disturb the delicate hormonal balance (endocrine disruption in rats) and compromise the reproductive fitness of living beings (Kumar et al., 2008); (g) causes embryonic toxicity coagulation of fertilized eggs, detachment of tail-bud from the yolk sac, yolk sack edema, malformation of the tail, scoliosis, and deformation of swim bladder in the embryos of zebra fish, Danio rerio (Rocha and De Oliveira, 2017); (h) causes reduction in the diversity of macroinvertebrates (Wosnie and Wondie, 2014); (i) cause acute embryo-toxicity and developmental defects in the sea urchins (Paracentrotus lividius and Sphaerechinus granularis) and serious toxicity in Daphnia magna (Oral et al., 2007); and (j) cause detrimental changes in the biochemical parameters, damage to gonad and mantle tissues, and also genotoxic effects in the snail, Pila globosa (Bhattacharya et al., 2016). Such toxic effects caused by TWW makes it a serious pollutant and hence, its adequate treatment to its final disposal into the environment is required to combat the environmental threats and protect the public health.

Microbes can play an important role in the effective degradation and detoxification of TWW as compared to currently applied physico-chemical approaches that are costly and causes secondary pollution. Therefore, the present study was to isolate and characterize the potential bacteria capable for reducing chemical oxygen demand (COD) from TWW for environmental safety.


The TWW sample (after secondary/biological treatment) was collected in pre-sterilized clean containers (capacity 20 l; Tarson Production Pvt. Ltd., USA) from the outlet of CETP located at Unnao (26.48o N, 80.43o E), Uttar Pradesh, India. The CETP is relied on the activated sludge treatment process (ASTP) and used to treat ~1.9 MLD of wastewater against a designed flow of 2.15 MLD. The CETP receives wastewater from a cluster of ~21. The collected TWW samples were immediately brought to the laboratory, stored at 4°C and used for the analysis of chemical oxygen demand (COD) and bioremediation study.

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The collected TWW samples were analyzed in three replicates for COD analysis to know the strength of pollution as per the standard protocols outlined in the “Standard Methods for Examination of Water and Wastewater” (APHA 2012). The open reflux method was used for the analysis of COD.

For bioremediation study, potential bacteria were isolated from contaminated TWW. For this, enrichment and serial dilution method was performed.Approx. 1 ml of suspension was mixed with 9 ml of distilled water and serially diluted. From the different dilution, 1 ml of sample was pour plated with nutrient agar and incubated for 24 h at 30°C to observe the development of colonies. Further, morphologically distinct colonies among the developed bacterial colonies were selected based on the colony morphology and then cultured by streak plate method on nutrient agar plate.

Further, the isolated bacteria were screened for the COD removal efficiency and treatability for TWW. For this, erlenmeyer flasks containing 100 ml of TWW at pH 7.0 were taken and supplemented with glucose (1%) as an extra carbon source. After that, the isolated bacteria were pre-cultured in the MSM broth. The composition of MSM broth was: Na2HPO4: 0.24 g, KH2PO4: 0.20 g, MgSO4: 0.001 g, CaCl2: 0.001 g, NH4NO3: 0.01 g, Glucose: 1 g, Peptone 0.25 g/100 ml. Further, all the flasks were individually inoculated with 10 ml of two days old pre-cultures of isolated bacteria and kept in incubator shaker at 32°C for five days. On the fifth day, the wastewater sample was taken out from the flasks for the determination of COD removal efficiency to define the treatability for TWW. Flasks containing effluent without nutrients and bacterial cultures were also kept in the same conditions as a negative control.

Further, the potential bacteria were selected for bioremediation studies were characterized by morphological and biochemical tests. The bacterium that found to remove maximum COD from TWW was further selected for bioremediation studies. The bioremediation of TWW was performed in the optimized conditions and assessed in terms of COD removal.


The physico-chemical analysis of TWW has revealed that it has highCOD (1248mgl-1), which was found to be higher than the recommended permissible values for industrial discharge (120 mgl-1 as per USEPA 2000). The high COD value of TWW might be due to the high organic content, unknown ROPs, dissolved minerals, and salts, which are responsible for serious soil and water pollution.

In the present study, a total of three (03) bacteria (GS12, GS13, & GS14) were isolated on the basis of distinct morphological appearance on nutrient agar plate and screened for the COD removal efficiency. Out of the three bacterial isolates,one bacterial isolate GS12 exhibited maximum COD removal up to 68.42%. The isolated bacterium GS12 was found gram-positive and rod-shaped and identified as Bacillus sp. and other test are listed in Table 1. After that, the isolated bacterium was optimized at temperature, pH and shaking speed for bioremediation studies. Further, the bioremediation experiment was performed to determine the treatability of isolated bacterium GS12 for TWW. After optimizationat different environmental parameters (temp.: 35, pH: 7.2, shaking speed: 120), the bacterial isolate GS12 showed 71.82% COD removal from TWW. Thus, the isolated bacterium GS12 successfully showed the bioremediation potential for TWW and can be used as a bioremediating agent for effluent treatment at large scale.

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Isolation and Characterization of Bacteria Capable for COD Removal from Tannery Wastewater 281

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Table 1: Morphological and Biochemical Characteristics of Bacterial Isolate GS12

Malonate -

Voges Proskauer’s +

Citrate utilization +

ONPG -

Nitrate Reduction +

Catalase +

Urease -

Arginine -

Sucrose +

Mannitol -

Glucose +

Arabinose -

Trehalose +

+: Positive;-: Negative

CONCLUSION AND RECOMMENDATION

The present study was to isolate and characterize the potential bacteria for the bioremediation of TWW. From this study, the following conclusions and recommendations can be drawn:

(a) Physico-chemical characterization of TWW reported that it has very high COD value beyond the permissible limits and thus, it is not suitable for discharge in receiving environment and require further treatment for environmental safety.

(b) The isolated bacterium GS12 was found capable to remove COD up to 71.82% and thus, showed astounding potential for bioremediation of TWW.

(c) Further, optimization studies are required in details to optimize the bacterial isolate GS12 for large scale treatment of TWW for environmental safety and public health protection.

REFERENCES

[1] Afaq S., Rana K.S. (2009). Impact of leather dyes on total protein of fresh water teleost, Cirrhinus mrigala (Ham.). Asian J Exp Sci 23(1):299-302.

[2] Aich A., Chattopadhyay B., Datta S., Mukhopadhyay S.K. (2011). Impact of composite tannery effluent on the amino-transferase activities in a fish biosystem, using Guppy fish (Poecilia reticulata) as an experimental model. Toxicol Environ Chem 93(1):85-91.

[3] Aich A., Goswami A.R., Roy U.S., Mukhopadhyay S.K. (2015). Ecotoxicological assessment of tannery effluent using guppy fish (Poecilia reticulata) as an experimental model: a biomarker study. J Toxicol Environ Health A 78(4):278-286.

[4] APHA (American Public Health Association) (2012). Standard method for examination of water and wastewater, 22nd edn. American Public Health Association, Washington.

[5] Bharagava R.N., Saxena G., Mulla S.I., Patel D.K. (2017a). Characterization and identification of recalcitrant organic pollutants (ROPs) in tannery wastewater and its phytotoxicity evaluation for environmental safety. Arch Environ Contam Toxicol. doi:10.1007/s00244-017-0490-x

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[6] Bhattacharya P., Swarnakar S., Mukhopadhyay A., Ghosh S. (2016). Exposure of composite tannery effluent on snail, Pila globosa: a comparative assessment of toxic impacts of the untreated and membrane treated effluents. Ecotoxicol Environ Saf 126:45–55.

[7] Gautam S., Kaithwas G., Bharagava R.N., Saxena G. (2017). Pollutants in tannery wastewater, pharmacological effects and bioremediation approaches for human health protection and environmental safety, In: Bharagava RN (ed) Environmental pollutants and their bioremediation approaches, 1st edn. CRC Press, Taylor & Francis Group, USA, p. 369-396. doi:10.1201/9781315173351-14

[8] Goutam S.P., Saxena G., Singh V., Yadav A.K., Bharagava R.N. (2018). Green synthesis of TiO2 nanoparticles using leaf extract of Jatropha curcas L. for photocatalytic degradation of tannery wastewater. Chem Eng J 336:386-396. doi:10.1016/j.cej.2017.12.029

[9] Kumar V., Majumdar C., Roy P. (2008) Effects of endocrine disrupting chemicals from leather industry effluents on male reproductive system. J Steroid Biochem Mol Biol 111(3-5):208-216.

[10] Matsumoto S.T., Mnlovani S.M., Malaguttii M.I.A., Dias A.L., Fonseca I.C., Morales M.A.M. (2006). Genotoxicity and mutagenicity of water contaminated with tannery effluent, as evaluated by the micronucleus test and comet assay using the fish Oreochromis niloticus and chromosome aberrations in onion root tips. Genet Mol Biol 29(1):148-158.

[11] Oral R., Meric S., De Nicola E., Petruzzelli D., Rocca C.D., Pagano G. (2007). Multi-species toxicity evaluation of a chromium-based leather tannery wastewater. Desalination 211:48-57.

[12] Praveena M., Sandeep V., Kavitha N., Jayantha Rao K. (2013). Impact of tannery effluent, chromium on hematological parameters in a fresh water fish, Labeo Rohita (Hamilton). Res J Animal Veterinary Fishery Sci 1(6):1-5.

[13] Rocha O.P., De Oliveira D.P. (2017). Investigation of a Brazilian tannery effluent by means of zebra fish (Danio rerio) embryo acute toxicity (FET) test. J Toxicol Environ Health Part A Curr Issues 80:1078-1085.

[14] Saxena G., Bharagava R.N. (2015). Persistent organic pollutants and bacterial communities present during the treatment of tannery wastewater. In: Chandra R (ed) Environmental waste management, 1st edn. CRC Press, Taylor & Francis Group, USA, p. 217-247. doi:10.1201/b19243-10

[15] Saxena G., Chandra R., Bharagava R.N. (2016). Environmental pollution, toxicity profile and treatment approaches for tannery wastewater and its chemical pollutants. Rev Environ Contam Toxicol 240:31-69. doi:10.1007/398_2015_5009

[16] USEPA (2002). The environment protection rules, 3A, schedule-II, III. U.S. Environmental Protection Agency, Office of research and development, Cincinnati.

[17] Wosnie A., Wondie A. (2014). Assessment of downstream impact of Bahir Dar tannery effluent on the head of Blue Nile River using macroinvertebrates as bioindicators. Int J Biodivers Conserv 6:342-350.

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Agro-industrial Waste as Source of Nutraceuticals and Health Promoting Molecules

Mamta Shukla1 and R.L. Singh2

1Department of Microbiology, Dr. Shakuntala Misra National Rehabilitation University,

Lucknow–2260172Department of Biochemistry,

Dr. RML Avadh University, Faizabad–224001E-mail: [email protected]

ABSTRACT

Oxidative stress via increased production of free radicals and other reactive oxygen species with decreased antioxidative defenses, is known to occur during fatal diseases. Numerous studies have shown that oxidative stress causes structural and functional alterations in molecular, cellular tissues and organ systems. Therefore functional foods which have antioxidant properties may be effective and useful for reducing the risk of fatal damage of oxidative stress. Herbal remedies are increasingly used by general public to replace or supplement conventional medicine and to protect from diseases caused by this damage. Antioxidants of plant origin are getting more importance in terms of their nutraceutical values because of their natural origin and no side effects. The present study was aimed to explore the antioxidant and nutraceutical properties of agrowaste part (Leaf, Twig and Bark) of three fruit plants. The concentrated extracts were primarily screened for polyphenolic content in dry weight (DW). In vitro antoxidant and DNA damage protection were further studied. In all the tested samples the total phenolic contentent (TPC) was found between 23.10-91.04mg of GAE/g of DW. In vitro antioxidant and DNA damage protective activity showed significant higher values mostly in leaf and barks extracts. The results showed that agrowaste part of plants have potential to serve as antioxidant and nutraceutical sources for pharmaceutical and food industries.

Keywords: Antioxidant, Total Phenolic Content, Agrowaste, DNA Damage, Oxidative Stress

INTRODUCTION

There is a cosiderable epidemiological evidence indicating association between diets rich in important phytochemicals and decreased risk of different diseases including cancers. Free radicals are generated continuously in the body due to metabolic reactions and diseases (Yeum et al., 2003). In order to protect themselves against free radicals, organism has endogenous and exogenous defense mechanisms. Yet these defense systems are not sufficient in critical situations of different stress levels, where the production of free radicals significantly increased (Monden et al., 1999). It has been reported that the diet rich in antioxidant phytochemical, such as polyphenolics, carotenoids, terpenoids and flavonoids protects against cellular damage due to ability to quench oxygen-derived free radicals (Dhakarey et al., 2005; Singh et al., 2009a).

Plants have played a significant role in maintaining human health and improving the quality of human life for thousands of years and have served to humans as valuable components of

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medicines, seasonings, beverages, cosmetics and dyes. In the aerobic environment, the most dangerous bye products are the species of reactive oxygen (ROS). The role of antioxidants is to detoxify reactive oxygen intermediates (ROI) in the body which produces in different metabolic activities (Halliwell & Gutteridge, 1999; Ames et al., 1993). Exogenous sources of ROS include tobacco smoke, certain pollutants, organic solvents, exposurue to sunlight, X-rays, ozone, auto-exhaust and pesticides. These ROS in the form of free radicals induces some oxidative damage to biomolecules like lipids, DNA, RNA, proteins and carbohydrates, resulting in more than 100 diseases (Block, 1992; Hertog et al., 1993; Bingham, et al., 2003).

The Carrissa carandus plant is native and common throughout much of Asia places. The common name of this plant is Karaunda in India. In India, it grows wild on the poorest and rockiest soils. The plant is straggly, woody, climbing shrub usually growing to 10 or 15 ft(3.5 m) high. Bark, leaves and fruits are alkaloid rich and also contain anthocyanin known as cyaniding 3-rhamnoglucoside works in different disease prevention. Aegle marmelos L., commonly known as bael, is a species of tree native to the Indian subcontinent and Southeast Asia. It is a deciduous shrub or small to medium-sized tree, up to 13m tall with slender drooping branches and rather shabby crown The bael tree contains furocoumarins, including xanthotoxol and the methyl ester of alloimperatorin, as well as flavonoids, rutin and marmesin etc. The sugar-apple, sweetsop, or custard apple is the fruit of Annona squamosa, the most widely grown species of Annona and a native of the tropical Americas and West Indies. Sugar-apple is high in energy, an excellent source of vitamin C. and manganese, a good source of thiamine and vitamin B6, and provides vitamin B2, B3 B5, B9, iron, magnesium, phosphorus and potassium in fair quantities. Plants with high antioxidant properties proved their strong candidature of its safe and effective nutraceutical values, which have still space to be explored. Considering this fact the present study was aimed to explore the antioxidant and nutraceutical properties of agrowaste part (Leaf, Twig and Bark) of these fruit plants.


Chemicals: Gallic acid and Bovine serum albumin (BSA) were procured from Sigma-Aldrich, St. Louis, USA., Folin Ciocalteau’s phenol reagents were the product of E. Merk, Mumbai, India. All other reagents and chemicals used were of analytical grade.

Sample Collection and Extraction: Sample was collected from the campus of Dr. RML Avadh University, Faizabad, U.P. and washed with tap water twice, dried, powdered and stored in polythene bags at 4oC. The powdered plant sample (50g) was extracted in a rotatory shaker at constant stirring rate for 2 days. The process was carried out thrice with 500 ml of hydroethanolic solvent (1:1). Solids were removed by filtration and the solvent of extracts was removed under reduced pressure at 150 PSI and 400C in a Buchi Rotavapor. The yield of powdered extracts were (2-6g) after solvent evaporation and further used for the experiments.

eStimAtion of AntioxidAnt StAtuS And dnA dAmAge protection totAl phenolic content (tpc)

TPC was measured with the method of Ragazzi and Veronese (1973). To 0.1 ml plant extract, 0.5 ml of Folin’s reagent (1N) and 1.0 ml of sodium carbonate was added subsequently. The test mixture was mixed properly and kept at room temperature for 30 minutes and made

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Agro-industrial Waste as Source of Nutraceuticals and Health Promoting Molecules 285

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up to 10 ml with distilled water. The absorbance of this solution was measured at 720 nm wavelengths. The TPC was reported as mg of gallic acid equivalent (GAE)/g of DW.

AntioxidAnt Activity By dpph method

Both 2, 2’-azinobis[3-ethylbenzothiazoline-6-suphonate] (ABTS) and 2, 2-diphenyl-1-picrylhydrazyl (DPPH) measure the total antioxidant activity (AOA) of the extracts in an organic medium. Therefore, antioxidant activity of the extracts was measured by using DPPH stable radical according to Yen & Duh (1994). Each extract (0.1 ml) was added to freshly prepared DPPH solution (6 x 10-5 M in HPLC grade methanol, 2.9 ml) and mixed vigorously. The reduction of the DPPH radical was measured by monitoring continuously, the decrease of absorption at 515 nm until stable values were obtained.

reducing poWer (rp)

Reducing power (RP) of the extracts was determined using a slightly modified ferric reducing-antioxidant power assay (Apati et al., 2003). Each extract (1.0 ml) was mixed with 2.5 ml of phosphate buffer (0.1 M pH 6.6) and 2.5 ml of 1% (w/v) potassium ferricyanide and mixture was incubated at 50°C for 20 min. After completion of incubation period, 2.5 ml of 10% (w/v) TCA was added to terminate the reaction. The upper layer (2.5 ml) was diluted with equal volume of deioinized water. Finally, 0.5 ml of 0.1% (w/v) FeCl3 was added after 10 min. The absorbance was measured at 700 nm, against a blank. Reducing power was expressed as ascorbic acid equivalents (1ASE = 1mM ascorbic acid). The ASE value is inversely proportional to reducing power.

Superoxide Anion rAdicAl ScAvenging ASSAy

This assay was based on the capacity of the extract to inhibit the photochemical reduction of nitroblue tetrazolium (NBT) by the method of Kakkar, et al. (1984). 3ml reaction mixture contained pyrophosphate buffer (0.052 M, pH 8.3, 1.2 ml), phenazine methosulphate (PMS) (186 M, 0.1 ml), nicotinamide adenine diphosphate reduced (NADH) (780 M, 0.2 ml), NBT (300 M, 0.3 ml) and different concentrations of extracts. The reaction mixture was incubated for 90 seconds at room temperature. Absorbance was taken at 560 nm by using an UV-Vis spectrophotometer. Identical tubes with reaction mixture were kept in the dark and served as blanks. The percentage inhibition of superoxide generation was measured by comparing the absorbance of the control and those of the reaction mixture containing test sample solution.

dnA dAmAge induced By fenton’S reAgent

Briefly, each extract (2-10 g/ml) and 500 ng plasmid DNA in 1x TE buffer (10 mM Tris-HCl and 1 mM EDTA, pH 7.2), were incubated for 10 min at room temperature followed by the addition of Fenton’s reagent (30 mM H2O2, 50 M ascorbic acid & 80 M FeCl3). The reaction mixture was incubated for 60 min at 30°C. The reaction mixture has final volume of 20.0 µl including phosphate-buffer saline (PBS), in 0.5 ml microcentrifuge tubes. After incubation, the samples were mixed with 3 µl of gel loading dye (0.15% bromophenol blue (BPB) and 80% (w/v) glycerol and immediately loaded into a 1.5 % agarose gel. The gel containing 40 mM Tris, 20 mM sodium acetate and 2 mM EDTA, and electrophoresed in a horizontal slab gel apparatus in Tris/acetate/EDTA gel buffer for 1.5 h (60 V/30 mA). The gels were then

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photographed with Gel Doc system (Alpha Innotech). Catechin and Silymarin (2.5 µg/ml) were used as positive control.

StAtiSticAl AnAlySiS

Data are expressed as mean ±SD of five replicates. Data were analysed on PRISM software version 3.0 using student’s t-test and one way ANOVA. * p<0.05; ** p<0.01 and *** p<0.001 were used as the criterion for significance.


Free radicals are generated in continuous manner by metabolic activities within the body. It has been reported that the diet rich in fruit and vegetables is more helpful in fighting with the diseases due to presence of high amount of phytochemicals like polyphenols, carotenoids, terpenoids and flavonoids etc., (Dhakarey et al., 2005; Singh et al., 2009a). Some of these antioxidants are endogenous but some are provided exogenously as essential diet (Singh et al., 2009b). TPC and reducing power of the plants (extracts of different agrowaste parts of it) were estimated (Table 1). The prominent extracts were selected for further antioxidant and DNA damage protection activities.

Table 1: TPC and Reducing Power (RP) of Extracts

Plant Part TPC (mg of GAE/g) ARP ASE/ml

C. carandus Leaf 84.48±2.65* 272.52±14.61** 2.34±0.18*

C. carandus Twig 46.25±1.55** 114.07±4.61* 3.87±0.58**

C. carandus Bark 23.10±4.65* 34.97±1.61** 5.34±0.18*

A.squamosa Leaf 81.62±1.56** 172.52±14.61** 3.04±0.28*

A.squamosa Twig 35.53±2.65** 28.23±4.61** 4.34±0.08**

A. squamosa Bark 42.78±2.75** 27.52±5.61* 3.34±0.16**

A.marmelos Leaf 91.04±2.65** 356.02±14.61** 1.34±0.28*

A.marmelos Twig 82.74±1.65** 172.52±15.51** 2.14±0.11***

A.marmelos Bark 73.95±0.65** 152.52±14.81* 3.34±0.12**

Quercetin 818.00±71.81***

* p<0.05; ** p<0.01 and *** p<0.001 compared with controls; student’s t-test, results are mean of three samples

Total phenolic content of samples varied from 23.97-91.04mg of GAE/g of DW. Leaf and bark extracts in most cases showed the higher values of TPC in comparison of other extracts. In present study the highest content was found in A. marmelos leaf (91.04 mg of GAE/g of DW) and lowest was in C. carandus bark (23.10 mg of GAE/g of DW); where as the A. squamosa twig and bark and C. carandus twig have shown moderate results. Phenolics are commonly found in plants and are known to be potent in multiple biological effects including antioxidant activity (Lee et al., 2002). Studies suggested that phenolic compounds of natural extracts are closely related with their antioxidant activities (Dehgan et al., 2007). In our study leaf and bark of most plant samples were found rich in polyphenolic content in comparison to the other ones, which also shows the resemblance with some previous studies of different plant materials (Ghasemi et al., 2009; Mamta et al., 2009). This accumulation of phenolics may be due the

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fact that accumulation of phenolics and flavones depends on low temperature and climatic conditions of plant parts and it supports its higher presence in leaf and bark (Singh et al., 2009b). Present results make the leaf of each plant as promising extracts and more valuable for further studies. Therefore the leaf extracts of A. marmelose (AMLE), A. squamosa(ASLE) and C.carandus (CCLE) were selected for further activities.

Fig. 1(a)–(c): Represents the Antioxidants Activity of Extracts Assessed by DPPH Radical Scavenging Assay in A. marmelos leaf(a), A. squamosa leaf (b) and C. carandus leaf

(c). Figure (d)-(f) shows superoxide radical scavenging activity by A. squamosa leaf(d), A. marmelos leaf (e) and C. carandus leaf (f); whereas (g) agarose gel electrophoresis pattern

showing protective effects of extracts on DNA damage; Lane 1:calf thymus DNA, Lane 2:Fenton reagent+DNA+ Silymarin, Lane3: Fenton reagent+ DNA+catechin,

Lane 4:Fenton reagent +DNA; Lane 5: Fenton reagent + DNA+ A. marmelos Leaf extract, Lane 6: Fenton reagent + DNA+ C. carandus Leaf extract, Lane 7: Fenton reagent + DNA+ A. marmelos Leaf extract

The determination of antioxidant value by DPPH is an easy, rapid and sensitive method to determine the antioxidant potential of a specific compound or plant extracts. The phytochemicals present in the plant extract, react with the DPPH radicals and are converted into a colourless α-α-diphenyl-β-picryl hydrazine. The decrease in the absorbance observed is due to reduction of the DPPH* radical by antioxidants present in the plant extracts, which form stable DPPH-H.

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The FRSA values of the plants samples have been summarized in Table 1. Results were expressed in the terms of anti-radical power (ARP) and anti-ascorbic acid equivalents (ASE). ARP was determined as the reciprocal value of the IC50 (inhibitory concentration) and EC50 (efficiency concentration), representing a comparable term for the effectiveness of antioxidant and radical scavenging capacity. The larger the ARP and ASE, the more efficient is antioxidant capacity. Table 1 showed that AMLE has better free radical scavenging capacity when it was compared with other extracts and is significant with the standard also. High antioxidant activity is characterized by low EC50 value and vice versa. It has been found that the free radicals are involved in the genesis of many diseases. So the herbal drugs containing free radical scavengers such as phenolics, ascorbic acid, flavonoids, carotenoids etc. may be useful in the treatment of many diseases (Singh et al., 2009a & 2009b).

Superoxide anion is a well recognized free radical species that is generated continuously by auto-oxidation process or by several cellular processes including the microsomal and mitochondrial electron transport systems. Moreover, superoxide anions produce other kinds of cell damaging free radicals and oxidizing agents that initiate DNA damage, protein oxidation and lipid peroxidation. The PMS-NADH-NBT system was used to determine superoxide anion radical scavenging activity which is a well known non enzymatic universal method. Results shows that all the extracts exhibited dose dependent NBT reduction but hydroethanolic extract of A. marmelos leaf (AMLE) showed maximum NBT reduction at low concentration whereas ethanolic extract of A. squamosa leaf (ASLE)showed NBT reduction at higher concentration.

The oxidative DNA damage protective activity of AMLE, ASLE and CCLE in comparison to silymarin and catechin against ·OH–induced damage on calf thymus plasmid DNA by using in vitro method was studied. Lane 1 shows control DNA, 2 & 3 lane have shown protective effect of standars; silymarin an catechin repectively, Lane 4 showed the damaging effect of fenton reagent which indicates that ·OH generated by decomposition of H2O2 produced both single and double strand DNA damage. The DNA damage was well protected in AMLE (Lane5) in comparison to ASLE and CCLE As shown in Fig. 1. The results were also significant with standards too. The results are also in resemblance of some previous studies on same pattern but with different plants (Singh et al., 2009b; Mamta et al., 2009).

The study suggested that agro-industrial waste such as; leaf, bark, peel and seed etc which are more common and primary agrowaste part of fruit plants are rich in polyphenols and antioxidant biomolecules. Therefore they may prove their strong candidature for being a good resource in natural pharmaceutical area. However further studies are still going on and needed to explore the molecular level of its working as well as their bioavailability and safety with efficacy of such materials experimentally.

REFERENCES

[1] Ames S.N., Shigenaga, M.K. & Hagen, T.M. 1993. Oxidants, Antioxidants and degenerative diseases of aging. Proceeding of the National Academy of Science of the United States of America. 90 (17): 7915-7922.

[2] Apati P., Szentmihalyi K., Kristo S.T., et al. Herbal remedies of Solidago-correlation of phytochemical characteristics and antioxidative properties. J Pharm Biomed Anal 2003; 32: 1045-53.

[3] Bingham M., Gibson G., Gottstein N., Pascual-Teresa S.D., Minihane A.M. and Rimbach G 2003. Gut metabolism and cardio protective effects of dietary isoflavones. Curr Top Nutra Res. 1:31-48.

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[4] Block G. 1992. The data support a role for antioxidants in reducing cancer risk. Nutr Rev. 50:207-213.

[5] Dehgan G., Shafiee A., Ghahremani M.H., Aedestani S.A. and Abdollahi M. 2007. Antioxidant potential of various extracts from Ferula szovitsiana in relation to their phenolic content. Ind j Agric Biochem. 45:691-699.

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290 National Conference on Intelligent Computing, Communication and Data Science (NCICCD-2018)

ISBN: 978-93-88237-24-6

Author IndexAgnihotri, Devanshu, 76Anuradha K. 221Arshi, Anfal, 7Awasthi, Vishnu Ji, 249

Bala, Madhu, 15Balachandaran, S. , 131Baranwal, Harshita, 100Basha, Nouraldin Almadi Ibrahim, 113Bharagava, Ram Naresh, 278Bharose, Ram, 113Buba, Saidu, 94

Chandra, Ram, 241Chaudhary, Rahul, 249

David, Ashish, 1, 25, 199Deepa S., 221Denis, D.M. , 25Dharaiya, Chetan N., 58

Ghintala, Akshaya, 15, 109Goel, Alka, 137Goutam, Surya Pratap, 260Gupta, Richa, 177

James, Abhishek, 113Jana, Atanu, 58Jindal, Tanu, 177

Kamalvanshi, Gwandi O., V. , 94Kanauji, Ajay, 187Kaur, Virpal, 241Khan, Ambrina Sardar, 177Khan, Amreen, 20Khan, Salman, 187Khatana, Raghu Nandan Singh, 153Kumar, Pankaj, 165Kumar, Parveen, 117Kumar, Vineet, 239, 272Kushuwaha, Saket, 100

Merwyn S., 7Mishra, Abha, 239Mishra, Akash, 7Mishra, Shraddha P., 7Mithare, Rachana Prasad, 143, 241Muniswamy, R.S., 143

Nafees, Mohd, 47Nath, Satyendra, 47, 100

Pahadi, Pintu Meena, 83Pandey, Mirtunjay, 260

Rachana, 143Ramchandra, 169Rameshwari, K.R. Talluri, 7, 221Rani, Rekha, 54, 62Rao, P. Smriti, 1, 117, 109, 165, 199Rath, Suvangi, 143Rawat Ranjan Manju, 117Roy, Diptarka, 260

Sagar, B.S., 35Sagar, Mamta, 83Sahithya, B.R., 47Sahoo, Prangya Paramita, 137Sain, Manohar Lal, 20, 113Sarangi, K.K., 137Saxena, Gaurav, 239, 272Shrivastava, J.P., 62Shukla, D.N. , 62Shukla, Mamta, 278Singh, Ajay Kumar, 7Singh, Bheiru, 15, 109Singh, Bhopal, 54Singh, Chhatarpal, 239, 272Singh, Pooja, 131Singh, R.P., 54Singh, R.L., 283Singh, R.N., 169Singh, Rajesh, 249Singh, Rama Kant, 165Singh, S.B., 165Singh, S.K., 165Singh, Shri Niwas, 199Singh, Vikram, 153Soni, Shweta, 83, 94Srivastava, Prateek, 177Sumana K., 226Suryavanshi, Shakti, 35

Thoma, Ashima, 1, 209Thomas, Tarence, 1, 100, 153, 177, 199Tripathi Ashutosh, 117Tripathi, Ashok, 249Tripathi, C.K.M. , 25

Verma, Mukesh Kumar, 15, 109Vishwakarma, Govind, 83

Yadav, Manish Kumar, 76Yadav, Suman, 221Yousuf, Mohd., 193

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