1

CHAPTER - I

INTRODUCTION AND REVIEW OF LITERATURE

1.1. INTRODUCTION

The environment encompasses all healthy living organisms, including

man. The environment provides resources which support life on the earth and help in the

growth of a relationship of interchange between living organisms and the environment in

which they live.

“Earth provides enough to satisfy every man's needs, but not every

man's greed”

-Mahatma Gandhi

Environment study deals with the analysis of the processes in water, air,

land, soil and organisms which leads to pollute or degrade environment. It helps one for

establishing standard, for safe, clean and healthy natural ecosystem. It also deals with

important issues like safe and clean drinking water, hygienic living conditions and clean

and fresh air, fertility of land, healthy food and development. Sustainable environmental

law, business administration, environmental protection, management and environmental

engineering are emerging as new career opportunities for environment protection and

managements. The industrial revolution heralded a completely new era in which the term

‘environment’ attained new dimension.

2

1.2. ENVIRONMENT

Environment is derived from an old French word ‘Environ’ meaning

‘Encircle’. The term environment is used to mean the region, surrounding or

circumstance in which anything exists and everything external to the organism is

included in it. Environment is defined as “the sum total of water, air and land

interrelationships among themselves and also with the human being, other living

organisms and property”.

It includes all the physical and biological surrounding and their

interactions. Environmental studies provide an approach towards understanding the

environment of our planet and the impact of human life upon the environment. Thus

environment is actually global in nature, it is a multidisciplinary subject including

physics, geology, geography, history, economics, physiology, biotechnology, remote

sensing, geophysics, soil science and hydrology etc.

The environment has four components namely Atmosphere Hydrosphere,

Lithosphere and Biosphere.

Atmosphere

It is a mixture of gases, mainly nitrogen, oxygen and carbon-di-oxide

which play a vital role in sustaining life on earth. It acts as a gaseous blanket and screens

the dangerous UV radiation entering the earth from the sun and transmits the radiations in

the range of 300 nm to 2500 nm. It plays an important role in balancing heat on earth and

in the hydrological cycle.

3

Hydrosphere

It includes all types of water resources such as oceans, seas, rivers, lakes,

streams, reservoirs, glaciers and ground waters. Nearly 97% of the earth’s water

resources are trapped in the oceans and seas are more saline. And 2.4% is locked up in

the glaciers and polar ice-caps. So, not even 1% of total water resources is available for

human and industrial purposes.

Lithosphere

It is outer mantle of the solid earth. The soil consists of complex mixtures

of inorganic and organic matter along with water. The organic minerals composed of

silicates of sodium, potassium, aluminum, calcium and iron, oxides of iron, manganese

and titanium and carbonates of magnesium and calcium. The organic matter which is less

than 5% of the soil determines the productivity of the soil. It consists of biologically

active compounds like polysaccharides, nucleotides, organo-phosphor and organo-

sulphur compounds, sugar and humus materials. The clay materials and humus in the soil

have a high cation exchange capacity and thus help in supplying essential trace elements

to the plant through soil as nutrients.

Biosphere

It is the global sum of all ecosystems. It can also be called the zone of life

on Earth, a closed (apart from solar and cosmic radiation) and self-regulating system.

From the broadest biophysiological point of view, the biosphere is the global ecological

system integrating all living beings and their relationships, including their interaction

with the elements of the lithosphere, hydrosphere and atmosphere. Man is the most

4

powerful disturber of his own environment, even though his health and perhaps his

survival on earth depend on its condition (Glynn Henry, 2004).

1.3. SCOPE AND IMPORTANCE OF ENVIRONMENTAL SCIENCE

Environmental science is a multidisciplinary science whose basic aspects

have a direct relevance to every section of the society. Its main aspects are:

Conservation of nature and natural resources.

Conservation of biological diversity.

Control of environmental pollution.

Stabilization of human population and environment.

Social issues in relation to development and environment.

Development of non-polluting renewable energy system and providing new

dimension to nation’s security.

Environment belongs to all the living beings and so it is important for all.

Living beings are affected by environmental issues like global warming, depletion of

ozone layer, dwindling forest, energy resources, loss of global biodiversity etc.

1.4. POLLUTION

Extensive modifications of the environment have been caused by shifting

millions of tones of materials from one place to another, converting them to less

degradable forms or into substances that are positively harmful to living organism. Any

undesirable state of the natural environment being contaminated with harmful substances

as a consequence of human activities is termed as “Pollution”. In detail, it can be defined

as presence of matter (solid, liquid, gas) or energy (heat, noise, radiation) whose nature,

5

location or quantity directly or indirectly alters the characteristics or processes of any

part of the environment and cause damage to the condition, health, safety or welfare of

plants, animals, humans or property’. The word pollution derived from Latin word

‘Pollutinem’ which means ‘make dirty’, is the act of polluting the environment.

The Royal Committee of Environmental Pollution reported the following

in its fifth report: Pollution occurs when enough of a substance present in the

environment to have harmful effects, as a result of Man’s activities. Many substances

which can become pollutants are present naturally in the environment in lesser amounts

and may be beneficial or even essential to it (Pandey and Carney, 2005).

According to the report of Environmental Pollution panel of U.S.

President’s Science Advisory Committee, “The environmental pollution is the

unfavourable alteration of our surroundings, wholly or largely, as a by-product of man’s

activities, through direct or indirect effects, of changes in energy patterns, radiation

levels, chemical and physical constitution and abundance of organism”.

Thus, the pollution causes undesirable changes and it threatens the land,

water, air and outer space environment which promote healthy living. The effects of

pollution are becoming prominent day-by-day and hence the problem of taking the

pollution has drawn serious attention of all concerned.

1.5. CLASSIFICATION ACCORDING TO ENVIRONMENT

When different spheres of the environment are affected by pollution, they are

categorized as

6

(i) Air Pollution

(ii) Water Pollution

(iii) Soil or Land Pollution

Air pollution

Air pollution is by far the most harmful form of pollution in our

environment. Air pollution is caused by the injurious smoke emitted by cars, buses,

trucks, trains, and factories, namely sulphur dioxide, carbon monoxide and nitrogen

oxides. Even smoke from burning leaves and cigarettes are harmful to the environment

causing a lot of damage to man and the atmosphere. Evidence of increasing air pollution

is seen in lung cancer, asthma, allergies, and various breathing problems along with

severe and irreparable damage to flora and fauna. Even the most natural phenomenon of

migratory birds has been hampered, with severe air pollution preventing them from

reaching their seasonal metropolitan destinations of countries. Chlorofluorocarbons,

released from refrigerators, air-conditioners, deodorants and insect repellents cause

severe damage to the Earth’s environment. This gas has slowly damaged the atmosphere

and depleted the ozone layer leading to global warming (Environmental pollution and its

Effects, 2013).

Water Pollution

Water plays a vital role in human life (Arunabh Mishra and Vaisishta

Bhatt, 2008). The consequence of urbanization and industrialization leads to spoil the

water. Water that is found in streams, rivers, lakes, wetlands and artificial reservoirs is

7

called surface water. Water that percolates into the ground and fills the pores in soil and

rock is called groundwater.

Among the various sources of water, ground water is considered to be the

safe for drinking purposes. The water which is being used for industries, agriculture and

human needs add continuously contaminants to ground water. (Anurag Tewari, 2010).

Water pollution caused industrial waste products released into lakes. Rivers, and other

water bodies, have made marine life no longer hospitable. Humans pollute water with

large scale disposal of garbage, flowers, ashes and other household wastes. In many rural

areas one can still find people bathing and cooking in the same water, making it

incredibly filthy. Acid rain further adds pollution in the water. In addition to these,

thermal pollution and the depletion of dissolved oxygen aggravate the already worsened

condition of the water bodies. Water pollution can also indirectly occur as an off shoot of

soil pollution-through surface runoff and leaching to groundwater (SimpleEnglish,

Wikipedia, 2013).When the quality or composition of water changes directly or indirectly

as a result of man’s activities such that it becomes unfit for any purpose and it is said to

be polluted.

Sources of water pollution

Water pollution mainly results from the following sources

i) Point sources of pollution

ii) Non-point sources of pollution

8

Point sources of pollution

A source of pollution can be identified readily, if it has a definite source

and place where it enters the water it is said to come from a point source. Eg. Municipal

and industrial Discharge Pipes.

Non-Point Sources of pollution

When a source of pollution cannot be readily identified, such as

agricultural runoff, acid rain, etc, they are said to be non-point sources of pollution.

INDUSTRIAL POLLUTION

Industrialization is considered the cornerstone of development strategies

due to its significant contribution to the economic growth and human welfare, but it

carries inevitable costs and problems in terms of pollution of the air and water resources

(Kannj and Achi, 2011). Specially, water bodies near to industrial area have been

extremely affected from disposal of waste which can alter the physical, chemical and

biological nature of the receiving water body. So, industrial waste is the most common

source of water pollution in the present day and it increases yearly due to the fact that

industries are increasing because most countries are getting industrialized (Osibanjio

et.al., 2011). Industrial waste-water originates from the wet nature of industries which

require large quantities of water for processing and disposal of wastes. Most industries

are therefore, located near water sources (Adekunle and Eniola, 2010). As societies

throughout the world become more aware of the issues involved in water pollution, there

has been considerable public debate about environmental effects of effluents discharged

into aquatic environments (Karki et.al., 2005). Wastes entering these water bodies are

9

both in solid and liquid forms. As a result, water bodies which are major receptacles of

treated and untreated or partially treated industrial wastes have become highly polluted

(Rishi and Rishi, 2011). Use of industrial effluent and sewage sludge on agricultural land

has become a common practice in India as a result of which these toxic metals can be

transferred and concentrated into plant tissues from the soil. These metals have damaging

effects on plants themselves and may become a health hazard to man and animals. Above

certain concentrations and over a narrow range, the heavy metals turn into toxins (Babich

et.al., 1982). Industrialization is considered the synonym to development but it is

necessary to review the impact of industrialization on society and environment otherwise

it can bring the following consequences

1. Ecosystem imbalance

2. Biodiversity loss

3. Toxic metal and non-metal discharge

4. Food chain imbalance

5. Disturbance of self purification mechanism

6. Gaseous emissions

POLLUTION IN VARIOUS INDUSTRIES

In oil refineries, the crude and production units generate oil in the form of

emulsion associated with water which is high in COD and contains fewer BOD. The

crude desalting unit produces emulsified oil, ammonia, phenol and suspended solids.

These pollutants produce relatively high BOD and COD. In crude oil refraction unit,

wastewater containing sulphides, chlorides, mercaptans and phenol are generated

10

whereas in thermal cracking process, wastewater contains high alkalinity, BOD, COD,

ammonia, phenol and sulfides.

India is in 20th place among the paper producing countries in the world.

The paper industry is a highly capital-intensive industry. The composition of effluents

depends upon the type of paper industry. The paper mill industry usually contains high

suspended solids, alkalinity and high BOD value.

The sugar industries are the third largest industries in India which ranks

next to iron and steel and cotton industries. The effluent usually contains a large amount

of dissolved organic matter, high BOD, total dissolved solids (TDS), and total suspended

solids (TSS). The effluent from these industries causes serious problems due to their

heavy organic load which normally requires lot of oxygen, resulting in the exhaustion of

oxygen required for fish to survive. When the organic pollutants present in the effluent

stagnate, there will be a rapid consumption of oxygen followed by anaerobic

stabilization. This will cause bad odour, black colour and fish mortality due to the

formation of hydrogen sulphide. The most important crop from which sugar can be

produced in commercial quantity are sugarcane. India is a largest sugar producing

country (Solomon, 2008).

Effluent from distilleries contains a large amount of dissolved organic

matter. The spent wash is the largest effluent stream from distilleries, the volume which

varies from 14-22 times of the volume of rectified spirit produced. The spent wash is

highly acidic. Anaerobic and aerobic treatments can be done but due to economic

reasons, the aerobic method does not find much application because of fairly high organic

load.

11

The increasing demands of the world market for semi-finished and

finished Indian leather has encouraged the growth of a large number of Tanneries in

India. Tannery effluent, being voluminous and highly putrescible in nature, damages the

normal life of the receiving water, when it is discharged without treatment. The major

pollutants are sulphides, chlorides, chromium, and arsenic contain high BOD, suspended

and dissolved solids, high pH, phenol, detergents, dyestuff and anti-septic agents.

The production of fertilizers also increases the pollution load on natural

streams. Nitrogenous fertilizer effluents are known to create problem due to the presence

of ammonia. The effluent discharged without treatment affects the availability of water

for drinking purpose. The major pollutants in these effluents are pH, ammonical nitrogen,

fluorides, suspended solids, chromate and high organic loads.

The industries whose trades wastes and effluents play a major role in

pollution of water include paper, textile, sugar, fertilizers, nonferrous and ferrous metals,

rubber, chemical works, vegetable oils, petrochemicals, distilleries and tanning industries

etc.,

Untreated industrial effluents and treated industrial effluents are the prime

polluting sources of ground water, the chemical oxygen demand (COD) and biological

oxygen demand (BOD) are frequently used as a measure of degree of polluting quality of

effluents. But experiment measurement of BOD requires nearly 5 days and COD requires

few hours. However, the BOD and COD values of an effluent can be quickly estimated

by theoretically using statistical regression analysis.

The newly adapted technique ‘Adaptive Neuro-Fuzzy Inference system’

(ANFIS) (Jang, 1993) incorporates the salient feature of both fuzzy logic and the artificial

12

neural networks (ANNs). ANFIS technique can be effectively applied for the prediction

of BOD and COD values, which will help for fast monitoring of the quality of effluents.

Soil

A healthy soil is essential for life. The word soil is derived from a Latin word

Solum, which means earthy material in which plants grow (Raut and Ekbote, 2012). Soil

study is commonly referred to as soil science. Soil can be defined as the weathered layer

of the earth’s crust with living organisms and their products of decay intermingled.

Importance of soil

Soil is a living system that represents finite resources vital to life on earth.

It forms thin of unconsolidated mineral and organic matter on the earth’s surface. It

develops slowly from various parent materials and is modified by time. Soil is one of the

most significant ecological factors, which is derived from the transformation of surface

rocks. Soil is essential for survival of the living world, especially for human beings. It is a

dynamic medium made up of minerals, organic matters, water, air and living creature

including bacterial and earthworms (Raut and Ekbote, 2012). Healthy soil gives us clean

air and water, bountiful crops and forests, product rangeland, diverse wild life, and

beautiful landscapes (Rajshekar et.al., 2010)

Soil Pollution

The rapid increase in human population, industrialization, use of excessive

amounts of pesticides and fertilizers in agriculture increased the stress on natural

resources including soil. Soil pollution usually results from the disposal of solid and

semi-solid wastes from agricultural practices and from unsanitary habits. The soil as

13

heavily polluted day-by-day by hazardous materials and microorganisms, which enter the

food chain or water and create numerous health problems (Essay on the pollution, 2013).

To make the situation worse, there are poisonous effluents from industrial

units, locomotives, automobiles and high flying air craft’s. Some of the dangers posed to

soil pollution are due to the fact that while numbers of the earth’s inhabitants are

increasing, the earth’s natural resources are by and large fixed as well as limited. Thus

soil gets heavily polluted day by day by hazardous chemicals with the result that micro-

organisms enter our food chain, air and water, which are consequently ingested by man.

Soil suitability

Land evaluation is an important feature in the field of agriculture and

geology. The determination of soil suitability for the cultivation of a particular

crop is one of the prime aspect of land evaluation. This is due to the fact that,

besides other decides factors, the physico - chemical characteristics of a soil play a

key role in determining the yield of crop. These physico – chemical parameters of a

soil are, now -a -days, significantly or drastically affected by pollution of various

kinds and from different sources. This makes necessary periodic monitoring of soil

parameters by accurate and fast evaluation techniques. There are many conventional

methods available for the evaluation of soil suitability for cultivation purposes.

Most of the research problems in the evaluation of land , like

suitability of soil for cultivation , contamination due to pollutants and changes in

fertility etc, uses multiple variables which interact with each other.

14

The yield of a particular crop largely depends on many important

factors like Physico - chemical characteristics of soil, quality of seed, availability of

water, sun - shine management practice etc. When the remaining factors are same,

the soil characteristics play an important role in determining the yield of the crop,

hence the suitability of soil for that crop.

In general, models used in soil studies are interdisciplinary. In many ways

mathematical or statistical models give only less accurate results due to non-exact nature

of the input parameters and their relationship with the output. Very little use of fuzzy

logic and has neural network has been used for evaluating the soil suitability of soils for

different crops.

1.6. POLLUTION BY HEAVY METALS

Environmental pollution with heavy metals is a global disaster that is

related to human activities such as mining, smelting, electroplating, energy and fuel

production, power transmission, intensive agriculture, sludge dumping and melting

operation (Igwe and Abia, 2006). All the heavy metals at high concentration have strong

toxic effects and are regarded as environmental pollutants (Sawidis, 2008). The

assessment of bio availability of pollutants in biological system is a strong indication of

their toxicity. In recent years, soil polluted by heavy metals has increased due to human

activities and removal of such pollutants has also been of great concern (Agunbiade and

Fawale, 2009, Uwumarongie et.al., 2008). Heavy metals are not biodegradable and tend

to accumulate in biological systems. The environment has been found to absorb

pollutants or clean up itself by natural biological/biochemical activities hence the

increasing use of plant to remediate to the environment. Plants can accumulate and

15

magnify trace pollutants like heavy metals to a level that is toxic to lives (Qasem et.al.,

2006).

Heavy metals are elements with high relative atomic mass (usually greater

than 6g/cm3) such as Cd, Cu, Zn, Ni, Al, Mo, Sn etc., as well as semi metals B, Te, As

and Se, as listed by occupational safety and health administration (Vijayarengan, 2012).

Agricultural soils in many parts of the world are slightly too moderately contaminated by

heavy metal toxicity. Heavy metals are included in the main category of environmental

pollutants as they can remain in the environment for long periods: their accumulation is

potentially hazardous to humans, animals and plants (Abdul Jaleel et.al., 2009,

Jayakumar et.al., 2008, Deram et.al., 2000). Excessive metal concentrations in

contaminated soils can result in decreased soil microbial activity and soil fertility and

yield losses (Seliga, 1993). Trace elements are necessary for the normal metabolic

functions of the plant, but at higher concentrations, these metals are toxic and may

severely interfere with physiological and biochemical functions (Chen et.al., 2001).

Although some metals are immobile and persistent, other metals are mobile, and

therefore, the Zn, Fe and Cd are three essential micronutrients for plant nutrition. Plants

are good environmental quality indicators and respond directly to air, soil and water

quality (Diaz and Massol Deya, 2003, Kabata-pendias, 2000). Since the plants can

naturally draw the pollutants from their local environment, their chemical composition

can indicate the degree of disturbances when assessed against background values

obtained from unpolluted vegetation (Massol-Deya et.al., 2005).

Many researchers have been demonstrated that plants are effective in

cleaning up contaminated soil (Wenzel et al., 1999). Phytoremediation is a general term

16

for using plants to remove, degrade, or contain soil pollutants such as heavy metals,

pesticides, solvents, crude oil, polyaromatic hydrocarbons, and landfill leacheates.

Long-term and extensive use of agricultural land with frequent application

of growing practices and use of pesticides (Nicholson et al., 2003) may cause heavy

metals such as zinc, iron and cadmium to be strongly accumulated in the topsoil.

Occurrence of zinc, iron and cadmium

Zinc

Zinc is one of the essential elements for many physiological processes in

plants, but its higher concentration, makes it toxic (Baccio et al., 2005). It is an important

element for both plants and animals. It plays an important role in several plant metabolic

processes. It activates enzymes and is involved in protein synthesis and in carbohydrate,

nucleic acid and lipid metabolism. But in excess levels zinc causes significant reduction

in growth and yield of plants (Sivasankar et.al., 2012, Vijayarengan, 2012). Zinc plays an

important role in many biochemical reactions within the plants. The various other roles of

zinc in plants

1. Production of auxin, an essential growth hormone

2. Regulates starch formation and proper root development

3. Formation of chlorophyll and carbohydrates

4. Enable plants to withstand lower air temperatures

5. Helps in the biosynthesis of cytochrome a pigment maintains plasma membrane

integrity and synthesis of leaf cuticle.

17

Zinc deficiency is a global nutritional problem in agricultural soils and

human populations in large number of countries that calls for closer cooperation between

agronomists, plant breeders, human nutritionists, the fertilizer industry and farmers.

Application of Zn-containing fertilizers offers a rapid solution to the

problem, and represents an important complementary approach to on-going breeding

programs for developing new genotypes with high Zn density in grain. Maintenance of

adequate amount of readily available Zn in soils ensures healthy root growth and thus,

better acquisition of Zn from soil. Zinc has relatively high phloem mobility and foliarly

applied Zn is, therefore, easily translocated into grain. Increasing number of evidence is

available showing that application of Zn to foliage represents a rapid approach to

enrichment of cereal grains with Zn, especially in the case of wheat. Use of Zn-

containing fertilizers can also contribute to crop production. Zinc fertilization can

increase crop yields. Balanced crop nutrition supplying all essential nutrients, including

zinc, is a cost effective management strategy. Even with zinc-efficient varieties, zinc

fertilizers are needed when the available zinc in the topsoil becomes depleted.

Zinc is required as structural and catalytic compounds of proteins and enzymes

and cofactors are essential to normal growth and development. But when present in

elevated levels in soils they are toxic and can ultimately cause the death of plants.

Iron

Iron is the fourth most abundant element and second most abundant metal

in the Earth’s crust (Nave, 2013). It is one of the seven metals known in antiquity (along

with gold, silver, copper, mercury, tin and lead). The average concentration of iron in the

earth’s crust is 50,000 ppm (Abundance of element in earth’s crust, Wikipedia, 2013).

18

The chief ores are the oxides hematite Fe2O

3, magnetite Fe3O

4 and its carbonate siderite

FeCO3

(Nave, 2013).

Iron is an absolute requirement for most forms of life, including humans

and most bacterial species. Plants and animals all use iron, and it can be found in a wide

variety of food sources (Human Metabolism, Wikipedia, 2009). The industrial uses of Fe

and its compounds are numerous. It is the major constituent in steel making. Several Fe

oxide forms find use as paint pigments, polishing compounds, magnetic inks, and

coatings for magnetic tapes. The soluble salts are variously used as dyeing mordant,

catalysts, pigments, fertilizer, feeds, and disinfectants, and in tanning, soil conditioning,

and treatment of sewage and industrial wastes. In humans, iron is an essential component

involved in oxygen transport (Washington National Academy press, 2001). It is also

essential for the regulation of cell growth, and differentiation of iron limits oxygen

delivery to cells, resulting in fatigue, poor work performance, and decreased immunity.

On the other hand, excess amounts of iron can result in toxicity and even

death. Toxicology considerations are important in terms of iron deficiency (anemia) and

accidental acute exposure and chronic iron overload due to idiopathic hemochromatosis

or as a consequence of excess dietary iron or frequent blood transfusions. The immediate

cause of death from the inorganic compounds of Fe in animals is respiratory failure.

Clinical signs preceding death are anorexia oligodipsia, oliguria, alkalosis, diarrhea, loss

of body weight, hypothermia, and alternating irritability and depression. In human

poisonings, symptoms of iron intoxication include vomiting, cirrhosis of the liver,

hemochromatosis, diarrhea, lethargy, coma, irritability, seizures, and abdominal pain

(Jamaluddin Ahmed and Uttam Kumar Roy, 2008). In soils too, the total iron content

19

remains well above 0.1 percent and therefore, it is often not categorized as a trace

element in soils. However, the plant’s biochemical requirement of this element is low

enough for it to be recognized as a micronutrient. Iron toxicity results from excessive

uptake of iron by plants.

Cadmium

Cadmium is a heavy metal and is found closely in association with zinc. In

the earth’s crust the average concentration of cadmium is 0.15-0.2ppm (Ghinwa et.al.,

2010). Cadmium (Cd), a common and transitional metal and available in the

environmental which is one of highly dispersed metals by human activities (Morsy et.al.,

2011). Cadmium has acute and chronic effect on health and environment. Once cadmium

released into environment, it stays in circulation and is not degraded in nature (Nortic

council of ministers cadmium review January, 2003). Geochemically, cadmium is quite

mobile in soil, water and thus freely taken up by plants. On the top soil, cadmium is

concentrated with organics (Tudoreanu et.al.,, 2004). In soil, higher cadmium

concentration can occur either naturally or through anthropogenic activities (Kirkby

et.al., 2008). Mostly the cadmium pollution in the environmental has occurred through

the mining, refining of metal ores through the application of cadmium- containing

phosphate fertilizers, sewage sludge and municipal composts to agricultural soils

(Alexander et al, 2010). Cadmium used in the manufacture of various products such as

batteries, chipset, pigments, televisions and semi conductors also cause of cadmium

pollution (Hashim et.al., 2004; and Poonam Sangwan et.al., 2013).

High concentrations of cadmium in soil represent a potential threat to

human health because it is incorporated in the food chain mainly by plant uptake

20

(Alvarez- Ayuso, 2008). The greatest concern due to cadmium contamination is because

of its occurrence in free ionic form. Cadmium enters into the environment through

weathering of rocks, forest fires and volcanic eruptions. It may be naturally presented in

air, water, soil and foodstuffs.

Cadmium is toxic both to plants and animals. The basic cause of the

toxicity probably lies in the much higher affinity of cadmium for thiol grouping (SH) in

enzyme and proteins. The presence of cadmium disturbs enzyme activity. In plants

excess cadmium may also disturb iron metabolism and cause chlorosis. Cadmium

availability depends much on soil pH and the presence of other cation species. Calcium

and zinc in particular depress the cadmium uptake (Akilandeswari, 2006).

1.7. REVIEW OF LITERATURE

Monitoring of pollution has become an essential act in controlling the

pollution. Physical, chemical and biological pollutions of soil and water occur through

different sources. Also organic and inorganic toxic pollutants are generally present in

micro and sub micro quantities in the environment and their determination at these levels

need accurate, precise and sensitive analytical techniques.

The simulation of BOD and DO Modelling in Mahanadi River System

lying in Odisha using ANN, analysed by Nibedita Guru and RamakarJha (2013). They

compared the results with statistical modelling and they concluded that the results

indicate the applicability of neural network model to recognize the pattern of the water

quality variable and to provide good predictions of the monthly variations of BOD and

DO in Mahanadi River lying in Odisha.

21

Najah et.al., (2013) studied the performance of ANFIS versus MLP-NN

dissolved oxygen prediction models in water quality monitoring. They concluded the

ANFIS model is more flexible than the ANN model considered, with more options of

incorporating the fuzzy nature of the real-world system. The ANFIS model was capable

of providing greater accuracy, particularly in the case of extreme events.

Fuzzy-logic modelling of Fenton’s strong chemical oxidation process

treating three types of landfill leachates was determined by Hanife Sari et.al., (2012).

They estimated that the fuzzy-logic models is very simple and there is no need to define

the complex physicochemical reactions and time consuming mathematical formulations

to predict removal efficiencies of several fundamental wastewater parameters prior to

discharge to receiving streams.

Application of Adaptive Neuro Fuzzy Inference System (ANFIS) in river

Kaduna discharge forecasting was analysed by Folorunsho, et.al., (2012). They showed

that the high level of accuracy with regards to the ANFIS-based model developed in

forecasting the river discharge especially with a correlation (r) value of 86%.Hence based

on the results obtained from this research, it can be concluded that the ANFIS based

model is a better modelling tools for predicting river discharge considering the strong,

high and positive correlation coefficient the model displayed.

Kumar et.al., (2012) studied the evaporation estimation using Artificial

Neural Networks and Adaptive Neuro-Fuzzy Inference System techniques. They

concluded that ANN and ANFIS techniques have good performances. Between ANN and

ANFIS, ANFIS model is slightly better albeit the difference is small. Although ANN and

22

ANFIS techniques seem to be powerful, their data input selection process was done by

trial and error method.

Modelling water-in-oil emulsion formation using fuzzy logic evaluated by

Kaan Yetilmezso et.al., (2012).They concluded that the fuzzy logic methodology, have

been successfully used to deal with subjects having ambiguities and uncertainties. In this

study, a MISO (multiple inputs and single output) fuzzy-logic-based model was proposed

as a new numerical modelling scheme for the prediction of water-in-oil emulsions

formation. Statistical results clearly indicated that, compared to the regression approach

the proposed MISO fuzzy-logic-based model showed a superior predictive performance

on forecasting of water-in-oil emulsions stability with a satisfactory determination

coefficient over 0.98.

Prediction of industrial solid waste with ANFIS Model and its comparison

with ANN Model was studied by Manoj Kumar Tiwari et.al., (2012). They stated that

ANFIS gave better results than ANN, due to a smaller uncertainty of ANFIS than ANN,

the output stability of ANFIS is suitable, and this model was selected as the optimum

model for waste generation forecasting in DBTC. However, ANN presented weak results

than ANFIS with respect to statistical criteria.

Areerachakul, (2012) evaluated the comparison of ANFIS and ANN for

estimation of biochemical oxygen demand parameter in surface water. His results showed

that cost and time to analyst BOD could be minimized. However, he recommended that

other techniques and/or other statistical models should also be approached in the

experiments.

23

Experiments of ANFIS modelling for the biodegradation of penicillin-G

waste water using anerobic hybrid reactor was evaluated by Mullai et.al., (2011). They

showed that the results proposed ANFIS model was well performing the performance of

AHR.

Dilek Erdirencelebi and Sukran yalpir (2011) studied the ANFIS

modelling for the prediction of anaerobic digestion effluent quality. They stated that

ANFIS prediction performance showed a high feasibility of the model based control

system on the anaerobic digester system to produce an effluent amenable for a

consecutive aerobic treatment unit.

Predicting effluent from the waste water treatment plant of industrial park

based on fuzzy network and influent quality was studied by Pai et.al., (2011). They found

that ANFIS architecture can overcome the limitations of traditional neural network. It

also revealed that the influent indices could be applied to the prediction of effluent

quality. After prediction, it is suggested that the ANFIS can be used as the objective

function or constrains in optimization for best design or operation in the future study.

Prediction of effluent quality of a paper mill waste water treatment using

ANFIS model was analysed by Jinquanwan et.al., (2011). They revealed that ANFIS’s

architecture consists of both ANN and fuzzy logic including linguistic express of MFs

and if–then rules, so it can overcome the limitations of traditional neural network

including possibility of getting trapped in local minimum and the choice of model

architecture, and to increase the predicting performance. Therefore, ANFIS is a good

choice for modelling the paper mill wastewater treatment performance.

24

HanYan et.al., (2010) analysed Adaptive Neuro Fuzzy Inference System

for classification of water quality status. They exhibited that ANFIS model performed

better than ANN model and can generate output value in continuous form which makes

water quality assessment more comprehensible.

Estimation of chemical oxygen demand in Leachate of municipal solid

waste using ANFIS-based model was evaluated by Maonsalas et.al., (2010). They

observed that the ANFIS model presented the best fit and smaller mean quadrate error

(MQE) when estimating leachate COD for leachate from 15 and 30% recycling regimes.

Modelling biological oxygen demand of the Melen River in Turkey using

an artificial neural network technique was studied Dogan et.al., (2009). They described

that the ANN model gives reasonable estimates for the BOD prediction.

Najah et.al., (2010) evaluated the water quality prediction model utilizing

integrated wavelet-ANFIS model with cross-validation. They stated that the WDT-

ANFIS module outperformed the ANFIS module with significant improvement in

predicting accuracy. This result indicated that the proposed approach was basically an

attractive alternative, offering a relatively fast algorithm with good theoretical properties.

This new technique would be valuable to assist decision-makers in reporting the status of

water quality, as well as investigating spatial and temporal changes.

Improving neural network prediction of effluent from biological

wastewater treatment plant of industrial park using fuzzy learning approach was

evaluated by Pai et.al., (2009). They determined that ANFIS’s architecture consists of

both ANN and fuzzy logic including linguistic express of MFs and if–then rules, so it can

overcome the limitations of traditional neural network including possibility of getting

25

trapped in local minimum and the choice of model architecture, and to increase the

predicting performance. After prediction, it is suggested that the ANFIS can be used as

the objective function or constrains in optimization for best design or operation in the

future study.

Modelling of COD removal in a biological wastewater treatment plant using

adaptive neuro-fuzzy inference system and artificial neural network was estimated by

Civelekoglu et.al., (2009). From their results the overall indicated that the ANFIS

modelling approach may be suitable to describe the relationship between wastewater

quality parameters and may have application potential for performance prediction and

control of aerobic biological processes in wastewater treatment plants.

Pai et.al., (2009) evaluated using fuzzy inference system to improve

neural network for predicting hospital waste water treatment plant effluent. They

explained that ANFIS model overcome the limitations of traditional neural network and

increase the prediction performance.

Prediction of water quality indices by Regression analysis and Artificial

Neural Networks were analysed by Rene and Saidutta (2008). They concluded that the

ANNs models gave accurate and reliable results, indicating the versatility of the

developed models and the predictions are highly significant when tested with the test

data. The empirical relations developed in this study and the developed ANN based

models can be applied with high degree of confidence for refinery wastewaters.

Application of Artificial Neural Networks to estimate wastewater

treatment plant inlet biochemical oxygen demand analysed by Emrah Dogan et.al.,

(2008). They reported that the Artificial Neural Networks and MLR model was used for

26

predicting BOD. On the basis of the comparison results, the ANN technique was found to

be superior to the MLR technique. On the basis of the comparisons, it was found that the

ANN model could be employed successfully in estimating the daily BOD in the inlet of

wastewater biochemical treatment plants.

A Neuro-fuzzy model for inflow forecasting of the Nile River at Aswan

high dam was evaluated by El-Shafie et.al., (2007). They reported that the ANFIS model

shows significantly higher accuracy and reliability in terms of prediction than ANN.

ANFIS modelling for estimation of COD in match industry effluents was

analysed by Kalyanaraman et.al., (2004).They predicted the COD value, also they

compared the results with statistical modelling and showed the superiority of ANFIS

modelling.

Fuzzy modelling or fuzzy identification, first explored systematically by

Takagi and Sugeno (1985) had found numerous practical applications in control,

prediction and inference.

Physico chemical characterization of farm land soil used in some villages

of Lunawada Taluka, District–Mahisagar Gujarat, India was studied by Jain Swanti

et.al., (2014). They showed the result that overall villages of Lunawada Taluk have

various parameters like EC, pH, OC, N, P, K are tabulated. The information would help

the farmers to decide the problems related to soil nutrients of fertilizers to be added to

soil to make production economic.

Soil quality indicators under continuous cropping systems in the arid eco-

system of India was analysed by Nishant Sinha et.al., (2014). They found that value of

SQI was positively and significantly correlated (R2=0.50, P< 0.01) with wheat equivalent

27

yield for all the cropping system. This implies that the index may have practical utility

for quantifying the soil quality.

Comparison of soil quality and productivity at two sites differing in profile

structure and top soil properties was explained by Stephen Merrill et.al., (2013). They

showed that high soil quality index value indicates positive responses to soil conservation

management and also they indicated the need for integration of soil profile and sub soil

information with near surface soil quality assessments.

Morugan Coronado et.al., (2013) described the application of soil quality

indices to assess the status of agricultural soils irrigated with treated wastewaters. They

suggested that the application of soil quality indices indicated that all the soils of the

study sites were in a state of disequilibrium regarding the relationships between

properties independent of the type of water used. However, there were no relevant

differences in the soil quality indices between soils irrigated with wastewater with respect

to their control sites for all except one of the sites which corresponded to the site where

low quality waste water was used.

Spandana et.al., (2013) determined the developing a soil quality index for

a Vrishabavathi command area. They showed that the outcome of the study was that the

soil quality index had fallon in the category of medium to high suitability of soil for

growing crops.

Vara Prasad (2013) explained the data base to identify and collection of

non spatial data elements pertain to soil quality problem in penna river basin using

remote sensing and GIS. He prepared spatial distribution maps for soil quality based on

the index computed on the laboratory analysis using ARC INFO software.

28

Pandeeswari and Kalaiarasu (2012) analyzed the studies on the physico-

chemical properties of the soil samples collected from different locations of tsunami

affected soils of Cuddalore district, of Tamil Nadu. This study proved that tsunami

affected soil are having low nutrient contents.

Physico-chemical analysis of soil and industrial effluents of sanganer

region of Jaipur, Rajasthan was described by Nidhi Joshi and Ashwani Kumar (2012).

They found that values of nitrogen, phosphate and potash concentration in the soil

samples also had wide variability.

Physico-chemical analysis of soil collected from Babhulgaon region

district yavatmal(M.S.) was determined by Raut and Ekbote (2012). They concluded

that result showed different concentrations of various physico-chemical parameters at

different sites. The texture of soil ranged between clay to clay loams with slightly

alkaline in nature. Bulk density (mg/m3) was ranged 1.16 to 1.22, porosity (%) ranged

between 53.90 to 56.20, maximum water folding capacity (%) ranged between 57.50

and70.32. Available water capacity (%) was ranged between 12.08 to 17.35, pH ranged

between 7.35 to 8.10, Electrical conductivity (ds/m) was ranged between 0.17 to 0.31.

Organic carbon (gKg-1) ranged between 4.8 to 8.1, calcium carbonate (%) was ranged

between 5.59 to 15.19.

Assessment of soil quality microarthropod communities are under

different land system: A case study in the mid-hills of central Nepal was analysed by

Farida Begum et.al., (2011). Their study indicated that land used and elevation had

significant effects on the soil micro-arthropod density, diversity and other biotic factors,

29

which in turn was affected the physico chemical quality of the soil and also soil

biological indicators reflect the physico chemical condition of soil.

Ayoubi et.al., (2011) evaluated that assessing impacts of land use change

on soil quality indicators in a loessial soil in golestan province, Iran. The physical,

chemical and biological characteristics of soil under foreland uses were measured and

suitable soil quality indicators were selected using factor analysis. They concluded that

greater attention was needed to conserve the soil on the hills slopes by preventing

deforestal and reclamation of degraded land by establishing appropriate forest and

orchard plantations.

Romina Romaniuk et.al., (2011) explained the soil quality index to

evaluate the vermicompost ammendments effects on soil properties. They found that SQI

showed a significant increase of soil quality with the vermicompost dose of 20 Mg /ha

especially by enhancing the bio chemical and biological properties.

Snober Bhat et.al., (2011) studied correlation on physico chemical

factors with vesicular-arbuscular mycorrhizas fungi distribution under different

agrocological conditions. This study revealed that all the physical and chemical factors

viz, soil moisture, soil texture, soil pH and EC, nitrogen, phosphorous, potassium and

carbon are positively correlated with the distribution of vesicular-arbuscular mycorrhizas

fungi.

YangJae et.al., (2010) studied about determining minimum data set for

soil quality assessment of organic farming system in Korea. They concluded that

adequate management for EC and orthophosphate are necessary to enhance the soil

30

quality in study area. They showed that the result of the study could provide general

guideline to manage organic farming systems.

Lauric Ceillon et.al., (2009) explained about predicting soil quality

indices with near infrared analysis in a wild fire chronosequence. They found that near

infrared analysis was a powerful and inexpensive substitute for soil quality assessments

compared to other conventional analysis.

Soil quality effects of tillage and residue under rice-wheat cropping on

vertisol in India was determined by Mohanty et.al., (2007). They developed a soil

quality index by regressing bulk density, penetration resistance, and organic matter on

crop yield for a right wheat cropping system on a vertisol in India, showed ranges of

0.84-0.82, 0.88-0.93 and 0.86-0.92 respectively. Finally they concluded that indices

developed were only for a vetisol, their method used to develop them could easily be the

extended to other soil with varying crop system and climatic condition.

Teklu Erkossa et.al., (2007) analyzed the indexing soil quality: A new

paradigm in soil science research. They compared the effects of land preparation

methods on soil quality (SQ) and use of the soil management assessment framework

(SMAF) in assessing SQ the ethiopian central highlands conditions was tested. They

concluded that SMAF could be a robust tool to assess the performance of land

management methods on soil quality at coffee doons but some modifications may be

required to fit to the prevailing cropping system and soil characteristics.

31

Vijayarengan and Deepthy Jose (2013) analysed the Phytoremediating

capability and nutrient status of four plant species under copper stress. They denoted that

the 50 mg kg-1 level of copper in the soil was beneficial for the nutrient status of Indian

mustard, maize, cotton and watermelon plants. The level of copper in the soil above 50

mg kg-1 proved to be toxic. The results indicated that the 50 mg kg-1 copper level can be

applied for increasing the nutrient status of Indian mustard, maize, cotton and watermelon

plants.

Vijayarengan and Mahalakshmi (2013) studied zinc toxicity in tomato

plants. They found that zinc treatment at all levels tested (except 50 and 100 mg kg-1)

decreased the various growth and yield parameters such as length of the root and shoot,

area of leaves and dry weight of root and shoot of tomato plants. However the 50 and 100

mg/ kg zinc level in the soil showed a positive effect on the overall growth and dry matter

yield of tomato plants.

Changes in growth, biochemical constituents and antioxidant potentials in

cowpea under cobalt stress was analysed by Packirisamy Vijayarengan (2012). He

found that the cobalt treatment at all levels tested (except 50 mg kg-1) decreased the

various growth parameters such as length of the root and shoot, number of nodules, area

of leaves and dry weight of root and shoot; biochemical constituents (pigments, sugars,

starch, amino acids and protein contents of leaves) of cowpea plants. However proline

and the enzymes increased (except 50 mg kg-1) with an increase in cobalt level in the soil.

Effect of toxic heavy metal contaminated soil on an ornamental plant

Georgina wild (dahlia) was studied by Lovely Shivhare et.al., (2012). It was also

32

observed that the shoots of the dahlia are more tolerant than roots of dahlia plant and the

biomass and seed germination also affected by the nickel and lead toxicity above the

normal concentration.

Manivasagaperumal et.al., (2012) described the effect of zinc on growth,

dry matter yield and nutrient content of Vigna radiata (L.) wilczek. Their results indicated

that low level zinc concentrations (50 and 100 mg kg-1 ) showed a significant increase in

the overall growth, dry matter yield and nutrient content, while higher concentrations

(150-250 mg kg-1) decreased the growth, dry matter production and nutrient content of

greengram.

Vijayarengan (2012) analysed the growth and biochemical variations in

radish under zinc applications. He concluded that the 50 and 100 mg kg-1 level of zinc in

the soil was beneficial for the growth of radish plants. The level of zinc in the soil above

150 mg kg-1 proved to be toxic. The results indicated that the zinc levels 50 to 100 mg kg-

1 can be applied for increasing the growth and yield of radish plants.

Phytoremediating capability and nutrient status of four plant species under

zinc stress was described by Sivasankar et.al., (2012). They concluded that the 50-100

mg kg-1 level of zinc in the soil was beneficial for the growth of chilli, marigold, mustard

and pigeon pea plants. The level of zinc in the soil above 150 mg kg-1 proved to be toxic.

The results indicated that the 50-100 mg kg-1 zinc level can be applied for increasing the

growth and yield of chilli, marigold, mustard and pigeon pea plants.

Response of nickel pollution on physiological and biochemical attributes

of wheat (triticum aestivum l.) was evaluated by Asifa shafeeq et.al., (2012). They

33

explained that, the excess nickel concentration altered the fundamental physiological

processes like photosynthetic and transpiration activities and also they found that

chlorophyll contents decreased with increasing nickel levels.

Effect of heavy metals on some biochemical parameters of sal (shorea

robusta) seedling at nursery level was studied by Preeti pandey pant et.al., (2011). Total

chlorophyll, amino acid, proline and ascorbic acid content were measured in the leaves of

the six month old seedling with the help of UV Spectrophotometer. Their results showed

that the total chlorophyll and amino acid content decreased with increased concentrations

of heavy metals.

Vijayaragavan et.al., (2011) described the changes in growth,

photosynthetic responses and biochemical contents of carrot plants under cadmium

toxicity. They exposed that cadmium at all levels (10,30 and 50mg kg-1) tested, decreased

the growth parameters such as root and shoot length, number of leaf, total leaf area,

photosynthetic responses such as photosynthetic rate and stomatal conductance and

biochemical constituents such as total chlorophyll, carotenoid and total sugar contents of

carrot plants compared to untreated plants.

Anantharaj et.al., (2011) evaluated by effect of heavy metals on Marine

Diatom Amphora Coffeaeformis (Agardh. Kutz). They indicated that, high concentration

of heavy metals copper and cadmium could affect the A.Coffearformis by reducing its

growth and biochemical compositions.

Khin S.Aye (2011) investigated the effectiveness of zinc sulphate and

biofertilizer on mustard plant. He found that the treatment using a mixture of zinc

34

sulphate and biofertilizer had the best yield (4688.008 kg/ha) within 50 days of sowing

and performed better than other treatments. Field experiment using zinc sulphate only

was second best yield (3380.75Kg/ha) and biofertilizer only treatment gave

(2639.04kg/ha).

The dynamics of heavy metals in plant–soil interactions evaluated by

Sebastian.et.al., (2010). They suggested that at low concentrations, the effects of heavy

metals are moderate, and the dynamics seem to be linear. However, increasing

concentrations exhibit nonlinear behaviours.

Abdul Jaleel,et.al., (2009) studied the antioxidant potentials protect Vigna

radiata (L.) Wilczek plants from soil cobalt stress and improve growth and pigment

composition. They concluded that antioxidant enzymes like catalase, peroxidase and

polyphenol oxidase activities were analysed from both control and treated plants. All the

growth parameters and pigment contents increased at 50 mg/kg cobalt level in the soil,

when compared with control. Further increase in cobalt level (100-250 mg/kg) in the soil

had a negative impact upon all studied parameters. From these results it is clear that

antioxidant potentials act as a protective mechanism in Vigna radiata under soil cobalt

stress.

Jayakumar et.al., (2009) evaluated cobalt induced variations in growth

and pigment composition of Arachis hypogaea L. They revealed that the growth

parameters and pigments have beneficial value at 50 mg/kg Co level in the soil, when

compared with control. Further increase in the Co level (100-200 mg/kg) in the soil has a

negative effect on these parameters. From these results it is clear that low concentration

of cobalt can be used as enhancer of A. hypogaea.

35

Effect of different concentrations of cobalt on morphological parameters

and yield components of soybean was studied by Jayakumar et.al., (2009). They

revealed that the yield increased due to the cobalt treatment to the soybean plants at

lower concentration only. The main advantageous yield was noted only in 50 mg/kg of

cobalt in soil. At higher concentration of cobalt in soil (from 100-250 mg/kg) there was a

marked reduction in yield parameters.

Chen et.al. (2009) analysed the functions and toxicity of nickel in plants.

They described the excess Ni inhibits growth and development of plants, induces leaf

chlorosis and wilting and reduces total plant yields. Nickel toxicity also disrupts

photosynthesis and alters related enzyme activities.

Effect on plant growth, biochemical parameters and metal accumulation

by Brassica juncea L. Studied by John et.al., (2009). Their results indicated that the

exposure of B. juncea to Cd and Pb results is a decrease in growth, pigment content and

at lower concentration of heavy metals increase in protein and proline was observed but

at higher concentrations it was decreased.

Aydinalp and Marinova (2009) studied the effects of heavy metals on

seed germination and plant growth on Alfalfa plant (Medicago sativa). Their results

indicated that the Alfalfa plant may be grown directly in soils individually contaminated

with moderate amounts of 𝐂𝐝+𝟐,𝐂𝐫+𝟐, 𝐂𝐮+𝟐 and 𝐍𝐢+𝟐. Detailed studies need to be done

in order to establish the maximum amount of 𝐙𝐧+𝟐 that the plants may tolerate and the

ability of the alfalfa plants to germinate and grow in media containing mixtures of these

heavy metals.

36

Gokulakumar and Narayanasamy (2008) studied FT-IR spectra analysis

of root rot disease in sesame (sesamum indicum). They correlated the extinction

coefficient (k) values with the changes in diketopiperazine of the root rot diseased roots

in sesame varieties.

FT-IR analysis of a plant (Calotropis Gigantea Linn) from an industrial

village was evaluated by Ramamurthy and Kannan (2007). They concluded that FT-IR

spectrum is able to predict the main chemical constituents in plant materials and also

compared the quantitative differences among the similar samples.

Impact of heavy metal toxicity on plant growth, symbiosis, seed yield and

nitrogen and metal uptake in chickpea was evaluated by Wani et.al., (2007). They stated

that the degree of toxicity of heavy metals on the measured parameters decreased in the

following order: cadmium, zinc, nickel, copper, chromium, then lead. Accumulation of

heavy metals was higher in the roots relative to the shoots of chickpea and was

significantly correlated with the concentration of the metals added to the soil.

Luisa Louro Martins and Miguel Pedro Mourato (2006) was described

the effect of excess copper on tomato plants growth parameters, enzyme activities,

chlorophyll, and mineral content. They highlighted the activities of three enzymes studied

in leaves (guaiacol peroxides, catalase and polyphenol oxidase increased transiently,

probably as an early response mechanism against Cu induced oxidative stress. At higher

Cu concentrations, this defense mechanism broke down and the activities of the enzymes

decreased accordingly.

Effects of some heavy metals on content of chlorophyll, proline and some

antioxidant chemicals in bean (Phaseolus Vulgaris L.) seedlings studied by Fikriye

37

Kirbag Zengin, and Mer Munzuroglu (2005). Their results showed that lead, copper,

cadmium and mercury toxicity decreased the total chlorophyll content of the leaves of

bean seedlings.

Effects of heavy metals on plant growth and photosynthetic activity was

studied by Servilia Oancea et.al.,(2005). They exhibited that effects of heavy met

als on plants resulted in growth inhibition, structure damage, a decline of physiological

and biochemical activities, as well as of the function of plants.

Oxidative changes and photosynthesis in oat plants grown in as-

contaminated soil was studied by Nevena Stoeva and Tzvetanka Bineva (2003). Their

physiological analysis showed a small negative effect of arsenic at concentration of 40

mg per kg soil, but the higher dosages of 80 and 160 mg per kg soil, generated stress in

oats plant and as a consequence leaf gas-exchange was suppressed. The chlorophyll

fluorescence ratio decreased. The chlorophyll and protein content also decreased.

Rana Athar and Masood Ahmad (2002) evaluated the heavy metal

toxicity effect on plant growth and metal uptake by wheat, and on free living

Azotobacter. Their results revealed that heavy metals brought about significant

reductions in plant growth and grain yield parameters.

38

1.8. OBJECTIVES OF THE PRESENT STUDY

The present work has been designed with the following prime

objectives in view, They are

i) To explain the methodological aspects of ANFIS and statistical modelling.

ii) To predict the biological oxygen demand and chemical oxygen demand

values of Engineering works industry and Pharmaceutical industry

effluents through ANFIS and statistical modelling.

iii) To predict the soil suitability of greens and paddy growing soils.

iv) To give a scientific validation in terms of physico - chemical analysis.

v) To study the beneficial and toxic effects of zinc , iron and cadmium on

the greens through Fourier transform infrared ( FT- IR ) spectroscopic

technique.