FORESTRY, ENVIRONMENT AND SUSTAINABLE DEVELOPMENT · Ibom State, Nigeria. Nneke, N. E. 97-101...

JOURNAL OF

FORESTRY, ENVIRONMENTAND SUSTAINABLE DEVELOPMENT

Volume 3 Number 1 (March) 2017

Published byDEPARTMENT OF FORESTRY AND NATURAL ENVIRONMENTAL MANAGEMENT

FACULTY OF AGRICULTUREUNIVERSITY OF UYO

www.uniuyo.edu.ng (Journal, Department)

ISSN: 2449-1845

JOFESD VOL. 3 No. 1 Published March, 2017

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UNIVERSITY OF UYO, UYO

DEPARTMENT OF FORESTRY AND NATURAL ENVIRONMENTAL MANAGEMENT

JOURNAL OF FORESTRY, ENVIRONMENT AND SUSTAINABLE DEVELOPMENT (JOFESD).

Editorial Advisers

Prof. L. C. Nnabuife - Nnamdi Azikiwe University, Awka, Anambra State, Nigeria

Prof. Labode Popoola - University of Ibadan, Ibadan, Nigeria.

Prof. Emmanuel I. Inah - University of Ibadan, Ibadan, Nigeria.

Prof. Pius O. Egwumah - University of Agriculture, Markurdi, Nigeria.

Prof. Luca M. Luiselli - Institute Demetra, via Olona, Rome, Italy.

Editorial Board

Editor-in-Chief: Prof. Enefiok S. Udo

Editor: Prof. Michael Akpan

Managing Editor: Dr. Samuel I. Udofia

Assitant Editor: Dr. Opeyemi Olajide

Associate Editors: Dr. Edem A. Eniang

Dr. I. N. Akpan-Ebe

Dr. (Mrs.) Mercy P. Akpan

Dr. E. E. Ukpong


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JOURNAL OF FORESTRY, ENVIRONMENT AND SUSTAINABLE DEVELOPMENT (JOFESD) is published biannually by the Department of Forestry and Natural Environmental Management, Faculty of Agriculture, University of Uyo, Uyo, Akwa Ibom State, Nigeria. All Rights Reserved: No parts of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, photocopying, recording or otherwise without prior written permission of the Copyright. Also, where part of this Journal is adapted, credit must be given to the author(s) and original source and the sense of the original source must not be distorted. ISSN: 2449-1845 Printed in Nigeria by: Wilonek Publishers Uyo Tel: +2348115160434


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JOURNAL OF FORESTRY, ENVIRONMENT AND SUSTAINABLE

DEVELOPMENT (JOFESD) DEPARTMENT OF FORESTRY AND NATURAL ENVIRONMENTAL

MANAGEMENT UNIVERSITY OF UYO, UYO, NIGERIA

CALL FOR PAPERS The Editorial Board of Journal of Forestry, Environment and Sustainable Development (JOFESD), hereby calls for scholarly research papers/articles on relevant issues in Nigeria, Africa and Global on Forestry/Forest Science, Wildlife Management, Environmental Sciences, Agriculture, Natural Sciences, Engineering/Technology, Social Sciences and other related areas for publication in the journal. The journal shall be published biannually (March and August). GUIDELINES FOR SUBMISSION OF PAPERS

Articles should be type-written with double-line spacing on face only, not more than 15 pages of A4 paper including reference, diagrams, pictures and appendices on 12 font size, Times New Roman font style and the new APA Referencing style.

The cover page should bear the title of the Paper/Article, the author’s (s’) name(s), affiliation, e-mail address and phone number.

Article should be accompanied with an abstract of not more than 250 words containing statement of problem, methodology, result and recommendations/ contributions to knowledge.

Authors should submit hard copies of their articles to the Editor-in-chief, Journal of Forestry, Environment and Sustainable Development (JOFESD) Department of Forestry and Natural Environmental Management, University of Uyo, P.M.B. 1017, Uyo, Akwa IbomState, Nigeria.

A soft copy of the paper/article should be sent on-line as an attachment to e-mail address: [email protected], [email protected] and copied [email protected] after paying an assessment fee of Two Thousand Naira (N2,000.00) or Twenty US Dollars ($20).

All manuscripts shall be peer reviewed to ensure accuracy and relevance. A manuscript will be accepted for publication sequel to the referees’ recommendation. We welcome original manuscripts that have not been submitted elsewhere for publication. Copyright of all accepted articles are ceded to JOFESD. For more enquiries, send an e-mail to [email protected] or [email protected] or [email protected] or [email protected].


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TABLE OF CONTENTS

PAGE(S)

Composite Indices of Living Standards of Communities in the Support Zones of Three National Parks in North-east Nigeria. Buba Zacharia Yaduma, Akosim Callistus and Akpan Michael

1-7

Pathogenicity of Black Pod Disease of Cocoa Pathogen in Ini Area, Akwa Ibom State. Nneke, N. E.

8-12

Ecology and Ethnobotany of Okoubaka aubrevillei Pellegr. & Norman: Viewpoint of Conservators and User Groups in Edo State, Nigeria. E. E. John-Onyijen and E. M. Isikhuemen

13-24

Population Growth and Damage Caused by Maize Weevil (Sitophilus zeamais Mots.) to Stored Maize Grains. Ime O. Udo

25-27

Impact of Coastal Erosion on Alpha Beach Community in Lagos, Nigeria. Maureen. N. Chukwu

28-34

Height-diameter Prediction Model for Ehor Tropical Natural Forest Reserve in Nigeria. Aigbe, H. I. and Amadi, I.

35-45

Effect of Different Land Use on Soil Microbial Biomass Carbon and Nitrogen in Acid Sand, Uyo, Nigeria. Godwin U. Akpan and Mohammed Iliyasu

46-55

An Assessment of Socio-Economic Status of Communities in National Parks of North-Eastern Nigeria. Buba Zacharia Yaduma

56-70

Size Composition and Growth Pattern of By-Catch Marine Crabs Callinectes amnicola off the Atlantic Coast, Southeast Nigeria. James Philip Udoh

71-88

Effect of Organic Fertilization on Yield Productivity of Cassava (Manihot esculenta Crantz) in Uyo, Southeastern Nigeria. Opara, A.C., Ikeh, A.O. and Etokeren, U. E.

89-96

Occurrence of Cercospora Leaf Spot Disease of Okra in Itu, Akwa Ibom State, Nigeria. Nneke, N. E.

97-101

Effect of Adhesives on the Strength Properties of Particle Board Manufacture from Sawdust of Different Wood Species. D. N. Izekor and I. Edealo

102-108

Impact of Crude Oil Spillage on Maize Plant (Zea mays L.) in Upenekang in Ibeno Local Government Area of Akwa Ibom State, Nigeria. Ndeh, E. S., Okafor, J. O., Akpan, U. G. and Olutoye, M. A.

109-114


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Spatio-Temporal Variations in the Benthic Macro-Invertebrate Communities of Stubbs Creek, South-Eastern Nigeria. Obot, O. I and Nicholas Eteobong

115-124

Effects of Leguminous Cover Crops and Densities on White Yam (Dioscorea rotundata Poir) Yield and Pest Severity at Harvest. Ikeh, A. O., Etokeren, U. E., Nwanne, A.J., Chinaka, I.C., and Essang, I. P.

125-135

A Comparative Study on Organic and Inorganic Method of Farming in Improving the Nutritional Quality of Ocimum gratissimum. Ekpo, F. E. Okey, E. N and Njoku, K. U.

136-142

Impact of Flood Disaster on Soil Quality Dynamics in Agro-Ecological Zone of Ebonyi State, Nigeria. Ubuoh, E. A. Uka, A. and Egbe, C.

143-153

Effects of Crop Residue Ash Application on Soil, Cowpea Yield and Economic Return to Management in Uyo, Niger Delta Region of Nigeria. Ikeh, A. O., Etokeren, U. E., Essien, I. E., Udo, E. A., Ukut, A.N. and Nwanne, A. J.

154-165

An Assessment of the Profitability of Cassava Processing in Edo State, Nigeria. Izekor. O.B. and Ilavbarhe, K.O.

166-173

The Effect of Atmospheric Nitrogen Dioxide Pollutant Distribution on Human and Plants in Akwa Ibom State. Eka, B. J. and Dike, M. C.

174-185


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COMPOSITE INDICES OF LIVING STANDARDS OF COMMUNITIE S IN THE SUPPORT ZONES OF THREE NATIONAL PARKS IN NORTH-EAST NIGERIA

Buba Zacharia Yaduma, Akosim Callistus and *Akpan Michael Department of Forestry and Wildlife Management, Modibbo Adama University of

Technology, Yola, Adamawa State *Department of Forestry and National Environmental Management, University of Uyo,

Uyo, Akwa Ibom State

ABSTRACT

This study analysed the socio-economic benefits of the support zones communities in the North-East Nigeria National Parks. The parks include Chad Basin National Park (CBNP), Gashaka Gumti National Park (GGNP) and Yankari National Park (YKNP). The objective of the study is to determine the Composite Index of Level of Living Standards (CILLS) of the selected communities. The support zone communities were selected by purposive sampling method. The instrument used for the study was questionnaire and oral interviews. The respondents were selected by random sampling method, while the parks’ management were interviewed on pre-determined questions. Inferential statistics were used to analyse the data collected. Results of the CILLS varied from 1.98 for Amchaka community in CBNP to 2.24 in Gashaka community of GGNP. The results showed low standard of living (LSL) of the communities across the three National Parks. It is recommended that the management of the three National Parks (CBNP, GGNP and YKNP) should be more responsive to their mandate in the area of provision of socio-economic facilities to the communities.

INTRODUCTION National Parks are natural ecosystems with unique attributes, playing special roles vital to national wellbeing. Apart from providing nature for eco-tourism, these protected areas enhance ecological processes and life support systems. For example, they enhance the process of soil regeneration, protection of nutrient cycles, environmental protection, as well as cleaning and purifying hydrological cycles. National Parks have been scientifically defined as relatively large areas of land or water where the ecosystems are not materially altered by human exploitation and occupation (IUCN, 2002). They are environments where plant and animal species, geo-morphologic sites and habitats are of special scientific, educational and recreational interest, which also contains a natural landscape of great beauty (IUCN, 2002). They play a central role in the social and economic development of rural environments where they are located. They also contribute to enhance the quality of life of all those who visit the project and improve the economic development of a country (Sheer, 2006).

However, there is a growing concern globally, over the destruction and eventual disappearance of valuable fauna and flora species on the tropical forests. Estimates suggest that the annual bush meat harvest from Africa’s tropical forest may now exceed one million tones (Tim, 2009). Despite the protection being given to the wildlife species within the conservation areas, there are still wide spread poaching activities in the National Parks mainly for the supply of bushmeat and trophies. Other activities such as bush burning, illegal grazing, farming, fishing and extraction of non-timber forest products are also carried out illegally in the National Parks (Akosim et al., 2010). Information is particularly lacking about the socio-economic and cultural activities of the local people around the parks and the effects of these on the conservation of the National Parks resources.

Yaduma B. Z et al. (2017). Composite Indices of Living Standards of Communities in the Support Zones of Three National Parks in North-east Nigeria. Journal of Environment and Sustainable Development, 3(1): 1-7


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The modern approach to conservation recognises the importance of achieving social and economic development along-side the proper protection of the natural and cultural heritage (Akosim et al, 2007). The Park authority needs to give special attention to approaches that sustain the local communities in and around the Park support zone areas. This implies that development options should be particularly geared towards those areas which can provide sustainable benefits to local people, rather than to meet wider economic aspirations. More can still be done to engage local people in the planning and management of their areas. What the situation is at present in the support zone of the National Parks in the north east zone of Nigeria is not documented, hence the need for this research to establish the social benefits of the buffer zones of three National Parks in north-east Nigeria.

MATERIALS AND METHODS

Study Location The study was conducted in the support zones of three National Parks in the north-east Nigeria. These Parks are: Chad Basin National Park (CBNP), Gashaka-Gumti National Park (GGNP) and Yankari National Park (YKNP). Chad Basin National Park (CBNP) Chad Basin National Park covers an area of 2,258 square kilometers. The park is dotted across Borno and Yobe States and the sectors are Chingurmi-Daguma, Bade-Nguru wetlands and Kilboa Forest (Bulatura Oases). The Parks is geographically situated between latitude 11°00' to 13°00'N and Longitude 13°00' to 15°20'E. Generally Borono and Yobe States experience dry arid type of climatic conditions, with mean annual temperature ranging from 28°C – 29°C. However, the maximum temperature rises to over 48°C at the onset of the rains. The two States experience cool temperature between December and February (the harmattan) period) with mean temperatures ranging from 20°C – 23°C. The area is characterized by two seasons, a long dry season and a short rainy season. The mean annual rainfall in the Sahel is about 180mm per annum. It commences in July and ends in October, whereas the dry season lasts for about 7 – 8 months (from November to June) (Marguba, 2002).

Gashaka-Gumti National Park (GGNP) Gashaka-Gumti National Park is the largest of the eight National Parks in Nigeria, covering an area of 6,731 square kilometers. It lies between 6° 55' and 8° 05' Latitude North, and between 11° 11' and 12° 13' Longitude east. The Park boundaries and land mass fall within Adamawa and Taraba States. The topography of the Park is hilly and mountainous with plains rising between 300m and 600m in altitude which are interrupted by escarpments to undulating rugged highlands with peaks rising between 600m and 1,850m above sea level. The climate varies from micro climate weather condition according to the location in the Park. The weather ranges from tropical dry humid, tropical moist humid in the low lands to sub-tropical temperature climate on the high plateau of Chappal Hendu, Chappal Shirgu, Sabere and Chappal Waddi, Mambilla Plateau which is mostly cool, cloudy, misty and breezy like that of Mediterranean region.

Yankari National Park (YKNP) Yankari is the nation’s first game reserve with an area of 2,244.10 sq. km. The Park lies within the Sudan Savannah vegetation zone with a vegetation complex known as Bukea africana/Combretum glotinosum type while the swamp flood plain of Gashi and Yashi support mosaic vegetation. It is situated within Duguri, Pali and Gwana Districts of Alkaleri Local Government Area of Bauchi State on coordinates 09° 45'N and 10° 30'E. The Park


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boundaries and land mass fall within Bauchi States of Nigeria and shares boundary with Plateau and Gombe States (Marguba, 2002).

Study Design and Data Collection The study was conducted in the support zones of the three National Parks located in the North-East geo-political zone of Nigeria. They accounted for 37.5% of the existing national parks in the country, and the geographical spread of the three national parks confers considerable distinctions on them, in terms of ecology of the parks as well as culture and socio-economic disposition of the support zones. Moreover, the three parks have a mosaic of features found in all the other national parks in Nigeria, hence their representativeness. The population of each community and copies of distributed questionnaire in each community of the National Parks are presented in Table 1.

Study Tools and Sampling Technique: Structured questionnaire for the support zone dwellers and interview with parks’ managements were the tools used in this study. Purposive sampling method was used in selecting National Parks and Support Zone Communities. Random sampling technique was used in selecting respondents in the support zone communities. Random sampling method was used to select not less than two hundred (200) respondents in each of the support zone communities found sharing boundary with the national park. From each community, not less than thirty (30) respondents were selected for the study (Table 1).

Table 1: Population of communities and questionnaire administered

National Parks State Community Population of community

Questionnaire distributed

Chad Basin Borno/Yobe Daguma 107 40 Bulatura 110 40 Amchaka 100 40 Chingurmi 110 40 Yusufari 100 40 Gashaka Gumti Adamawa/Taraba Tikobi 117 50 Gumti 133 50 Gashaka 133 50 Mayo-Salbe 117 50 Yankari Bauchi Maina-Maji 100 40 Yelwa-Dukuri 100 40 Pali 100 40 Yello 100 40 Baggos 100 40 Total 14 1,527 600

Data Collection Six hundred (600) copies of the questionnaire were administered to the respondents; however, only four hundred and fifty eight were returned (Table 2). The questionnaire was designed to collect data on socio-economic indicators: health, schools, schools, portable water, road, electricity, employment, housing, ownership of mobility, electronics, agricultural productivity and income earnings of the respondents.


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Table 2: Copies of questionnaire retrieved from the respondents National Parks State Community Population of

community Questionnaire

retrieved Chad Basin Borno/Yobe Daguma 107 32 Bulatura 110 33 Amchaka 100 30 Chingurmi 110 33 Yusufari 100 30 Gashaka Gumti Adamawa/Taraba Tikobi 117 35 Gumti 133 40 Gashaka 133 40 Mayo-Salbe 117 35 Yankari Bauchi Maina-Maji 100 30 Yelwa-Dukuri 100 30 Pali 100 30 Yello 100 30 Baggos 100 30 Total 14 1,527 458

Data Analysis Computation of Composite Index of level of living standards (CILLS) was the Composite Index of Level of Living Standard (socio-economic wellbeing) of people resident around the National Parks was computed using the model of Singh and Dhillon (2004). The details of the model are as follows: the socio-economic indicators (health, schools, water, road, electricity, employment, housing, ownership of mobility, electronics, agricultural productivity and income) were assessed on a three point scale from 1 to 3 as described by Ogunleye (2002), where one (1) represents poor, two (2) represents fair and three (3) represents good. The total of these scores was found for each indicator, for each community and for all the sampled communities in the support zones of the National Parks. The detail of the model is stated as follows:

CILLS = HCe

HCr+SCe

SCr+RDe

RDr+WTe

WTr+ELe

ELr+EMe

EMr+HOe

HOr+OMe

OMr+ETe

ETr+APe

APr+INe

INr

Where: CILLS = Composite Index of Level of Living Standard HC = Health SC = Schools RD = Road WT = Water EL = Electricity EM = Employment HO = Housing OM = Ownership of mobility ET = Electronics AP = Agricultural productivity IN = Income earnings E = Communities R = Support zones ΣLQs = Summation of location quotients which gives the CILLS


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The higher the CILLS the higher the socio-economic wellbeing and vice versa. The range of values from 0 – 4.99 implies low standard of living (LSL), 5 – 6.99 represents moderate standard of living (MSL) while 7 – 10 implies high standard of living (HSL).

RESULTS

The composite index of level of Living standard of respondents obtained from five communities in CBNP is presented in Table 3. The table shows that Chingurmi community had the highest CILLS of 2.20 while Amchaka community had the least of 1.98.

Table 3: Composite Index of Levels of Living Standard of Respondents in Five Communities in Chad Basin National Park

S/NO Community CILLS Remarks 1. Daguna 2.04 LSL 2. Bulatura 2.00 LSL 3. Amchaka 1.98 LSL 4. Chingurmi 2.20 LSL 5. Yusufari 2.06 LSL

Respondents’ Composite Index of Level of Living Standard (CILLS) in Tikobi, Gumti, Gashaka and Mayo Salbe communities of GGNP are presented in Table 4.9. Gashaka had the highest CILLS of 2.24, while the least (2.18) was obtained in Gumti community.

Table 4: Composite Index of Level of Living Standard of Respondents in four Communities of Gashaka Gumti National Park

S/NO Community CILLS Remarks 1. Tikobi 2.21 LSL 2. Gumti 2.18 LSL 3. Gashaka 2.24 LSL 4. Mayo-Salbe 2.20 LSL

Results of the Composite Index of Level of Living Standard (CILLS) for communities in YKNP are presented in Table 5. The results showed that Yello community had the highest CILLS of 2.21 while Maina Maji, Yalwa Dukuri, Pali and Baggos recorded equal index of Living Standard.

Table 5: Composite Index of Level of Living Standard of Respondents in four Communities of Yankari National Park

S/NO Community CILLS Remarks 1. Maina-Maji 2.20 LSL 2. Yelwa-Dukuri 2.20 LSL 3. Pali 2.20 LSL 4. Yello 2.21 LSL 5. Baggos 2.20 LSL


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DISCUSSION AND CONCLUSION Results of Composite Index of Level of Living Standard (CILLS) in the support zone communities of the three national parks in the north-east Nigeria (CBNP, GGNP and YKNP) revealed that the highest CILLS of 2.24 was obtained in Gashaka community in the support zone of GGNP. The least CILLS of 1.98 was obtained in Amchaka community in the support zone of CBNP. According to Singh and Dhillon (2004), the range of values of 0 – 4.99 CILLS indicates low level of socio-economic wellbeing; 5 – 6.99 indicates moderate level while 7 – 10 shows high level of socio-economic wellbeing of the people. Therefore, the CILLS obtained for all the communities in all the three support zones in this study fall within low level of socio-economic wellbeing. The implication of the results is that the management of the three national parks have not met its mandate in the area of provision of socio-economic infrastructure that could serve as a platform for the upliftment of the standard of living of the people. This agrees with the reports of Gawaisa (1997), WCPA (2000), Okeyoyin (2009), Saidu (2010), and Marguba (2002) that infrastructural provisions such as roads, schools, clinics, electricity, water, agricultural products and employment opportunities to the support zone dwellers are mandates given to the park management for the socio-economic transformation of the local communities. This in turn attracts the support of the local communities for the park project. Therefore, any negative attitude or negative perception of the local residents may not be unconnected with the inability of the parks to play their statutory role of providing necessary infrastructures to the support zone communities. The Composite Index of Level of living Standard in all the communities across the three parks indicated low standard of living (LSL). Thus, the provision of socio-economic facilities in the communities in the support zones is inadequate, hence it can not impart positively on the local dwellers socio-economic wellbeing.

RECOMMENDATION Government should sufficiently fund the parks to enable the management carry out their statutory role of providing more socio-economic facilities in the support zone communities.

REFERENCES

Akosim, C., Yaduma, Z. B., Gawaisa, S. G. and Mamman, G. S. (2007). Evaluation of the relative importance of five principal forest reserves for biodiversity conservation in Adamawa State, Nigeria.

Akosim, C., Bode, A. S., Kwaga, B. T. and Dishan, E. E. (2010). Perception and involvement of neighboring communities of Kainji Lake National Park towards the parks conservation programme. Journal of Research in Forestry, Wildlife and Environment, 2(1 and 2): pp.1117-4196.

Gawaisa, S. G. (1997). Status of large mammals and impact of human activities in Gashaka Gumti National Park, Nigeria. B. Tech. Thesis, Federal University of Technology, Yola, p. 46.

IUCN (2002). Communiqué on links between Biodiversity Conservation and Food Security: The sustainable use of wildlife species for meat. IUCN Switzerland.

Marguba, B. (2002). Nigeria National Parks their significance and potentials to the nation. The Magazine of the Nigerian National Parks Vol. 1, No. 1, pp. 7-10.

Ogunleye, O. A. (2002). An Introduction to research method in education and social sciences. Ibadan: Sunshine International Publications (Nig.) Ltd. pp. 58-78.

Okeyoyin, O. A. (2009). Impact of livelihood activities of local communities on wildlife resources in Kainji Lake National Park, Nigeria. Ibadan Press, p. 23.


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Saidu, B. A. (2010). Conservation of wildlife resources in relation to sustainable rural development in neighbouring communities of Kainji Lake National Park. B. Tech. Thesis, Federal University of Technology, Yola.

Sheer, M. (2006). The Benefits of Parks: Why America Needs More City Parks and Open Space, Trust for Public Land. Pp. 20-23.

Singh, J. and Dhillon, S. (2004). Agricultural Geography. (3rd Edition). India: Tata McGraw-Hills Publishing Company Limited.

Tim, P. (2009). Regeneration and environment: Socio-economic wellbeing of local communities. Available at mhtml//www.wlga.clilc/nationalparks/ (Accessed 8th January 2009).

WCPA (World Commission on Protected Area) (2000). Protected Area: Benefits Beyond Boundaries. World Commission on Protected Area in Nigeria. The World Conservation Union (I.U.C.N.), p. 88.


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PATHOGENICITY OF BLACK POD DISEASE OF COCOA PATHOGE N IN INI AREA, AKWA IBOM STATE.

Nneke, N. E. Department of Crop Science, University of Uyo,

P.M.B 1017, Uyo, Akwa Ibom State ([email protected], 07031110980)

ABSTRACT Disease surveys were conducted in four cocoa growing communities in Ini Local Government Area of Akwa Ibom State, namely: Ikpe Ikot Nkon, Ekoi Ikpe, Itu Mbonuso, and Ibam Edet. The studies were carried out at the peak of the rainy season (July-September) in two consecutive years: 2013 and 2014, to determine the status of black pod disease of cocoa incited by Phytophthora palmivora in these locations and the susceptibility to the pathogen of two varieties of cocoa (Amazon and D-38), commonly grown in the area. The results showed that disease incidence and severity (48.3% and 3.2) respectively were highest in the Amazon variety of cocoa in Itu Mbonuso community, and lowest (10.6% and 1.0) respectively in the D-38 variety of cocoa in Ibam Edet Community. Laboratory studies showed that, the infection rate of the pathogen were significantly (P=0.05) higher (1.2mm/day) on the Amazon variety than D-38 variety (0.4mm/day). Keywords: Survey, Phytophthora palmivora, incidence, severity, pathogenicity, Ini.

INTRODUCTION Cocoa (Theobroma cocao L.) is an important cash crop in the developing countries of the humid tropics. Africa and especially West Africa, is the leading producer of cocoa in the world, responsible for an estimated 65% of the world’s total output of 2.7 billion tonnes (FAO, 1981, De Latter-Gasquet et al, 1998). Nigeria is the world’s fourth producer of cocoa, accounting for more than 169,000 metric tonnes in the 10 year period between 1980-1991 and a per hectare yield of 338kg annually (FAO, 1981). Cocoa in Nigeria is grown mainly in the south western and south eastern parts of the country, with Abia State as the major production centre in South-eastern Nigeria. (De Latter-Gasquet et al, 1998).

The black pod disease of cocoa incited by Phytophthora palmivora is the most important and widely distributed fungal disease of cocoa worldwide (Raemaekers, 2001). Species of the pathogen persist in the soil and reach tree trunks by rain splash during the wet season or are carried up by tent-building ants thereby infesting pods and other parts of the cocoa plant at relative humidities of 60-80% and temperatures of 20-300C (Lass and Wood, 1985, Raemaekers, 2001). All black pod diseases of cocoa were attributed to one species of the pathogen P. palmivora, a fungus that has attained a very wide distribution within the humid tropics because of the diversity of its host range in all cocoa-growing areas (Raemaekers, 2001). Various species of the pathogen such as P. palmivora, P. megakarya and P. infestans have been implicated in the incidence of the black pod disease of cocoa in Nigeria, Cameroon and in various other parts of West Africa, but the most virulent are known to be P. palmivora and P. megakarya (Raemaekers, 2001). Other species of Phytophthora namely, P. capsici and P. citrophthora are known to be destructive to cocoa pods in Brazil. These species are different from one another in cytology, morphology, ecology and pathogenicity (Lass and Wood, 1985). Economic losses due to the black pod disease in Nigeria and elsewhere are difficult to estimate in view of the fact that the incidence of the disease is weather-dependent, being highest when much rainfall coincides with the later stages of pod

Nneke, N. E. (2017). Pathogenicity of Black Pod Disease of Cocoa Pathogen in Ini Area, Akwa Ibom State. Journal of Environment and Sustainable Development, 3(1): 8-12.


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development and lowest in that part of the crop that matures in the dry season (Filani, 1973). Differences in varietal susceptibility also influence damage (Lass and Wood 1985). However, the disease constitutes a serious constraint to cocoa production, leading to losses of about 10% worldwide, 44% in west and central Africa (Lass and Wood, 1985, Neil, 2002). In Nigeria, production and revenue losses of 80-90% have been reported (Raemaekers, 2001). Therefore, this study was conducted to assess the current black-pod disease of cocoa on two widely grown varieties of cocoa (the Amazon and the D-38) in Ini Local Government Area of Akwa Ibom State as well as to determine the pathogenicity of Phytophthora palmivora on cocoa.


Study Area Surveys of the black pod disease were conducted in four different cocoa-growing communities (5km apart) in Ini Local Government Area of Akwa Ibom State in the humid tropics of south-eastern Nigeria. The communities surveyed were: Ikpe Ikot Nkon, Ekoi Ikpe, Itu Mbonuso, and Ibam Edet (Long. 07° 47'E, Lat. 05° 20'N., Alt. 110m above sea level) The studies were carried out at the peak of the rainy season (July-September) in two consecutive years, 2013 and 2014. Mean annual rainfall in the area was 1970mm, mean maximum and minimum temperatures were 30°C and 21°C respectively, during the period of the investigation. Data Collection and Laboratory Study

Determining disease incidence and severity Percentage disease incidence on infested cocoa pods was determined as follows: ��.��

!��"#��.�� "$�#�� X 100

Disease severity index was assessed on a five point scale (Wokocha, 1998), where:

1. = 1-20% of pods infested 2. = 21-39% of pods infested 3. = 40 -50% of pods infested 4. = 51 – 69% of pods infested 5. = > 70% of pods infested

Isolation of Phytophthora palmivora Infested cocoa pods collected from the field were taken to the laboratory and washed for 2 minutes in running water to remove soil and other debris. The pods were emptied of seeds and the husks cut into 5mm segments including the advancing margins of infection. Segments were surface disinfected in 0.1% commercial bleach (Sodium hypochlorite) for 5 minutes and rinsed in three changes of distilled water. The segments were dried between sheets of sterile filter paper and plated on fresh potato dextrose agar (PDA) in 9.00cm Petri dishes. The dishes were incubated at 280C for five days. P. palmivora was identified from pure cultures according to Barnett and Hunter (1972) method.

Pathogenicity of P. palmivora on pods of two varieties of cocoa. The pathogenicity of P. palmivora on the two cocoa varieties was evaluated in laboratory experiments. A total of 5 physiologically mature pods of each cocoa variety were used. The pods were washed with clean water and surface disinfected with 0.1% commercial bleach


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(Sodium hypochlorite). A single hole was made on each pod, using a sterile 5mm cork borer. A pure culture (5mm) of the pathogen was artificially inoculated into each hole and the inoculation site sealed with petroleum jelly. Each inoculated pod was enclosed in a humid chamber (a moist transparent polyethylene bag, 30 x 60cm in size supported by iron clamps and containing damp cotton wool). The pods were incubated for 11days at room temperature (25°-28°C). Five non-inoculated pods of each variety were similarly set up, as controls. Infection rate of P. pamivora on each pod of each variety of cocoa was measured daily throughout the duration of the experiment, using a transparent 30cm ruler.

RESULTS AND DISCUSSION Results of disease survey (Table 1) showed that in both Amazon and D-38 cocoa varieties, the incidence and severity of the black pod disease under natural infection were highest (48.3% and 3.2) in the Amazon variety in Itu Mbonuso community, and lowest (10.6% and 1.0) in the D-38 variety in Ibam Edet community. It was also found that the disease incidence and severity under artificial inoculation were significantly higher (45.9%-48.4% and 2.6-3.2) respectively on the Amazon variety than on the D-38 variety (35.6%-37.3%, 1.6-2.0) respectively. Pathogenicity tests (Fig. 1) showed that the rates of infection of the two varieties of cocoa by P. palmivora were similar in the first six days after inoculation. Thereafter, the rate of pathogen invasion of the Amazon variety increased remarkably, reaching its peak (1.2mm/day) nine days after inoculation. This was significantly (P= 0.05) higher than the invasion rate (0.4mm/day) of the D-38 variety, on the same day after inoculation. These observations indicate that the Amazon variety of cocoa was significantly more susceptible to attack by P. palmivora than the D-38 variety. These observations are supported by the findings of Lass and Wood (1985) and Raemaecker (2001). Wokocha and Onwuka (2003) also observed that naturally infected cocoa pods of the Amazon variety, had a lower mean weight (0.28kg/pod) than similar diseased pods of the D-38 variety (0.36kg). This lower weight was probably an indication that the black pod disease was more damaging to the pods of the Amazon variety than to those of the D-38 variety. Table 1: Incidence and Severity of the Black pod disease incited by P. palmivora on two Naturally infected varieties of cocoa, in Ini Local Government Area of Akwa Ibom State

Cocoa varieties Locations Amazon D-38 Incidence Severity Incidence Severity Itu Mbonuso 48.37 3.22 37.30 1.24 Ekoi Ikpe 34.00 2.58 18.60 2.00 Ikpe Ikot Nkon 45.90 1.06 35.60 1.60 Ibam Edet 12.00 2.61 10.60 1.02


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Fig. 1: Pathogenicity of P. palmivora on two cocoa varieties: Amazon and D38, 11 days after

inoculation in a humid chamber at 27°C vertical bars respresent LSD0.05

Despite its greater susceptibility to the black pod disease, the Amazon variety of cocoa is still widely cultivated by farmers in Ini Local Government Area. This may be due to its greater economic value as indicated in such features as its larger pods and more seeds per pod.

CONCLUSION

The study has shown that disease incidence and severity (48.3% and 3.2) respectively were highest in the Amazon variety of cocoa in Itu Mbonuso community and lowest (10.6% and 1.0) respectively in the D-38 variety in Ibam Edet community. The infection rate of the pathogen was found to be significantly higher on the Amazon variety than on the D-38 variety.

REFERENCES

Barnett, H. L and Hunter, B. B. (1972). Illustrated genera of imperfect fungi (4th Edition). Macmillam Publishing Company, New York. pp. 92-93.

De Latter-Gasquet, M. Despreaux, D. and Barel, M. (1998). Prospective study of the Cocoa Commodity Channel. Plantations Research Development 5(6): 683-691.

FAO (Food and Agricultural Organization). (1981). FAO Production yearbook, 35: FAO, Rome. 360pp.

Filani, G. A. (1973). The Chemical control of Phytophthora pod rot in Nigeria: An evaluation of the present situation. Cah. Orstom Ser. Bio. 20:91-94.

Lass, R. A. and Wood, G. A. (1985). Cocoa Production. World Bank Technical Paper No. 39:44-47.

Neil, G. (2002). How does Phytophthora infect cocoa? GRO Cocoa (IRAD Publication) No. 2:6.


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Raemaekers, R. H. (2001). Crop Production in tropical Africa. External trade and

international cooperation Brussels, Belguium Goekiut Graphics Inc. and C. I. P. Royal Library Pp. 909-910.

Wokocha, R. C. (1998). Effect of crop residue on the damping-off disease of tomato seedlings induced by Sderotium rolfsii in the Nigerian savanna. Nigerian Journal of Plant Protection 17:18-24.

Wokocha, R. C. and Onwuka, J. E. (2003). Wet season field survey of the black pod disease and mistletoe infection of cocoa in Amuro-Ibere- Unpublished.


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ECOLOGY AND ETHNOBOTANY OF Okoubaka aubrevillei PELLEGR. & NORMAN: VIEWPOINT OF CONSERVATORS AND USER GROUPS I N

EDO STATE, NIGERIA

E. E. John-Onyijen and E. M. Isikhuemen* Department of Forest Resources and Wildlife Management, Faculty of Agriculture,

University of Benin, Benin City, NIGERIA. *Corresponding Author: [email protected] Tel: +2348033885159

ABSTRACT Okoubaka aubrevillei Pellegr. & Norman is a hemi-parasitic mono-generic tropical forest tree endemic to the Guinean West African rainforest. The ecology and ethno-medicinal uses of O. aubrevillei were evaluated in the rainforest region of Edo State, Nigeria. The snowball sampling technique was used in combination with questionnaire and key informants’ interview to elicit information from forestry field staff in Edo State Ministry of Environment and Public Utilities, Benin City, Nigeria (who constituted the primary participants). Equipped with the recommendations of the primary participants, we contacted the secondary participants (herbalists/users in 14 communities in five Local Government Areas and vendors in five markets). Results revealed that O. aubrevillei is believed to possess magical powers while its parts were used for the prevention and treatment of diverse ailments, including evil spirit related disorders. Tree bark is most frequently used (78.4%); users obtain them mostly from market vendors (47.9%), and directly from the wild (41.3%). Respondents posit that O. aubrevillei is progressively exterminated through harvest pressure (43%) and habitat loss (48.1%). Regardless of its fast declining population, respondents gave a lucid no-cause-for-alarm verdict on the current status of O. aubrevillei in the wild; contending that its mystical power would sufficiently guarantee its continued existence. To unravel the idiosyncrasies and generate critical mass of robust ecological information on O. aubrevillei, it is imperative to encourage and embark on interdependent investigations that underscore empirical research and indigenous knowledge.

Keywords: Okoubaka aubrevillei, ethno-medicine, hemi-parasite, indicator species, indigenous knowledge.

INTRODUCTION

Okoubaka aubrevillei Pellegr.and Norman is the only hemi-parasitic tree found in the rainforest region of Nigeria. Its name is derived from the word: ‘Oku baka’, an Ayin Language in Cote d’ Ivoire, meaning ‘death tree’ (Lowe, 2012). It is a non-pioneer tropical tree usually found in closed cover of evergreen forest (Burkill, 1985), rocky hills (Dovi, 2013) or slopes, and mostly alone in areas where it is found (Borokini, 2015). O. aubrevillei is an important medicinal plant which has remained invaluable in the repository of herbalists and ethno-medicine dependent businesses and users. WHO (2001) defines medicinal plant as herbal preparations produced by subjecting plant materials to extraction, fractionation, purification, concentration or other physical or biological processes which may be produced for immediate consumption or as a basis for herbal products. On the other hand, Ethnobotany is concerned with the relationship between people and plants (Jones, 1941), including attitude of people towards them like naming, classification, uses, management and the values placed on them (Hamilton et al., 2003).

O. aubrevilllei currently faces serious anthropogenic threats in places where it is endemic in Nigeria (Borokini, 2015; Isikhuemen, 2012). This is as a result of the high demand for its parts, particularly ‘tree bark’ by local people for diverse uses, e.g. treatment of various ailments (Isikhuemen and Iduozee, 2008), spiritual protection (Maundu et al., 2006; Myren, 2011), construction and fuelwood (Ladipo et al., 2008), and sacred and

John-Onyijen, E. E. and Isikhuemen, E. M. (2017). Ecology and Ethnobotany of Okoubaka aubrevillei Pellegr. & Norman: Viewpoint of Conservators and User Groups in Edo State, Nigeria. Journal of Environment and Sustainable Development, 3(1): 13-24.


Page | 14

magical purposes (Marshall and Hawthorne, 2012). Despite the enormous value placed on the tree by local people in Nigeria, O. aubrevillei was only captured as ‘threatened species’ on the Red list data base of the International Union for the Conservation of Nature and Natural Resources (IUCN) in 2015 (Borokini, et al. 2015). According to Osemeobo (2005, 2007) “there were less than 20 growing stands of O. aubrevillei in Nigeria”; however, Ihenyen et al., (2009, 2010, 2011) “hypothesized that a tree was found in every 0.08km2.”

The Nigerian rainforest is located mainly in the South between Latitude 4o and 9o N (Ola-Adams and Iyamabo, 1977). It is acutely ravaged by anthropogenic stressors such as loss of habitat occasioned by land degradation and pollution associated with oil and gas exploration, agricultural intensification, including slash and burn agricultural practices, intensive and uncontrolled logging, development of infrastructure and urbanization, etc. (Isikhuemen, 2014). These stressors have negatively influenced the lifestyle of the rural and forest dependent poor – to the extent that they frequently contend with diminishing levels of small forest item incomes as well as fluctuating values of products and poor harvest returns (Isikhuemen, 2012). The trend in the decline of the rainforest ecosystem is not abating – it will ultimately lead to the despoliation of fragile ecosystems and disappearance of some mono-generic tree species most of which are largely unknown and yet to be characterized (Isikhuemen, 2014).

Despite the rich potentials of O. aubrevillei toward boosting the nation’s foreign exchange earnings, it is being indiscriminately exploited for timber, as non timber forest product (NTFP) and for use as supplement in both orthodox- and ethno-medicines. According to Szaro (1992), the best times to restore a species or an ecosystem is when it is still available or present. Most published works on Oukubaka aubrevillei, also called “African Juju tree” have emanated largely from reviews which have been used for generalizations. This paper evaluates the ecology and ethno-medicinal uses of O. aubrevillei based on the perspectives of diverse stakeholders – government (forestry) personnel, herbalists and users in five Local Government Areas(LGAs) and vendors in selected markets (in one LGA) in the rainforest region of Edo State, Nigeria.


Study Area: The study was carried out in the rainforest region of Edo State (Lat. 05o 44'N & 7o 34'N and Long. 05o 4'E & 06o 45'E) (United Nations Development Programme, 2005). Edo State has a total land area of 19,707km2 and human population of 3,233,366. With the rainforest vegetation in the South, derived and guinea savanna in central and north parts, the state is conveniently sub-divided into three senatorial districts. The climate is characterized by wet and dry seasons. Rainfall is bimodal with average mean annual rainfall of 2289 mm; mean relative humidity: 84%, rarely falling below 80%; while the mean maximum and minimum temperatures are 33oC and 23oC respectively (Isikhuemen and Bamawo, 2013). Data Collection and Analysis: Data were collected in five purposively selected Local Government Areas (LGAs) – Orhionmwon, Ovia North East, Ovia South West, Uhunmwode and Oredo – out of the seven LGAs which constitute the rainforest region of Edo State (Figure 1). The snowball sampling technique (Denzin and Lincoln, 2005) was used in conjunction with two sets of semi-structured questionnaire and key informants’ interview. Responses were elicited from the primary participants (forestry field staff in Edo State Ministry of Environment and Public Utilities). Based on the recommendations of the primary participants, we reached out to selected traditional medicine practitioners/users in the four LGAs, and vendors in the selected markets in the fifth LGA.


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Figure 1: Map of Edo State showing the rainforest region and study area One hundred and ninety nine (199) copies of the questionnaire were administered to participants across the different occupational domains – government, communities and markets. However, of the 135 copies were retrieved, 95 were completed and returned by users/forestry personnel and 40 from traditional medical practitioners/market vendors ((Table 1). The decision on which instrument – questionnaire or interview – to use in eliciting responses from participants was largely based on participants’ willingness to genuinely respond and provide unbiased answers to questions on the subject matter. Data were analysed using simple descriptive statistics. The harmonic mean was used to relativize data on threats and ecological characteristics. Table 1: Questionnaire and key informants tools used

Participant Dept/LGA/Mkt Respondent Tool*

Issued Retrieved

Govt. staff Forestry Dept Field station 1,2 50 21 Herbalist/User Orhionmwon Ologbo-nugu 1,2 10 6 Ugo 1,2 10 9 Uguomokhua 1,2 10 6 Herbalist/User Ovia N/East Odighi 1,2 5 2 Herbalist/User Ovia S/West Iguobazuwa 1 7 5 Iguoriakhi 1 8 6 Ikoka 1 5 5 Udo 1,2 10 6 Herbalist/User Uhunmwode Egba 1 6 3 Ehor 1,2 10 8 Igbogiri 1 5 2 Igomoson 1,2 10 9 Ugbiyaya 1 3 1 Umuokpe 1,2 10 5 Vendors in Mkts

Oredo(Market) Edaiken 1 4 4

Ekiosa 1 5 5


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New Benin market

1 7 7

Oba market 1 5 5 Oliha Market 1 4 4 Herbalist/User OviaN/East Odighi 1,2 4 1 Herbalist/User Uhunmwode Umuokpe 1,2 2 2 Ugomoson 1,2 1 1 Total 199 135

Source: Field study (2016) Tool*: Mkt. = Market; 1 = Questionnaire, 2 = Key informants’ interview

RESULTS

Ethno-medicinal uses of O. aubrevillei The results on ethno-medicinal uses of O. aubrevillei revealed that respondents in communities and selected markets were unanimous in their presentations that the species was an important and highly revered mystical tree which users approached (with nudity, a batten and different items of appeasement) for protection against evil forces and for curing diverse ailments, especially the ones that are somewhat supernatural and defy orthodox treatments. The largest response from market participants was obtained at the New Benin market; while respondents from Ologbo-Nugu recorded highest among communities (Table 2).

Table 2: Uses of O aubrevillei Uses

Eda

ikn

Eki

osa

New

beni

n

Oba

Olih

a

Olo

gbo

N-U

gu

Ugo

Odi

ghi

Ikok

a

Udo

Ugo

mos

on

Um

okpe

Tot

al

Per

cent

(%

)

Mea

n

Treatment of ailment

4 2 6 2 2 5 4 1 1 1 1 2 31 50.8 2.58

Mystical power

2 4 5 4 4 4 3 1 - - 1 2 30 49.2 2.50

Total 6 6 11 6 6 9 7 2 1 1 2 4 61 100 5.08

Source: Field Survey (2016). With regards to the type of ailments that O. aubrevillei prevents/cures, respondents listed seven; with evil spirit related infirmity scoring highest while insanity was least (Figure 2).


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Figure 2: O. aubrevillei and the ailments it prevents and/or cures

The respondents’ opinions on the most frequently used parts of O. aubrevillei for the treatment of ailments across stakeholder domain were varied. However, participants were unanimous that the ‘bark’ was the most sought after and frequently used; affirming that it could be prepared exclusively or in combination with other plant parts into concoctions or infusions before application or use (Figure 3). The number of respondents who claimed that the ‘bark’ was most frequently used was highest in New Benin Market. However, respondents from two communities – Ugo, Ologbo-N-ugu and Ugomoson – contended that the bark, leaf and seed were all utilized, although for different purposes (Figure 3).

Figure 3: Most preferred parts of O. aubrevillei for use in ethnomedicine

28.7

18.5

8.3

18.5

2.8

7.4

15.8

0

5

10

15

20

25

30

35

Evil spiritrelated

illnesses

Arthritis Malariafever

Convulsion Insanity Stroke Asthma

Par

ticip

ants

0

1

2

3

4

5

6

7

8

No.

of r

espo

nden

t

Market vendors/Communities

Bark Leaf Seed


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The recipe for compounding or preparing different herbal products and supplements by herbalists/traditional doctors and end users (e.g. infusion, decoction, etc.) is presented in Table 3. The largest number of participants who voluntarily and freely provided information on the different ways of making infusion, decoction, etc. was recorded in New Benin market (Table 3).

Table 3: Extraction, preparation and application of O. aubrevillei

Market Pound bark for bathing

(Infusion)

Bathe with

bark & leaves

(Infusion)

Mix bark with native soap & A. melegueta (infusion)

Char plant roots and rub onto patient’s

body (decoction)

Bathe with ground bark mixed with

other plant parts (infusion)

Immerse leaves in water & bathe or

rub (infusion)

Total

Edaiken - - 4 - - - 4

Ekiosa - 1 -- - - - 1

New Benin 5 - - 1 - - 6

Oba 1 - - - - - 1

Ologbo-N-ugu 1 - 1 - - 2 4

Ugo - - 1 - 2 1 4

Odighi - - - 1 - - 1

Ikoka - - - 1 - - 1

Udo - - - 1 - - 1

Ogomoson - - 1 - - - 1

Umukpe - - 2 - - - 2

Total 7 1 9 4 2 3 26

Percent (%) 26.92 3.85 34.62 15.38 7.69 11.54 100

Source: Field Survey (2016)

Conservation policy and current status of O. aubrevillei in the wild Participants did not betray any competency on the lopsidedness of extant policy and laws on conservation of endangered under-utilized flora, particularly O. aubrevillei. The general views of participants presented on a 4 Likert scale response options indicate that the population of O. aubrevillei in the wild was not only declining at an alarming rate, but increasingly becoming very scarce. A significant number of respondents (ca. 36%) comprising forestry field staff and participants from Ologbo-nugu community posited that O. aubrevillei was no longer common in the wild; contending that existing forest policy/law in Edo State had become a disincentive to, and clog on, community involvement in the protection of O. aubrevillei and other underutilized species in protected and off reserve (free) areas (Table 4).


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Table 4: Present status of O. aubrevillei in the wild Dept./L.G.A Respondent Common Rare Very scarce Lost Total Forestry Department Field staff - 13 8 - 21 Orhionmwon Ologbo-nugu 1 - 5 7 13 Ugo - 2 - - 2 Igomukhua - - 6 - 6 Ovia North East Odighi - 1 1 - 2 Ovia south west Iguobazuwa - 5 - - 5 Iguoriakhi - - 6 - 6 Ikoka - 1 4 - 5 Udo - 4 2 - 6 Uhunmwode Egba - 3 - - 3 Ehor - - 8 - 8 Igbogiri - 3 - - 4 Ugbiyaya - - 1 - 1 Ugomoson - 8 1 - 9 Umokpe - - 5 - 5 Total 1 40 47 7 95 Percent (%) 1.0 42.1 49.5 7.4 100.0

Source: Field study (2016)

Majority of the respondents (77%) were unanimous in their submission that the bark of O. aubrevillei was the most frequently harvested and commonly sold by vendors in herbal markets. The forestry personnel (government staff) constituted the largest number of respondents who acknowledged that over-harvesting (scarring) of tree bark often predisposes O. aubrevillei to physiological breakdown and ultimately, death (Figure 4).

Figure 4: Tree part that often predisposes O. aubrevillei to breakdown/death.

However, participants (76%) were of the view that extensive scarring of the tree bark beyond the species’ elastic limits of resilience could instigate hormonal disorder and loss of vital organs which might lead stunted growth or outright death. Figure 5 (A & B) are composite photographs of O. aubrevillei taken in February, 2016. However, during a repeat visit in August, much of the bark had been removed while the tree lost all its leaves.

0

5

10

15

20

No

. o

f re

spo

nd

en

ts

Forestry personnel/Community

Leaf Fruit/Seed Bark


Page | 20

Photo by: E. E. John-Onyijen (2016)

Figure 5: (A) Heavily scarred trunk of O. aubrevillei; (B) Healthy O. aubrevillei Anthropogenic threats and ecological idiosyncrasies of O. aubrevillei The synchronized result of threat factors and the species ecological peculiarities (including its hemi-parasitic influence on consociated species) in its range are presented in Table 5. Most respondents affirmed that O. aubrevillei kills most vascular plants growing close to, or near it. However, in response to a question ‘on why most trees and other vascular plants do not thrive or survive near O. aubrevillei in the wild, participants were rather imprecise; arguing that the tree possesses unrestricted magical power which it invokes in addition to spewing vaporous substances to kill plants, animals and even humans. Participants listed four species which grow close to or near O. aubrevillei (Table 5). Table 5: Threats and ecological characteristics of O. aubrevillei Variable Forestry staff &

users (n=95) Herbalist &

vendors (n=40) Harmonic mean

Threat/Hemi-parasitic feature

98.9 77.5 92.6

Harvest/Habitat pressure 47.9 68.4 43.0 Magically kills trees 58.5 52.6 48.1 Poor regeneration 10.6 36.8 12.6 Forage by frugivores 2.1 0.0 1.5 Irregular seed year 0.0 5.3 0.7 Associated Species 75.8 35.0 63.7 Myrianthus arboreus 90.2 57.1 84.7 Musanga cercropoides 9.7 7.1 9.3 Celtis spp. 0.0 28.6 4.6 Milicia excels 0.0 7.1 1.2

Source: Field Study (2016)

Majority of respondents affirmed that the commonest rainforest tree which grows luxuriantly and often forming consociation around O. aubrevillei was Myrianthus aboreus.

A B


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Figure 6 shows a large population of advanced growth of Myrianthus aboreus under a mature O. aubrevillei tree in Sapoba Forest Reserve, Nigeria.

Photo by E. M. Isikhuemen (2016)

Figure 6: Large population of natural regeneration of Myrianthus arboreus growing under a mature tree of O. aubrevellei.

DISCUSSION Okoubaka aubrevillei is the only known hemi-parasitic rainforest tree in West – Central Africa. According to Hawthorne (1995), O. aubrevillei is possibly the largest species in the in the Santalaceae which attains a height of up to 40m in the West African rainforest. Although it is reputed to kill most vascular plants growing close to it (e.g. Keay, 1989), it is this bizarre characteristic that makes it highly attractive in ethnomedicine, especially for use in the treatment of strange ailments that have defied orthodox medicine. The outcome of this study is in accord with the works of several authors (e.g. Borokini, 2015; Marshall and Hawthorne, 2012; Isikhuemen, 2012; Isikhuemen and Iduozee, 2008; EMEA, 2000) who have alluded to the fact that O. aubrevillei is iconic; highly revered, and widely used for the treatment of diverse ailments, notably, malaria fever, rheumatism, convulsion, asthma, etc. in most cultures. Ita and Effiong (2013) compiled 6 poly-herbal mixtures involving O. aubrevillei barks for treating malaria fever. It is also worshipped by some local people and communities in West Africa – owing to the mythical powers credited to it.

The result on the uses of O. aubrevillei for the treatment of of diverse ailments, including evil related illnesses (see Figure 2) is in agreement with the findings of several authors. For example, Myren (2011) and Maundu et al. (2006) reported that O. aubrevellei has high efficacy for spiritual protection and for resuscitating failing health conditions attributed to the evil spirits; (2) Oseomobo (2007) averred that the bark of O. aubrevillei is used for the treatment of insanity; and (3) van Andel et al. (2012) posited that the decoction of tree bark and seed is used for treatment of convulsion. Borokini (2015) reported that the bark and seed of O. aubrevillei are in high demand for ethno-medicinal application in Nigeria and most West/Central countries where the tree is endemic. The geographical and ecological requirements of O. aubrevillei in Edo State, Nigeria conform to same or similar conditions in Ghana and some other West African countries (Burkill, 1985; Veenendaal et al. 1996). The greatest challenges faced by O. aubrevillei in all its range in Nigeria include: habitat loss as well as unregulated and unsustainable harvest, particularly the tree bark which


Page | 22

result is debilitating scars – with attendant cessation of normal physiological functions and ultimately, death. The participants’ views on harvest pressure and declining population and/or rarity of the species in all its range in Nigeria is in agreement with Isikhuemen (2012) as well as Isikhuemen and Iduozee (2008) who asserted that the palpable disappearance of O. aubrevellei in the wild is largely due to harvest pressure as well as fragmentation and loss of habitats.

Hardie (1963) had underscored the mythical powers that some cultures and rural communities ascribe to O. aubrevillei. According to Hardie, the Edo tradition in Nigeria forbids the use of machetes to obtain the tree bark; preferring the use of wooden batten instead. There was a consensus among respondents across communities and occupational group that O. aubrevellei is always accorded noble treatment in the event that one desires to take or harvest any of its part. The general view was that “anyone (typically male) who desires to harvest the bark of O. aubrevillei would first of all strip himself naked and keep his clothes some distance away. He then runs and embraces the tree armed with habitual items (e.g. cowries, white chalk, kola nuts, piece of white cloth, etc,) for appeasement before any attempt is made to obtain the bark of the tree. Respondents contended that appeasement and incantations were made simultaneously while the appeaser remained in nude condition; he then smacks the tree trunk with the wooden batten, takes a strip off the bark and quickly runs back to wear his clothes. The theory is that in the event that the tree (O. aubrevillei) felt the pain or injury inflicted and it went in pursuit of the appeaser/visitor, it would hardly recognize him having worn his clothes.

The results of the hemi-parasitic temperament and idiosyncrasy of O. aubrevillei, particularly its impact on most trees that grow around it (with the exception of few specialized taxa) forming consociations (see Figure 6), are in agreement with the results of Isikhuemen and Iduozee (2008); Isikhuemen (2014, 2012); Hardie (1963). In a study conducted at a rainforest site in Nigeria, Hardie (1963) reported that “no tree was found 80feet (ca. 24m) of Okoubaka tree, except for Myrianthus arboreus, Musanga cecropoides and woody Vernonia.

CONCLUSION

Okoubaka aubrevillei is the only tropical forest hemi-parasitic tree which is highly regarded and worshipped as a totem in some parts of Southern Nigeria. Its use in ethno-medicine for fetish reasons and for the treatment of diverse ailments is awesome. The bark, seed and leaves are the most frequently used parts. Despite its current ethnomedicinal values and the potentials for future use in orthodox medicine, the species is seriously threatened in all its range by uncontrolled exploitation, harvest pressure and local extinction. O. aubrevillei is increasingly assuming greater relevance in the health care delivery system both at the local, national and regional levels. It is therefore recommended that concerted efforts be put in place to develop policies and legislation to support the conservation of the relic stands while encouraging rural communities and government agencies to support its rehabilitation in areas where the population is at or below its critical threshold of naturally regenerating itself.


Page | 23

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knowledge for research and conservation in west and central Africa. Journal of Biology and Life Science, 6: 67-77.

Borokini, T.I., Rivers, M.C. and Wheeler, L. (2015). Okoubaka aubrevillei. The IUCN Red List of Threatened Species 2015: e.T71022951A71022977. http://dx.doi.org/10.2305/IUCN.UK.2015-4.RLTS.T71022951A71022977.en. Assessed: 15/01/2017.

Burkill, H. M. (1985). The Useful Plants of West Tropical Africa, Vol. 1, Families A-D, Royal Botanical Gardens, Kew. 960 pp.

Denzin, N. and Lincoln, Y. (2005). The Sage handbook of qualitative research. Sage, Thousand Oaks, California, USA.

Dovi, E. (2013). Comparative Studies on the In-Vitro Antioxidant and Antimicrobial Properties of Methanolic and Hydro-Ethanolic Plant Extracts from Five Medicinal Plant Parts of Ghana. M. Phil Thesis, Kwame Nkrumah University of Science and Technology, Ghana 112pp.

European Agency for the Evaluation of Medicinal Products (EMEA) (2000). Okoubaka aubrevillei. Summary Report.The European Agency for the Evaluation of Medicinal Products. Veterinary Medicine Unit, United Kingdom. EMEA/MRL/673/99-FINAL. http://www.ema.europa.eu/docs/en_GB/document_Library/Maximum_Residue_Limits_Report/2009/11/Wc500015212.pdf

Hamilton, A. C., Pei, S., Kessy, J., Khan, A. A., Lagos-Witte, S., and Shinwari, Z. K. (2003). The purposes and Teaching of Applied Ethnobotany. People and Plants Working Paper. WWF, Godalming, U.K. http://www.rbgkew.org.uk/peopleplants/wp/wp10/ index.html

Hardie, A. D. K. (1963). Okoubaka- A Rare Juju Tree. The Nig. Field, 27(2): 70 – 72.

Hawthorne, W. D. (1995). Ecological profile of Ghanaian forest trees. Tropical forest papers 29. OFI/ODA, Oxford.

Ihenyen, J., Okoegwale, E. E., and Mensah J. K. (2009). Composition of Tree Species in Ehor Forest Reserve, Edo State, Nigeria. Nat. Sci. 7(8): 8-18

Ihenyen, J., Okoegwale, E. E., and Mensah, J. K. (2010).Tree/Shrub Species Diversity of Ehor Forest Reserve in Uhunmwonde Local Government Area of Edo State, Nigeria. Researcher. 2(2), 37 - 49.

Ihenyen, J., Mensah J. K., W. O. Osunde, and E. Ogie-Odia (2011). Checklist of the Tree/Shrub Species of Edo State, Nigeria. J Apple Env Biol. Sci. 1(9), 276-282.

Isikhuemen, E. M. (2012). Resolving Institutional Impedement to Foster Conservation of Threatened and Under-Utilized Rainforest Flora in Southern Nigeria. UNU-INRA Seminar Series, UNU-INRA. United Nations University-Institute for National Resourses in Africa. Accra, Ghana.www.inra.unu.edu

Isikhuemen, E. M. (2014). Rainforest Degradation in southern Nigeria: Role of Forestry Institutions. UNU-INRA Working Paper 7. United Nations University-Institute for National Resources in Africa, UNU-INRA. Accra, Ghana. 41pp.

Isikhuemen, E. M. and Bamawo, P. O. (2013). Effect of forest understorey shade on vegetative growth and development of Thaumatococcus danielli (Benn.) Benth. Nigerian Journal of Forestry, 43 (1 & 2): 45 – 52.

Isikhuemen, E. M. and Iduozee, O. F. (2008). Degraded Forests in Protected Landscapes: Prospects for Biodiversity Rehabilitation in Urhonigbe Forest Reserve, Edo State, Nigeria. In: Parrotta, J.A., A. Oteng-Yeboah, and J. Cobbinah (eds.). Traditional Forest-Related Knowledge and Sustainable Forest Management in Africa. IUFRO World Series, Volume 23.


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Ita, P. B. and Effiong, E. E. (2013). Medicinal Plants Used in Traditional Medicine by Rural Communities in Cross River State, Nigeria. J. Health, Med. Nurs. 1, 23-29.

Jones, V. (1941).The nature and scope of ethnobotany. Chronica Botanica, 6, 219-221. Ladipo, D. O., Adebisi, A. A., and Bosch, C. H. (2008). Okoubaka aubrevillei Pellegr. &

Normand. In: Schmelzer, G.H. and A. Gurib-Fakim (Eds.). Prota 11(1): Medicinal plants 1. [CD-Rom]. PROTA, Wageningen, Netherlands.

Keay, RW. J. (1989). Trees of Nigeria. Clarendon Press Oxford. 476p.

Lowe, J. (2012). Comment on the Research Note Igi-nla (Big tree). Nig. Field, 77, 127-128.

Marshall, C. A. and Hawthorne, W. D. (2012). Important Plants of Northern Nimba County, Liberia: A Guide to Most Useful, Rare or Ecologically Important Species, with Mano Names and Uses. Oxford Forestry Institute, Oxford, England. 460 pp.

Maundu, P., Kariuki, P., and Eyog-Matig, O. (2006). Threats to Medicinal Plant Species – an African Perspective. In: Miththapala, S. (ed.) Conserving Medicinal Species: Securing a Healthy Future. IUCN: Ecosystems and Livelihoods Group, Asia. 184 pp.

Myren, B. (2011). Magic Plants in the South of Ghana. Report of Research Internship. Biology Leiden University, Belgium. 52pp.

Ola-Adams, B. A. and Iyamabo, D. E. (1977). Conservation of Natural Vegetation in Nigeria. Environmental Conservation 4(3) 217 – 226.

Osemeobo, G. J. (2005). Living on the Forests: Women and Household Security in Nigeria. Small-scale For. Econ., Mgt. Policy, 4(3), 343-358.

Osemeobo, G. J. (2007). Who decides on access to genetic resources? Towards Implementation of the Convention on Biological Diversity in Nigeria. Small-scale For. 6. 93 -109.

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United Nations Development Programme (UNDP) (2005). Edo State Economic Empowerment and Development strategy Report, June, 2005. 7p.

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World Health Organization (2001). Legal Status of Traditional Medicine and Complementary/Alternative medicine: A world-wide review. WHO Publishing 1.


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POPULATION GROWTH AND DAMAGE CAUSED BY MAIZE WEEVIL

(Sitophilus zeamais MOTS.) TO STORED MAIZE GRAINS.

Ime O. Udo Department of Crop Science, Faculty of Agriculture, University of Uyo,

P.M.B. 1017, Uyo, Nigeria Phone: +234-8023-292513 Email: [email protected]

ABSTRACT

An experiment was mounted in the Crop Protection Laboratory, University of Uyo in order to assess the level of population growth of the maize weevil, Sitophilus zeamais and damage caused to stored maize grains. The treatment consisted one, two, three and four pairs of adults S. zeamais of 3 – 5 days old. The insects were introduced into 100 g of grains in plastic cups and covered white muslin cloth with the aid of rubber bands. Each treatment was left to stand for two months, and thereafter, the numbers of off-spring produced were counted and damage assessed by calculating the percent weight loss. Data generated were subjected to analysis of variance. The results showed that there was significant difference of off-spring from the one pair treatment (149) recording the highest while the least was number of off-spring was recorded from the treatment with four pairs of insect (103). The difference between the weight losses in the maize grains was also significant (P<0.05) There was a significant weight loss observed in the treatment with four pairs of insects (18.2 g) as against the treatment with one pair of insects (13.0 g). Periodic inspection of grains in storage should be carried out by farmers to prevent increasing build up of pest population which would lead to economic loss and threatens food security.

Keywords: Population growth, damage, maize weevil, food security, produce inspection

INTRODUCTION Maize, a member of the family Poaceae, is an important cereal used as food by both man and animal in saharan and sub-saharan Africa. It also has industrial purposes such as making of adhesives, paints and explosives (IITA, 2003). Post harvest losses to storage insect pests have been recognized as an increasingly important problem in Africa (Epidi et al., 2009). However, maize in storage is prone to attack by diverse insect pests, which cause considerable damage and threatens food security. One notable pest of stored maize is Sitophilus zeamais (Motsch.) which is known to cause up to 30 – 100 % loss of stored maize where infestation is heavy (Udo, 2011). S. zeamais infests maize in the field before harvest and continues in storage, thus damaging maize and can have extreme economic impact for a producer after harvest and during storage. Information on the population growth relative to damage caused to stored maize by S. zeamais is scanty and sometimes not recorded. This study therefore was carried out to evaluate the population growth of S. zeamais and the damage caused by the insect to maize in storage. It is hoped that results obtained would enhance effective maize grain storage particularly amongst rural poor resource farmers.


Culturing of Insects Adult S. zeamais were obtained from infested stock of maize at Uyo main market, Akwa Ibom State, Nigeria. The insects were reared on whole maize and were transferred to a glass jar containing 300g of grains previously sterilized in a freezer for 14 days. After one week

Udo, I. O. (2017). Population Growth and Damage Caused by Maize Weevil (Sitophilus zeamais Mots.) to Stored Maize Grains. Journal of Environment and Sustainable Development, 3(1): 25-27.


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of oviposition, all insects were removed and discarded by freezing to enable the emergence of same age progeny that were used to establish the main culture. Progeny Production One pair, two pairs, three pairs and four pairs of 3 – 5 days old sexed S. zeamais were introduced into 100 g of maize grains in plastic cups to assessed for the emergence of the first filial generation (off-spring). Maize grains which had been kept in the freezer to prevent hidden infestation were used for the experiment. The cups were covered with white muslin cloth and left to stand undisturbed for two months, while the number of insects emerging from each treatment was counted for one week. Damage assessment At the end of the two months storage period, samples of 100 grains were taken from each cup and number of damaged grains (grains with characteristic holes) and undamaged grains were counted and weighed. Percent damage was computed using the method of FAO (1985). Data Collection and Analysis Data on off-spring production and damage caused were subjected to analysis of variance (ANOVA) and means were separated using least significance difference (LSD) at 5% probability level.

RESULTS AND DISCUSSION The progeny (off-spring) production from the different treatments of S. zeamais is summarized in (Table 1). The results showed that there was significant difference of off-spring from the one pair treatment (149) recording the highest while the least was number of off-spring was recorded from the treatment with four pairs of insect (103). This could be as result of competition amongst the females in egg laying. Furthermore, there could be the secretion of egg laying pheromone that deters other females from ovipositing in an already attacked grain. There could also arise from the problem of too many developing stages within grains competing for available resources which if depleted would not favour full development of the progenies (Hodges et al., 1983, Tyler and Boxall, 1984).

The difference between the weight losses in the maize grains was also significant (P<0.05) There was a significant weight loss observed in the treatment with four pairs of insects (18.2 g) as against the treatment with one pair of insects (13.0 g) (Table 1). This observation was expected, because the higher the number of insects, the greater the degree of damage done to grains. It therefore becomes imperative that the number of insect pests infesting or attacking stored product should be reduced to the barest minimum.

In conclusion, this study has revealed the exponential increase in population growth from fewer numbers of insects than when they are more in numbers, and also that weight loss is directly proportional to the number of insect pests. The higher the number of insects attacking stored maize, the higher the degree of damage sustained. Farmers should always monitor insect pest presence in stored products periodically by using indices like frass production, heat accumulation, exuviae and increased relative humidity, in order to remediate insect pest attack at an earlier stage so as to strengthen food security.


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Table 1: Progeny development of Sitophilus zeamais and percent weight loss caused to maize grains in storage. Treatment (Insect pair) Progeny development Percent weight loss

1 149 0.42 2 131 3.76 3 129 4.04 4 103 6.88

LSD (P<0.05) 18.0 1.64

REFERENCES

Epidi, T. T., Udo, I. O. and Osakwe, J. A. (2009). Susceptibility of Sitophilus zeamais Mots and Callosobruchus maculates F. to plant parts of Ricinidendron heudelotii. Journal of Plant Protection Research 49(4): 411 – 415.

FAO (1985). Prevention of Post- harvest food losses.Training Series No.10 (122). Food and Agriculture Organisation of the United Nations, Rome. 120pp.

Hodges, R. J., Dunstan, W.R. Magazini, I. and Golob, P. (1983). An outbreak of Prostephanus truncates (Horn.) (Coleoptera: Bostrichidae) in East Africa. Protection 5: 183 – 189

IITA (2003). Research Guide 30. IITA Training Programme. Ibadan, Nigeria

Tyler, P. S. and Boxall, R. A. (1984). Post-harvest loss reduction programmes: a decade of activities; what consequences? Tropical Stored Product Information. 50: 4 – 13

Udo, I. O. (2011). Potentials of Zanthoxylum xanthoxyloides (Lam) for the control of Stored Product Insect Pests. Journal of Stored Products and Postharvest Research 2(3): 40 – 44.


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IMPACT OF COASTAL EROSION ON ALPHA BEACH COMMUNITY IN

LAGOS, NIGERIA

Maureen. N. Chukwu Department of Pure and Applied Sciences, Faculty of Science

National Open University of Nigeria Plot 91, Cadastral Zone, Nnamdi Azikiwe Expressway, Jabi, Abuja

[email protected]

ABSTRACT Coastal erosion is a dominant seasonal climatic factor in Alpha beach community as a result of rise in sea level. The Impact of Coastal erosion on Alpha beach community in Lagos Nigeria was investigated. The research was motivated by the condition in Alpha beach area as affected by coastal erosion. A total of 60 people living in Alpha beach community in Lagos, Nigeria were interviewed using structured questionnaires. The instrument was validated through peer review and pilot testing. Data collected were summarized and computed using descriptive statistics and Likert scaling test. Results showed that ninety-two percent of the respondents affirmed that coastal erosion destroyed their infrastructure and properties, distorted their business and increased environmental pollution. It impacted negatively on their social lives leading to relocation of some members of the community and retarded community development. It also reduced the reliability of ocean shipping, impacted negatively on marine lives and activities, thus increasing economic risks. It is recommended that the government and other stakeholders should come to the aid of the community by providing them with affordable health services and armoring the shoreline with seawalls, revetments and jetties to remedy the adverse effects of the coastal erosion.

Key words: Environmental pollution, social lives, community development, marine lives, economic risks, stakeholders.

INTRODUCTION

Coastal erosion is the wearing off of land and the removal of beach or dune sediments by wave action, tidal currents, wave currents, high winds and drainage. Causes of coastal erosion include waves generated by storms, wind, or fast moving motor craft, hydraulic action, abrasion impact and corrosion. It may take the form of long-term losses of sediment and rocks, or merely a temporary redistribution of coastal sediments. Erosion and inundation are key impacts from rising sea levels and increased oceanic activity in coastal communities and waterways connected to the ocean. According to Douglas, (1995 ) reported that the global average sea level had risen by about 1.0 to 2.5 millimeters per year during the last century along the Atlantic and Gulf coasts. However, some parts of Maine and the Pacific Northwest have experienced relative sea level decline because of post-glacial rebound (Leatherman, 1993; Douglas, 1995). Houghton et al., 1996, reported that the Intergovernmental Panel on Climate Change projected a global rise in sea level of between 15 cm and 95 cm, with an estimate of roughly 50 cm by 2100, implying that rates of sea level rise will accelerate in future. Coastal erosion is influenced by both natural factors and human activities (Rijn, 2011). Natural factors contributing to coastal erosion include sand supply; changes in sea level, geologic characteristics; sand-sharing systems of beaches and dunes and the effects of waves, currents, tides, and wind. Human activities that can alter natural processes include dredging of tidal entrances, construction of jetties and groins, hardening of shorelines with seawalls, beach nourishment, and construction of harbors and sediment-trapping dams.

Climate change such as sea level rise, changes in the frequency and intensity of storms, increases in precipitation, and warmer ocean temperatures could affect coastal areas

Chukwu, M. N. (2017). Impact of Coastal Erosion on Alpha Beach Community in Lagos, Nigeria. Journal of Environment and Sustainable Development, 3(1): 28-34.


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in a variety of ways. Rising atmospheric concentrations of carbon IV oxide are causing the oceans to absorb more of the gas and become more acidic which could have significant impacts on coastal and marine ecosystems.

Coastal habitats such as wetlands, estuaries, dunes and beaches contain a wealth of biological diversity. Beaches are temporal features where sand is always being removed and added. Sandy beaches normally retreat landward in response to sea level rise. According to Leatherman et al., 1999, long term shoreline retreat on the Atlantic Coast averaged about 150 times that of sea level rise. It then follows that an additional rise of 10 cm in sea level could result in 15 meters of beach erosion. Alpha community is presently under threat probably because of global warming, dredging activities elsewhere, or the Eko Atlantic Project, which is a new city being built off the shore of Lagos. Important social, cultural, and environmental activities attract people to coastal shore. People visit and live near the coast for various reasons ranging from tourism, fishing, surfing, and other recreational activities. Coastal erosion, flooding and water pollution affect man-made infrastructure and coastal ecosystems (Sanò et al., 2011). Several problems tend to arise in eroding areas. These include loss of beach, property loss, damage to infrastructure such as roads transport and water treatment systems (Rangel-Buitrago et al., 2015).

There is evidence that coastal forests and trees provide some coastal protection and that the clearing of coastal forests and trees has increased the vulnerability of coasts to erosion such as in Viet Nam (Cat et al., 2006), Sri Lanka (Samarayanke, 2003), India (Gopinath and Seralathan, 2005) and Thailand (Thampanya et al., 2006). Kunreuther, 1998 and Godschalk et al., 1998, reported that the costs of coastal disasters are raising as more people and structures are exposed to hazards. Heinz Center (1999) emphasized that many hidden costs relating to coastal hazards are imposed on the business community, individuals, families and neighborhoods, public and private institutions, and natural resources and the environment. Regulatory measures for shoreline management include specific rules and conditions for land use, construction, and development. These include a determination of the inland extent to which any coastal regulations apply and name the state and local agencies authorized to administer the regulations. In some areas, groins, seawalls, bulkheads, and other measures are used to prevent erosion of the coastline. However, the seriousness of coastal erosion calls for urgent action irrespective of possible acceleration in sea level rise.

The objective of this study is to investigate the impact of coastal erosion on Alpha beach community and their environment with a view of finding preventive measures to combat the effects. In order to find this objective, the following research questions were asked. i. How does coastal erosion affect the residents of Alpha beach community? ii. What measures can be taken to combat the effect of coastal erosion?

MATERIALS AND METHODS A descriptive survey research design was adopted in this study to investigate the impact of coastal erosion on Alpha beach community in Lagos, Nigeria. Survey design was adopted because representative sample of the population studied was selected and the result generated from the study was generalized to the population under investigation. The sample population for the study comprises 60 respondents living or working in Alpha beach community in Lagos. Simple random sampling technique was used to select the respondents from coastal property and businesses owners as well as other members of the community affected by coastal erosion. The study was thus limited to Alpha beach community in Lagos. The instruments used for data collection were observation and personal interviews using structured questionnaires. The questionnaire consists of two sections. The first section


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focused on the socio-economic characteristics of the respondents while the second section had 18 Likert type items and was designed to assess the impact of coastal erosion on Alpha beach community and their environment. This include functions aimed to indicate strongly agreed = 4, agreed =3, disagreed =2, strongly disagreed =1. The questionnaire was validated to improve the quality and content before administration. The test-reset reliability scale yielded reliability coefficient of 0.80.

Data analysis: Data collected were summarized and computed using frequency counts and percentages while information on the influence of coastal erosion on various activities of the Alpha beach community were computed on a three and four point Likert Rating Scale (LRS), strongly agreed = 4, agreed = 3, disagreed = 2, strongly disagreed = 1. The mean score was computed as 4+3+2+1 = 10/4 =2.50. Using the interval score of 0.05, the upper limit cut-off was determined as 2.50 + 0.05 = 2.55 and the lower limit as 2.50 - 0.05 = 2.45. On the basis of this, mean score (MS) below 2.45 (i.e. < 2.45) were ranked ‘low’, those between 2.45 and 2.54 were considered ‘medium’ (i.e. 2.45 ≥ MS ≤ 2.54), while the mean score greater than or equal to 2.55 (i.e. MS ≥ 2.55) were considered ‘high’.

RESULTS AND DISCUSSION

Socio-economic Characteristics of the Respondents The summary of selected socio-economic characteristics of members of Alpha beach community is shown in Table 1. Their average age is 40 years; majority of them (79%) of them were below 50 years old. This is an indication that most of the Alpha beach community members are still young, physically able and energetic with the potential to control the oceanic erosion effectively. Majority of the community members (78%) are married with only 22% singles. 11% had attained tertiary education while 39% had secondary education. This shows that if control measures are introduced the community members will not be challenged in implementing it. Such measures can focus on preventing the adverse effects of the oceanic erosion. On the average 56% of the community members are property owners; an indication that most of them will probably be victims of the coastal erosion hazard. Some of the community members (30%) reside close to the beach while 26% of them have their workplace and business close to the beach.

Table1: Socio-economic characteristics of the community members Characteristics Frequency Percentage

(%) Gender Male

Female 30 50 30 50

Age 21 - 30 years 31 – 40 years 41 - 50 years 51 years and above Average 40 years

11 19 19 31 17 29 13 21

Marital status Single Married

13 22 47 78

Educational attainment No formal Education Primary Secondary Tertiary

13 22 17 28 23 39 7 11

Ownership of property Yes No

34 56 26 44

Nearness of the beach to residence

Close (1 – 5 kilometers) Far (beyond 5 kilometers)

18 30 42 70


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Nearness of the beach to place of work/ business

Close (300 meters – 1 km) Far (beyond 1 km)

16 26 44 74

Table 2: Extent of loss experienced by community members due to Coastal Erosion (August – November, 2014)

Variable Frequency Percentage (%)

Erosion Experience Experience loss Did not experience loss

55 92 05 08

Proportion of loss experienced 80% 60% 40% 20%

12 20 09 15 15 25 24 40

Majority (92%) of the community members encountered loss due to coastal erosion (Table 2). The coastal erosion had long washed away the tarred road which was the lifeline of economic activities there. It also destroyed many shops, bars, and market stalls that were the community members’ means of livelihood. It also destroyed a church located on the beach (Figure 1). Also in line of destruction was a community health Centre (Figure 2) while a mosque on the beach was also reduced to rubbles. The coastal had also rendered many of the community members homeless.

In addition, the coastal erosion causes high incidence of water borne diseases, extinction of plants and animals and higher risk of environmental pollution (Figure 3). Houses close to the eroding shore now worth less than similar houses close to relatively stable shorelines as reflected in their sales price. Coastal property owners express strong emotional attachment to their properties; they prefer to redevelop the structures damaged by coastal erosion rather than demolish them.

Figure 1: A church building destroyed by coastal erosion at the beach.

Figure 2: A community health Centre destroyed by coastal erosion at the beach


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Figure 3: Shore covered with deposits from coastal erosion at the beach (pollution).

Influence of Coastal Erosion on the various activities of the Community Members Table 3 shows the impact of coastal erosion on the various activities of the community members. Mean scores greater 2.55 were rated as high. Based on this, coastal erosion was found to have a significant effect on all the activities except community road and government’s awareness of the problem. The community members are indeed suffering seriously from the ill effects of the coastal erosion. The government and other stakeholders should as a matter of urgency come to their aid by devising appropriate protective measures to combat the negative effects of coastal erosion on alpha beach community. Table 3: The impact of coastal erosion on the various activities of the community members

Variables Strongly disagreed

Disagreed Agreed Strongly agreed

Total Mean Score

Influence of coastal erosion on water volume.

0 (0.0) 0 (0.00) 39 (1.95) 21 (1.40) 60 3.35

Influence of coastal erosion on houses in the community.

0 (0.00) 0 (0.00) 7 (0.35) 53 (3.53) 60 3.88

Influence of coastal erosion on landmass.

0 (0.00) 0 (0.00) 5 (0.25) 55 (3.67) 60 3.92

Influence of coastal erosion on community members’ abode.

0 (0.00) 0 (0.00) 8 (0.4) 52 (3.47) 60 3.87

Influence of coastal erosion on community development.

0 (0.00) 1 (0.03) 16(0.80) 43 (2.87) 60 3.70

Influence of coastal erosion on farmlands.

1 (0.02) 0 (0.00) 48 (2.40) 11 (0.73) 60 3.15

Influence of coastal erosion on community roads

0 (0.00) 0 (0.00) 17 (0.85) 43 (0.87) 60 1.72

Influence of coastal erosion on the community’s social life.

0 (0.00) 0 (0.00) 20 (1.00) 40 (2.67) 60 3.67

Seasonal influence of coastal erosion.

0 (0.00) 5 (0.17) 53 (2.65) 2 (0.13) 60 2.95

Influence of coastal erosion on community members’ job.

0 (0.00) 1 (0.03) 52 (2.60) 7 (0.47) 60 3.10

Influence of coastal erosion on plant species.

0 (0.00) 0 (0.00) 55 (2.75) 5 (0.33) 60 3.08

Influence of coastal erosion on animal species.

0 (0.00) 0 (0.00) 55 (2.75) 5 (0.33) 60 3.08

Influence of coastal erosion on the community’s population.

0 (0.00) 0 (0.00) 19 (0.11) 41 (2.73) 60 2.84


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Loss to the community for the 10 years (quantified in hundreds of Millions of Naira).

0 (0.00) 0 (0.00) 31 (1.55) 29 (1.93) 60 3.48

Loss to individual community members for the 10 years (quantified in tens of Millions of Naira).

0 (0.00) 0 (0.00) 26 (1.30) 34 (2.27)

60 3.57

In the next few years more harm will be encured if the situation is left unchecked.

0 (0.00) 0 (0.00) 40 (2.00) 20 (1.33) 60 3.33

You are taking some control measures to salvage this situation

2 (0.03) 25 (0.83) 6 (0.30) 27 (1.80)

60 2.96

Government’s awareness of the problem.

1 (0.02) 24 (0.80) 25 (1.25) 10 (0.67)

60 2.02

It can lead to the disappearance of the community from the map of Lagos state.

0 (0.00) 0 (0.00) 34 (1.70) 26 (1.73) 60 3.43

Coping mechanisms against coastal erosion In the past, Alpha community members responded to the oceanic erosion by relocating inland. However, most of the land had been sold off hence such relocations are no longer possible. Nowadays, they have devised various coping mechanisms at home, business and workplace. The approaches available to avoid the adverse effects of coastal erosion include setting structures far away from the shore, sand fencing, use of sand mounds, sand dunes and sand bags. The aforementioned approaches are not very effective; hence the community members are appealing to the government to urgently come to their aid by putting some measures in place to control the coastal erosion.

CONCLUSION AND RECOMMENDATIONS

It is evident from the research work that coastal erosion had some adverse effects on the alpha beach community. Based on the findings of the study, the following recommendations are made: Alpha beach community members should be educated on the coping and control mechanisms to combat the adverse effects of oceanic erosion. The government and other stakeholders should provide affordable health services for the community members. Federal government should as a matter of urgency construct an embankment to save guard future occurrence of oceanic erosion at Alpha beach. The government should also provide assistance to the disaster victims.

ACKNOWLEDGEMENTS I wish to appreciate the community and their leaders for their understanding and cooperation throughout the period of the study. I also want to appreciate my beloved husband, Mr Alex. A. Chukwu for his moral and financial support during the period.


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REFERENCES

Cat, N.N., Tien, P.H., Sam, D.D. & N.N. Bien. (2006). Status of coastal erosion of Viet Nam

and proposed measures for protection. This volume (abstract). Douglas, B.C. (1995). Global sea level change: Determination and interpretation. Reviews

of Geophysics (supp.) July: 1425–1432. Godschalk, D., Beatley, T., Berke, P., Brower, D.J. and E.J. Kaiser, E.J. (1998). National

Hazard Mitigation: Recasting Disaster Policy and Planning. Covelo, Calif.: Island Press.

Gopinath, G. & Seralathan, P. (2005). Rapid erosion of the coast of Sagar island, West Bengal India. Environment Geology, 48: 1058–1067.

Heinz Center. (1999). The Hidden Costs of Coastal Hazards-Implications for risk assessment and mitigation. Covelo, Calif.: Island Press.

Houghton, J.T., Meira Filho, L.G., Callander, B.A., Harris, N., Kattenberg, A. and Maskell, K. eds. (1996). Climate change 1995: The science of climate change. Report by the Intergovernmental Panel on Climate Change. New York, N.Y.: Cambridge University Press.

Kunreuther, H. (1998). Introduction. Chapter 1 in Paying the price: The Status and Role of Insurance against Natural Disasters in the United States, H. Kunreuther and R. Roth, Sr., eds. Washington, D.C.: Joseph Henry Press.

Leatherman, S.P. (1993). Modes of shoreline behavior: Erosion rate analysis using geomorphic principles. pp. 218–223 in Proceedings of International Coastal Symposium, Hilton Head Island, S.C.

Leatherman, S.P., Zhang, K. and Douglas. B. (1999). Sea level rise shown to drive beach erosion. EOS (81): 55-57.

National Oceanic and Atmospheric Administration (NOAA). (1999). Billion-dollar U.S. Weather Disasters 1980–1999. Asheville, N.C.: National Climatic Data Center. Available at http://www.ncdc.noaa.gov/ol/reports/billionz.html.

Rangel-Buitrago, N. G, Anfuso, G. and Williams, A. T. (2015). Coastal erosion along the Caribbean coast of Colombia: Magnitudes, causes and management. Ocean and Coastal Management, 114: 129-144.

Rijn, L. C. (2011). Coastal Erosion and Control. Ocean and CoastalManagement, 54 (12): 867- 887.

Samarayanke, R. A. D. B. (2003). Review of national fisheries situation in Sri Lanka. In: G. Silvestre, L. Garces, I. Stobutzki, M. Ahed, R.A. Valmonte-Santos, C. Luna, L. Lachica-Alino, P. Munro, V. Christense & D. Pauly (Eds.). Assessment, management and future direction of coastal fisheries in Asian countries, pp. 987–1012. WorldFish Center Conference Proceedings 1120 pp.

Sanò, M., Jiménez, J.A., Medina, R., Stanica, A., Sanchez-Arcilla, A and Trumbic, I. (2011). The role of coastal setbacks in the context of coastal erosion and climate change. Ocean and CoastalManagement, 54 (12): 943-950.

Thampanya, U., Vermaat, J.E., Sinsakul, S. & Panapitukkul, N. (2006). Coastal erosion and mangrove progradation of Southern Thailand. Estuarine, Coastal and Shelf Science, 68: 75–85.


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HEIGHT-DIAMETER PREDICTION MODEL FOR EHOR TROPICAL

NATURAL FOREST RESERVE IN NIGERIA

*Aigbe, H. I. and Amadi, I.

Department of Forestry and Wildlife Management, Faculty of Agriculture, University of Port Harcourt, Choba, P.M.B. 5323, Port Harcourt, Nigeria

*Corresponding author’s Email: [email protected]

ABSTRACT Height-diameter relationships have been applied in forest management for various practical purposes and are important in forest inventory determination. In this study, height-diameter models were developed for Benin City (BC) areas 12/1, 15/1 and 16/1 in Ehor Forest Reserve, Edo State, Nigeria. Systemic line transect was employed for data collection. Sample plots of size, 20m x 20m (0.04 ha) were laid and woody plant species with diameter at breast height (dbh) ≥ 5 cm were identified and their dbh and height measured. Eight models were evaluated based on adjusted coefficient of determination (R2adj), Standard Error of Estimate (SEE), F ratio and residual plot. The results indicates that the average number of tree per hectare were 206, 809 and 675 for BC’s 12/1, 15/1 and 16/1 respectively. Linear and logarithmic models were most suitable model for BC 12/1 while logarithmic and polynomial models were most suitable models for BC 15/1. Linear, logarithmic and polynomial equations were the best adjudged models for BC 16/1. The residual graph shows the model does not violate the assumption of independence of error. Key word: Height-diameter relationships, Ehor Forest Reserve, logarithmic and linear models, polynomial equations.

INTRODUCTION Diameter at breast height (dbh) and tree height are important tree characteristics that are very useful in prediction of tree dimension (Buba, 2013). The relationship between dbh-height is considered extremely necessary in forest inventories (Afrifa and Adomako, 2014). They have been applied in forest management for various practical purposes (Afrifa and Adomako, 2014). Height-diameter prediction model are principally applied in height estimations (Gonzalez et al., 2007) and for predicting missing total height (Huang et al., 1992). Tree total height is important for estimating tree volume (Walters and Hann 1986) and assessing stand productivity through site index (Hann and Scrivani, 1987). According to Huang et al., (1994), tree height is usually measured only for a subsample of trees selected across the range of diameters observed, while diameter is measured conventionally for all the sampled trees. The reason is because measurement of dbh variable is easy and fast but the measurement of height is time consuming and more difficult. As a result, foresters estimate the remaining heights with height–dbh prediction model. Foresters can also use height–dbh prediction model to indirectly estimate tree height growth by applying the model to dbh that were either measured directly in a continuous inventory or predicted indirectly by a dbh-growth equation.

Height-dbh prediction model can either be used for local application or regional application. The local application depends on tree dbh that is only applicable to the stand where the height-dbh data were gathered. The regional application which utilizes the generalized height-dbh equations are a function of tree diameter and stand variables and can be applied at the regional level. Several approaches have been described and utilized for generalized height–dbh relationships (Sharma and Parton, 2007). Huang et al. (2000) and Zhang et al. (2002) developed discrete models for different ecological and geographical

Aigbe, H. I. and Amadi, I. (2017). Height-diameter Prediction Model for Ehor Tropical Natural Forest Reserve in Nigeria. Journal of Environment and Sustainable Development, 3(1): 35-45.


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regions. Aigbe and Oyebade (2012) investigated height-diameter model for Sakponba Forest Reserve, Nigeria. The objective of this study was to developed height-dbh prediction model for Ehor tropical Forest Reserve that will be useful for forest inventories and serves as management tools for sustainable forest management. The study represents the first major attempt to model height- dbh in the reserve.


Study data Ehor Forest Reserve constitute BC 16/1, BC 15/1 and BC 12/1 areas. It occupies 7,680 hectares of land (Figure 1). It is situated between latitudes 6.00 34’ N and 6.00 38’ N and longitudes 5.00 54’ E and 5.00 58’ E (Ihenyen et al., 2010). The soil of Ehor Forest Reserve is well drained and composed of sands, sandy loam and loamy sands. The BC areas differ in terms of topography. The BC 12/1 is highly undulated and BC 15/1 has flat topography while BC 16/1 has flat, undulating and sloppy topography. The mean annual temperature in Ehor is 25.50C. March is the hottest month of the year (en Climate-data, 2015). The average temperature in August is 23.70C, it is the lowest mean temperature of the whole year. The mean temperature fluctuates during the year by 3.4 0C (en Climate-data, 2015). The mean precipitation is 1755mm. Precipitation is lowest in January with an average of 10mm (en Climate-data, 2015). The difference in precipitation between the driest and wettest months is 301 mm (Aigbe and Odulami, 2016).

Source:Azeez et al, (2010) Figure 1: Map of Edo State showing the three BC areas of Ehor Forest Reserve Systemic line transect was employed for laying of plots. Two transects with a distance of 500m between them were laid at the centre of each of the three BC areas. Sample plots of size, 20m x 20m (0.04 ha) were laid in alternate direction along each transect at 250m interval and thus summing up to 4 sample plots per transect and a total of 8 sample plots per study site. This method was used to ensure that the forest is relatively covered (Adekunle et al., 2013). Within each plot, woody plant species with diameter at breast height (dbh) ≥ 5 cm were identified and their dbh and height measured. Trees were identified by their


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botanical names and family names by an experienced forest taxonomist. Some of the tree’s that their botanical name was not immediately known on the field were identified by their common name. Trees that were not identified by botanical and common names in the field were designated “unknown”, and samples of their part(s) (such as leaves, bark, fruits) were collected and used for identification in the laboratory. Data Analysis Regression analysis was used to determine the statistical relationship between height and dbh of trees in the three BC areas. Linear, quadratic, inverse and quadratic regression models were tested. The best adjudged model was chosen based on high adjusted coefficient of determination (R), adjusted coefficient of determination (R2

adj) lowest Standard Error of Estimate (SEE), highest F ratio (F) and equations that produced unbiased estimates as well as residual plots that shows conformity with the assumption of independence of error. A confidence level of 95 % probability was used for statistical significance.

RESULTS AND DISCUSSION A summary of tree growth attribute is shown in Table 1. BC’s 12/1, 15/1 and 16/1 had average dbh/cm of 10.0 ± 0.27, 18.17 ± 0.59 and 21.48 ± 0.57 respectively while the average height/m were 8.40 ± 0.33, 12.61 ± 0.40, and 14.70 ± 0.39 respectively. The table indicates that the average number of tree per hectare were 206, 809 and 675 for BC’s 12/1, 15/1 and 16/1 respectively. These values are indication that the forest reserve is still vigour and healthy. The diverse nature of tropical rainforest may have contributed to such number of trees per hectare in the forest reserve because Onyekwelu et al, (2008) reported that between 100 and 300 tree species ha-1 is found in rainforests. Nwoboshi (1982) also stated that the number of tree species ha-1 in very rich rainforests could be as high as 400.

Following several iteration, the best model were chosen based on highest adjusted coefficient of determination (R2adj)), lowest Standard Error of Estimate (SEE), highest F ratio (F) and equations that produced unbiased estimates as well as residual plots that shows conformity with the assumption of independence of error. These statistics value for evaluation are indication of goodness of fit. At times, one cannot get all this evaluation results from a single model. The best approach to getting the best model therefore, is to look out for the model that has most represented statistics value for evaluation of regression equations.

In BC 12/1, model 1 as shown in Table 2 had the highest R2adj. (0.578) and the highest

F ratio (90.04) but its SEE (1.752) compared with the other models appear to be high. On the other hand, the model with the lowest SEE (model 3) had R2

adj. and F ratio of 0.501 and 66.29 respectively. Although, the entire model developed for BC 12/1 were significant (p ≤ 0.05) but model 1 (linear) and 2 (logarithmic) appear to be best in predicting the total tree height from dbh because model 1 had the highest R2

adj. and the highest F ratio while model 2 had a lower SEE, a relatively higher R2

adj. and the higher F ratio (Table 2). The models developed for BC 15/1 are presented in Table 3. Out of the several

models, model 2 (logarithmic) and 4 (polynomial) were adjudged the best for predicting total tree height from dbh in BC area 15/1. Model 2 had R2

adj. value to be 0.617 and SEE = 0.373. Its F ratio value was 415.99. Model 2 had the highest F ratio and a significantly low SEE which made the regression equation considered best. The R2adj. value (model 2) was also significantly good. Model 4 had R2

adj. of 0.712 and F ratio of 321.39. Table 4 showed the models developed for BC 16/1. All the regression equations

were significant (p ≤ 0.05) but models 1 (linear), 2 (logarithmic), 4 (polynomial) and 7 (polynomial) were adjudged the best. The R2

adj. (0.653) value and F ratio (408.26) value


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were the factors that gave model 1 the advantage of been chosen. Models 2, 4 and 7 had R2

adj. values of 0.643, 0.686 and 0.698 respectively. Several height–diameter equations have been developed using only tree diameter as

the predictor variable for estimating total tree height (e.g., Moore et al., 1996; Peng et al., 2001; Jayaraman and Zakrzewski, 2001; Colbert et al., 2002; Robinson and Wykoff, 2004; Aigbe and Oyebade, 2012). In this study, linear and logarithmic equations were adjudged the best for BC 12/1 while logarithmic and polynomial equations were adjudged best for BC 15/1. BC 16/1 had linear, logarithmic and polynomial equations as best equations. Afrifa and Adomako (2014) had reported linear regression model for height-diameter relationship. Kalipsiz (1984); Demirci and Gul (1993); Avsar (2004) had all stated that the relationship between height and dbh could be described by polynomial equation. Many of the height–diameter equations obtainable in previous research findings use a log-linear model form (Curtis 1967; Wykoff et al. 1982; Aigbe and Oyebade, 2012). However, the relation between the height of tree and its diameter varies among stands (Calama and Montero, 2004) and depends on the stand conditions and environmental influence (Sharma and Zhang, 2004).

The residual graphs for BC 12/1, 15/1 and 16/1 models over a range of independent to investigate the homogeneity of variance and confirm conformity of the regression equation to the assumption of regression analysis are shown in Figures 2a –h, 3a – h and 4a – h respectively. The graphs depicted that the spread of the residuals on the positive and negative sides of the plot have a constant breadth and are horizontal (Aigbe, 2014). This implies that it is homogenous, does not violate the assumption of independence of error and does not follow any systematic trend.


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Table 1: Summary of Tree Growth Attribute in the Study Areas

Site Average tree/ha

Average dbh/cm

Minimum dbh/cm

Maximum dbh/cm

Average Height/m

Minimum Height/m

Maximum Height/m

BC 12/1 206 10±0.270 6.68 18.14 8.40±0.332 3.90 15.30 BC 15/1 809 18.17±0.588 4.50 76.38 12.61±0.396 2.40 25.20 BC 16/1 675 21.48±0.565 5.73 47.74 14.70±0.388 2.70 25.50

Source: Aigbe and Odulami, 2016

Table 2: Regression Models for BC Area 12/1

Model Model Form R R2 R2adj SEE F a bo b1 b2 1 H = a + b0 (D)* 0.765 0.585 0.578 1.752 90.04 0.5650 0.7632 2 LnH= a+ b0 (LnD) * 0.755 0.569 0.563 0.206 84.66 -0.0604 0.9319 3 H-1 = a + b0 (D-1) * 0.713 0.509 0.501 0.029 66.29 0.0105 1.1620 4 H = a + b0 (D) + b1 + (D2) * 0.765 0.588 0.572 1.765 44.37 -0.0325 0.8757 -0.00495 5 H-1 = a + b0 (D) * 0.686 0.470 0.462 0.030 56.85 0.2384 -0.0105 6 H = a + b0 (D + 1) * 0.765 0.585 0.578 1.752 90.07 -0.1986 0.7632 7 H = a + bo (D) + b1 (D2) + b2 (D3) * 0.768 0.589 0.569 1.770 29.63 -9.4157 3.4895 -0.23557 0.006454 8 H = a + b0 (D-1) * 0.744 0.554 0.547 1.816 79.407 16.6311 -79.366

H = Total height/m; D = dbh/cm; R =correlation coefficient; R2 = coefficient of determination; Radj.= adjusted coefficient of determination; SEE = Standard Error of Estimate; F = F ratio; a, bo, b1, b2 = fitting parameters; * = significant at P < 0.05


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Table 3: Regression Models for BC Area 15/1

Model Model Form R R2 Radj SEE F a bo b1 b2 1 H = a + b0 (D) * 0.742 0.551 0.549 4.274 315.10 3.534 0.4996 2 LnH= a+ b0 (LnD) * 0.786 0.618 0.617 0.373 415.79 -0.253 0.9472 3 H-1 = a + b0 (D-1) * 0.741 0.548 0.547 0.0528 311.91 0.000304 1.59816 4 H = a + b0 (D) + b1 + (D2) * 0.846 0.715 0.712 3.410 321.39 -3.295 1.1792 -0.01317 5 H-1 = a + b0 (D) * 0.588 0.346 0.343 0.0636 135.99 0.201581 -0.00488 6 H = a + b0 (D + 1) * 0.742 0.551 0.549 4.274 315.10 3.035 0.4996 7 H = a + bo (D) + b1 (D2) + b2 (D3) * 0.847 0.718 0.714 3.401 216.07 -1.724 0.9541 -0.00484 -7.9x10-5

8 H = a + b0 (D-1) * 0.752 0.566 0.564 4.203 334.61 21.885 -131.657 H = Total height/m; D = dbh/cm; R =correlation coefficient; R2 = coefficient of determination; Radj.= adjusted coefficient of determination; SEE = Standard Error of Estimate; F = F ratio; a, bo, b1, b2 = fitting parameters; * = significant at P < 0.05 Table 4: Regression Models for BC Area 16/1

Model Model Form R R2 Radj SEE F a bo b1 b2 1 H = a + b0 (D) * 0.809 0.655 0.653 3.367 408.26 2.7527 0.5562 2 LnH= a+ b0 (LnD) * 0.803 0.645 0.643 0.285 390.68 -0.1331 0.9122 3 H-1 = a + b0 (D-1) * 0.772 0.596 0.594 0.033 317.41 0.003959 1.4670 4 H = a + b0 (D) + b1 + (D2) * 0.830 0.689 0.686 3.205 236.84 -2.5232 1.0678 -0.01077 5 H-1 = a + b0 (D) * 0.654 0.428 0.425 0.039 160.74 0.1734 -0.00409 6 H = a + b0 (D + 1) * 0.809 0.655 0.653 3.367 408.26 2.1966 0.5562 7 H = a + bo (D) + b1 (D2) + b2 (D3) * 0.838 0.702 0.698 3.142 167.57 4.2454 0.0054 0.037077 -0.00064 8 H = a + b0 (D-1) * 0.748 0.559 0.557 3.808 272.19 23.36388 -155.977

H = Total height/m; D = dbh/cm; R =correlation coefficient; R2 = coefficient of determination; Radj.= adjusted coefficient of determination; SEE = Standard Error of Estimate; F = F ratio; a, bo, b1, b2 = fitting parameters; * = significant at P < 0.05.


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Fig. 2a: Residual plot using total height function based on dbh alone

Fig. 2b: Residual plot using logarithmic total height function based on logarithmic dbh alone

Fig. 2c: Residual plot using total height inverse function based on dbh inverse alone

Fig. 2d: Residual plot using total height function based on dbh & dbh2

Fig. 2e: Residual plot using total height inverse function based on dbh alone

Fig. 2f: Residual plot using total height function based on dbh + 1alone

Fig. 2g: Residual plot using total height function based on dbh/dbh2/dbh3 inverse alone

Fig. 2h: Residual plot using total height function based on dbh inverse alone

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Fig. 3d: Residual plot using total height function based on dbh/dbh2


Fig. 3f: Residual plot using total height function based on dbh + 1alone

Fig. 3g: Residual plot using total height function based on dbh/dbh2/dbh3 inverse alone


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Fig. 4d: Residual plot using total height function based on dbh & dbh2


Fig. 4f: Residual plot using total height function based on dbh + 1 alone

Fig. 4h: Residual plot using total height function based on dbh/dbh2/dbh3 inverse alone


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CONCLUSION

This study has shown that the estimation of total tree height from dbh is appropriate because of the strong correlation between total tree height and dbh. Linear, logarithmic and polynomial equations were suitable in predicting total tree height from dbh in BC areas 12/1, 15/1 and 16/1 of Ehor Forest Reserve. The models developed is very useful in optimizing the cost of carrying out forest inventory and reducing the time spent in the forest during measurements. The applicability of the models developed in this study is limited to the study area. Additional data is required for suitability outside the study area to improve the prediction validity of the model.

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EFFECT OF DIFFERENT LAND USE ON SOIL MICROBIAL BIOM ASS

CARBON AND NITROGEN IN ACID SAND, UYO, NIGERIA

Godwin U. Akpan1 and Mohammed Iliyasu2

1 Department of Soil Science and Land Resources Management, University of Uyo, P.M.B. 1017 Uyo, Nigeria

2 Department of Soil Science University of Calabar, P.M.B. 1115, Calabar, Nigeria

ABSTRACT Soil quality changes with different types of land use and management and depends on the physical, chemical, biological and biochemical properties of the soil. This study examined the effect of different land use on soil microbial biomass carbon and nitrogen. The research was carried out in Uyo, Nigeria between September, 2013 to May, 2015. Soil samples were collected from soils under three land use types namely forest, pasture and cultivated soils at the depths of 0-15 and 05-30cm. After soil analysis, the results showed that forest soil had the highest organic carbon (43.8+5.8g/kg) followed by cultivated soil (39.6 3.2g/kg) while the pasture had the least (36.5 +14.1g/kg). The highest total nitrogen was obtained from forest soil (1.9+0.02g/kg) followed by cultivated soil (1.6+0.1g/kg) and pasture soil had the least (1.2+0.1g/kg). The results also showed that the forest soil had significant (P <0.05) microbial biomass carbon (25.10+1.18µgg-1) follow by pasture (8.30 +0.22 µgg-1) and cultivated soils (1.60 + 0.01 µgg-1), respectively. Similarly, the forest soil had microbial biomass nitrogen significantly (P<0.05) higher than pasture and cultivated soils both at the surface and sub-subsurface soils. Conclusively, land use and management methods have effect on soil properties.

Key Words: Acid sands, microbial biomass carbon, Nitrogen, land use.

INTRODUCTION Soil microbial biomass acts as the transformation agent of the organic matter in soil. As such, the biomass is both a source and sink of the nutrients C, N, P and S contained in the organic matter. It is the centre of the majority of biological activity in soil (Jekinson 1988). To properly understand biological activity in soil, one must therefore have knowledge of the microbial biomass.

Investigating the flow of C and N in the soil from newly deposited plant or other materials to the mineral forms of carbon dioxide and ammonium or nitrate ions clearly shows the central role of the microbial biomass. Microbial biomass is therefore the living portion of the soil organic matter, excluding plants roots and soil animals larger than 5x103 µm (Ley, Lipson, and Schmidt, 2001). Microbial biomass generally comprises approximately 2% of the total organic matter in soil and it may be easily dismissed as of minor importance in the soil. But microbial biomass is an important agent in controlling the overall biological activity of the soil. The soil microbial biomass is the active component of the soil organic pool which is responsible for organic matter decomposition affecting soil nutrient content and consequently primary productivity in most biogeochemical processes in terrestrial ecosystem (Franzlubbers, Haney and Hans, 1999). Cregorich, Liang, Drug, Mackernzie and McGill 2000, Haney, Franzludders, Hans, Hossien and Zubener 2001). The importance of micro-organisms in ecosystem functioning has led to an increased interest in determining soil microbial biomass (Azam, Farooq and Lodh, 2003).

Akpan, G. U. and Iliyasu, M. (2017). Effect of Different Land Use on Soil Microbial Biomass Carbon and Nitrogen in Acid Sand, Uyo, Nigeria. Journal of Environment and Sustainable Development, 3(1): 46-55.


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Therefore measuring microbial biomass is a valuable tool for understanding and predicting long-term effects or changes in land use and associated soil conditions (Sharma, Rai, Sharma, and Sharma 2007). The dearth of baseline data on the impact of land use types on microbial biomass C and N in humid tropical rain forest region has led to the assessment of the impact of forest, pasture and agricultural or cultivated lands on microbial biomass C and N in acid sand, Uyo Nigeria.

MATERIAL AND METHODS

The three different land use types considered for this study include forest, pasture and cultivated land and are within the same ecological zone. The forest under study is the forest reserve of the Department of Forestry, University of Uyo. The forest land covers about 30,000 square meters. The vegetation of the forest land consists of Tectona grandis, Gmelina arborea, Acacia aureculiformis, Cola argentea, Brachystegia eurycoma, Terminalia catappa, Pentaclethra macrophylla, Persea americana and Gliricidia sepium. The pasture land is the plot that was formerly used as Teaching and Research Farm of the University of Uyo, it is about 5 hectares. The vegetation of the pasture land consists of Andropogon goganus, Andropogon tectorum, Axonopus compress us, Brachiria lata, combretum hispidum, Cnestis ferruginea and Lieffa cylindrical. The cultivated land is the teaching and research farm of the University of Uyo. It covers an area of 10 hectares. The major annual crops cultivated include maize (Zea mays L.), Fluted pumpkin (Tetfairia occidentalis) and Cassava (Manihot esculenta). Climate of the Study Area The study area is located within the humid tropical rain forest zone of Nigeria. Uyo is within latitude 4o30" and 05o30" N and longitude 7o30" and 08o30" E the soils of Uyo are formed on coastal plain sand deposit (Arenic hapludult). They are generally sandy and acidic with pH ranging from 4.0-6.0 (Kang, Atta-Krah, and Reynolds 1996). Uyo is characterized by two distinct seasons, wet and the dry seasons. The wet season starts from March to October, while the dry season starts from November. A short dry spell is normally noticed in August and is traditionally referred to as August Break. The rainfall ranges from 2000 – 3000mm, the temperature is uniformly high and ranged from 28 – 30°C. Sampling This experiment was conducted in a completely randomized design. Soil samples were collected at the depths of 0-15 and 15-30cm using soil auger. At each land use type, soil sample was augured within three points. Samples from 0-15 and 15-30cm depths were placed in well labeled sampling bags and taken to the laboratory, in the laboratory, the samples were separated into two portions:- (1) Portion meant for the physical and chemical properties was air-dried, sieved and stored far the analysis, (2) The second portion was used for the determination of microbial biomass C and N

(this was done on the fresh moist soil the same day of sampling). DETERMINATION OF SOIL PROPERTIES Soil particle size distribution was determined by hydrometer method (Bouyoucos, 1962), soil reaction (pH) in 1;2.5 soil water suspension by pH meter (Rowell 1994), electrical conductivity (EC) was measured in 1:5 soil/water suspension using electrical conductivity meter, Bulk density was determined as described by Black (1965), organic carbon was determined by Walkley and Black wet oxidative method (1934), Available phosphorus was determined by extracting soil samples with Bray-P-1 extractant (Udo and Ogunwale 1986), Total nitrogen was determined by the micro-kjedhl digestion method (Bremner 1965),


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Exchangeable bases (Ca2+, Mg2+, K+ and Na+) were determined by extracting the soil with IN ammonium acetate (pH 7.0) as described by Udo and Ogunwale (1986). Determination of Microbial Biomass Carbon (MBC) Soil microbial biomass C was estimated by extracting 20.0g field-moist soil samples in 0.5Mk2SO4, known as the chloroform-fumigation-extraction method, described by Brookes, Landman, Pruden and Jekinson (1985) and Vance, Brookes and Jekinson (1987) Duplicate sub samples from each land use type were placed in 50ml glass beakers. Samples designated for fumigation were placed in vacuum desicators. The samples were fumigated with ethanol free choloroform (CHCl3) for 24h in the dark at 28uC in a desicator. After the chloroform was removed, soils were transferred to a 250ml beaker, where 120ml of 0.5MK2O4 was then added. At the same time, the unfumigated soil samples were placed in the beaker bottles and were treated in the same way, where they served as controls. Beakers were shaken for 30min on a reciprocating shaker and supernatants were filtered through a whatman no. 42 fitter paper (Vance, Brookes and Jenkinson 1987). Microbial biomass C was measured in 10ml aliquots of K2SO4 extracts in a test tube, and oxidized with 5ml 0.4Nk2Cr2O and 5ml of H2SO4 were added and digested for 10min and titrated using 0.5 FeSO4 with 1,10-phennathorbine ferrous sulphate as the indicator (Vance, Brookes and Jekinson 1987) . Microbial biomass C was Calculated as follows CMIC = EC/KEC eqn……………………… (1) Where EC = (organic C extracted from fumigated soil) - (organic C extracted from non-fumigated soil). KEC = 2.64, a proportionality factor for converting the Ec value to Cmic Microbial biomass N (Nmic) (Wu, Joergensen, Pommerning, Chaussad and Brookes 1990). The kjeldahl digestives-titration method was used to determine the total N in the K2SO4 extract. With 10ml of 95% H2SO4, 15ml of extract was digested after the addition of 0.4ml of 0.2M CulSo4 to promote organic matter breakdown. The mixture was digested at 380oC for 3 h until all of the organic compounds were decomposed. The solution was brought to a volume of 250ml with subsample was steam-distilled in a strong alkaline solution (10 MNaOH) and the distillate was collected in a boric acid-mixed indicator solution. The solution was then back- titrated (Anderson and Ingram, 1993). N was calculated using the following equation 2 (Brookes, Landman, Pruden, and Jekinson 1985). Biomass N = EN/0.54 eqn …………………………………………………….………(2) Where: EN = (total N from fumigated soil) – (Total N from unfumigated soil) Statistical Analysis Statistical analyses were carried out using SPSSI/08 package programme. The effect of land use on soil properties was determined by one-way analysis of variance. Other descriptive statistics used included mean, standard error.

RESULTS AND DISCUSSION The results in Table 1 showed the physical properties of the soils of the three land use types. The particle size distribution of the soils of respective land use type shows that values were sand particle 850.0+ 14.140, 810.0+42.42g and 790.0+ 14.14g/kg for forest, pasture and cultivated lands respectively. Silt had the values of 80.0+0.0g, 70.0+14.14g and 100.0g/kg of pasture, forest and cultivated lands respectively. The mean values for clay fraction were 70.0+14.14g, 120.0+ 56.57 and 100.0+0.12g/kg in forest, pasture and cultivated soil respectively. The low content of silt and clay fractions suggest that these soils may have


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serious structural instability. This could influence the productivity of the soil negatively. The textural characteristics of these soils showed the predominance of loamy sand (LS) textural class in the land use types in both surface and subsurface horizons. The texture is generally coarse with low activity clay suggestion that the soils may have low soil -water holding capacity. The mean values for bulk density of the soil of the three land use types were 1.52+0.01 gcm31, 1.56+ 0.04 and 1.87+0.04 gcm3 in forest, pasture and cultivated soils respectively. The high bulk density obtained in cultivated soil may be attributed to compaction of the soil as a result of human activity in land preparation using conventional method such as tractor. The high value obtained in pasture land use type may be attributed to movement of animals in and out of the place. Value of bulk density obtained in this study are slightly higher than values obtained by Ogban and Ekerette (2001) in this area. They reported bulk density of 1.40-1.49gcm-3 in soil of coastal plain sands parent materials of Akwa Ibom State. Bulk density of this magnitude reflects the dominance of the particle size by quartz sand fraction. Esu, Akpan-Idiok, Ayolagha and Idoko (2009) highlighted that bulk density values of 1.60-1.80gcm-3 may have low aeration and water movement for optimum plant growth. The values obtained in this study may reflect low aeration and slow percolation of water within these soils which is very essential in nutrient absorption by plants. The results in table 2 show the chemical properties of soil of the land use types. Soil pH of the three land use types were 6.35+0.07, 6.35+0.07 and 6.25 +0.07 in forest, pasture and cultivated soils. Comparatively, forest and pasture soils had the same pH value which was higher than the cultivated soil, but the pH of the three land use types were not significantly (P>0.05) different from each other. The low pH values obtained in the land use types might directly responsible for the low microbial biomass recorded. USDA (2013) highlighted that pH below 6.0 inhibits bacterial activity, and low nutrients availability such as nitrogen, phosphorus, potassium, calcium and magnesium but some bacteria such as Acidothiobacillus ferrooxidans can grow in pH as low as 2.5. Table 1: Physical Properties of the soils Land Use SN Sand

Silt (g)

Clay

Textural Class

BD (gcm-3)

Forest Min 840 80 60.0 LS 1.51 Max 860 80 80.0 LS 1.52 Mean 850.0 80 70.0 LS 1.52 Sd 14.14 0.0 14.14 0.01 CV 1.66 0.0 12.85 0.47 Pasture Min 780 60 80.0 SL 1.55 Max 840 80 160.0 LS 1.57 Mean 810 70.0 120.0 LS 1.56 Sd 42.43 14.14 56.57 0.01 Cv 5.24 20.20 47.14 0.91 Cultivated Min 780 100 100.0 LS 1.54 Max 800 120 100.0 LS 1.59 Mean 790 110.0 100.0 LS 1.87 Sd 14.14 14.14 0.12 0.04 Cv 1.79 12.86 0.0 2.26

The soil of the three land use types is classified as slightly acid and may not pose serious limitation to crop production (Udo, Ibia, Ogunwale, Ano and Esu (2009), Esu, Akpan-Idiok, Ayolagha and Idoko 2009).

The electrical conductivity (EC) obtained in the three land use types had the means values of 0.024 +0.001, 0.043+0.02 and 0.037+0.01 ds/m in forest, pasture and cultivated soil. It can inform trends in salinity, crop performance, nutrient cycling (particularly, nitrate) and


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biological activity and, along with pH, can act as chemical soil health indicators respectively. The electrical conductivity of the three land use types are classified as low (Esu, Akpan-Idiok, Ayolagha and Idoko 2009), and lower than 2 ds/m given by Anderson and Ingram (1993) as critical values for crop production, this implys that these soils may not have any EC threat related issue to crop production.

Organic carbon is a major chemical property of the soil. The values obtained from the three land use types were 47.9 +14.1, 46.5+ 11.4 and 41.8+ 3.2g/kg respectively for forest, pasture and cultivated soils for 0-15cm depth while 15-30 cm depth had the following values 39.7+1.4, 26.5+4.0 and 37.3+3.0 g/kg respectively for forest, pasture and cultivated soil. The occurrence of higher organic carbon higher in the surface soil than the sub surface and may be due to the high accumulation of organic matter in the upper layer of the soil profile. The organic carbon contents in the forest and pasture was higher than that in cultivated soil although it was not significantly (P>0.05) different from each other. The low organic carbon content in the cultivated soil may be attributed to rapid mineralization under the high temperature as well as the soil exposed to direct solar heating and moisture conditions of the tropical climate. The degradation of organic matter content affects the nutrient status and structural stability of the soil, which lead to poor water infiltration and susceptibility of the soil to erosion. The cultivated soil may lack the capacity to supply essential nutrients such as nitrogen, sulphur and phosphorus to crop because of low organic matter content. This is in line with Lal (1989) who reported a linear decline in soil organic matter content with cumulative soil erosion. Generally, forest ecosystems contain higher organic matter due to the regular litter availability and subsequent decomposition. Soil organic matter affects biochemical, chemical, biological and physical soil properties that control soil microbial activity. The nitrogen content of the three land use types are generally low in the surface soil (0-15) and very low in the sub surface (15-30) according to Esu, Akpan-Idiok, Ayolagha and Idoko 2009) rating. The results showed 2.0 +0.02, 1.2+0.01 and 1.8+0.01g/kg respectively for forest, pasture and cultivated land use types in the surface soil (0-15) while the sub surface soil showed 0.17+0.02, 0.11+0.01% and 0.16+0.01% respectively for forest, pasture and cultivated land use types. Comparatively, forest soil had the highest total nitrogen followed by pasture while the cultivated soil had the least, but not statistically (P>0.05) different from each land form type. The available phosphorus was generally at medium level in all the three land use types in both surface and subsurface soils according to Esu, Akpan-Idiok, Ayolagha and Idoko (2009). The values obtained were 13.99+ 0.85mg/kg, 14.8+3.4 mg/kg and 11.99+1.13mg/kg in forest, pasture and cultivated soil respectively for 0-15xm depth, while 15-30cm depth had 12.79+1.13mg/kg, 9.99+3.40mg/kg and 10.39+3.0mg/kg respectively for forest, pasture and cultivated land use types.


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Table 2: Chemical Properties of the soils

Sand use Depth pH

EC P OC TN Ca Mg Na K EA ECEC BS

dS/m Mg/kg g/kg cmol/g % Forest 0-15 6.4 0.021 13.99 47.9 2.0 144.0 16.0 0.8 2.0 24.0 18.68 87.15 15-30 6.3 0.026 12.79 39.7 1.7 100.0 12.0 0.7 1.1 18.0 13.18 86.34 Mean 6.35 0.024 13.39 43.8 1.85 122.0 14.0 0.75 1.6 21.0 15.93 86.745 Sd 0.07 0.00 0.85 5.8 0.02 31.10 2.8 0.1 0.6 4.2 3.89 0.57 Cv 1.11 15.04 6.34 13.24 11.47 250.5 202.0 9.43 41.06 20.20 24.41 0.66 Pasture 0-15 6.4 0.054 14.8 46.5 1.2 108.0 16.0 0.7 1.3 38.0 16.4 76.83 15-30 6.3 0.031 9.99 26.5 1.1 84.0 14.0 0.6 1.2 28.0 12.78 78.09 Mean 6.35 0.043 12.10 36.5 1.65 96.0 15.0 0.7 1.3 33.0 14.59 77.46 Sd 0.07 0.02 3.40 14.1 0.01 17.0 1.4 0.1 0.1 7.1 2.56 0.89 Cv 1.11 38.27 27.44 38.75 6.15 17.68 9.43 10.88 5.66 21.43 17.54 1.15 Cultivated 0-15 6.3 0.032 11.99 41.8 1.8 112.0 190.0 0.7 1.0 39.0 17.07 77.15 15-30 6.2 0.041 10.39 37.3 1.6 88.0 120.0 0.6 0.9 13.0 11.45 88.64 Mean 6.25 0.037 11.19 39.6 1.7 100.0 15.5 0.7 0.95 26.0 14.26 82.895 Sd 0.07 0.01 1.13 3.2 0.01 17.0 4.9 0.1 0.1 18.4 3.97 8.12 Cv 1.13 17.44 10.11 8.05 0.32 16.97 31.93 10.88 7.44 70.71 27.87 9.80

SD = Standard deviation CV= Coefficient of variation


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0

5

10

15

20

25

30

FOREST PASTURE CULTIV

0-15

15-30

Microbial Biomass Carbon (MBC) The values for microbial biomass C were 24.10+1.18, 7.30+0.22, and 1.60+0.001µgg-l soil respectively for forest, pasture and cultivated soil in surface soil while values for subsurface soil were 8.30+2.18, 4.20+0.22 and 1.10+0.01µgg-l respectively for forest, pasture and cultivated (fig 1). The microbial biomass C in the forest soil was significantly (p < 0.05) higher than the pasture and cultivated soils in both the surface and subsurface soils. The higher microbial biomass C in the forest soil may be attributed to high organic matter content of the soil compared to pasture and cultivated soil.

Fig 1: Microbial Biomass C in the three studied land use types

The results obtained in this study are similar to those obtained by Kara and Bolat (2008), they obtained high values of microbial biomass C in forest soil compared to pasture and agricultural soils in temperate soils, while similar result was also reported by Hernot and Robertson (1994) in similar land use types of tropical soils. Microbial Biomass N The results for microbial biomass nitrogen for surface and subsurface were as follows 75.40+2.93µgg-1, 31.30+2.35µgg-1 and 27.30+ 1.35µgg-1 for forest, pasture and cultivated respectively for surface soil (0-15 cm depth) and 5.47+1.93µgg-1, 3.92+0.25µgg-1 and 2.93+0.25µgg-1 for forest, pasture and cultivated soils respectively in the subsurface soil (15-30cm depth) (Fig. 2). The value of microbial biomass N obtained in the forest soil was significantly (P<0.05) higher than the values obtained from pasture and cultivated soils.


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Fig. 2: Microbial Biomass N in the three studies land use types In terms of magnitude, the microbial biomass N was in this order; forest > pasture >cultivated. The higher microbial biomass N in the forest soil might be attributed to high organic matter content of the forest soil and high mineralization of the organic matter by microorganisms to release the nutrient to the soil. Also, forest soil is less disturbed as compared to pasture and cultivated lands.

The microbial biomass N values are in accordance with the results of the previous works (although the values are not the same reported by Sharma, Rai, Sharma and Sharma (2004) for different land uses (forest agroforestry, agriculture and waste land). Martikeinen and Palojarvi (1990) also had higher results for coniferous forest soils. These differences in the microbial biomass C and N may be due to the differences in climatic conditions, difference in ground cover vegetation, the number of roots, soil types and properties, types of land use and management as well as sampling times.

CONCLUSION The results from this study demonstrates that land use methods exert profound influence on microbial biomass C and N. Forest and pasture land use types increased microbial biomass C and N. Different plant species affect soil microbial processes which are dependent upon their litter quality and quantity and also upon below-ground biomass supporting microbial activities. Our data suggest that forest soil may be healthier when compared with other land use soils. It can be concluded that the soil health of the studies land use types is in the order of forest, pasture and cultivated.

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Brookes, P. C. Landman A, Pruden G and Jekinson DS (1985). Chloroform fumigation and release of soil nitrogen: a rapid extraction method to measurement microbial biomass nitrogen in soil. Soil Boil. Biochem. 17:837-842.

Cregorich EC, Liang BC, Drug AF, Mackernzie and McGill WB. (2000). Ehicidaiton of the source and turnover of water soluble and microbial biomass carbon in agricultural soils. Soil Biol. Biochem 32:581-587.

Esu, I. E., Akpan-Idiok, A. U., A. A. Ayolagha and M. Idoko (2009). Soil Fertility Evaluation in Three Southern State (Cross River, Edo and Rivers). Cultancy Report Submitted to the FMAWR, Abuja, 149 pp.

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Haney R.L, Franzluebbers A.J., Hans F. M., Hossien Z. R. and Zubener D. A. (2001). Molar concentration of K2SO4 and soil pH effect estimation of extractable C with chloroform fumigation extraction. Soil Biol. Biochem. 38:1501-1507.

Hernot, J. and G. P. Robertson (1994). Vegetation Removal in Two Soils of the Hurried Tropics: Effect on Microbial Biomass. Soil Biol. Biochem. 26: 111 -116.

Jekinson, D. S. (1988). Determination of Microbial Biomass Carbon and Nitrogen in Soil. In: Advances in Nitrogen Cycling in Agricultural Ecosystems. (Ed. J. R. Wilson). CAB. Wallingfod England. pp. 368 – 386.

Kang, B. T, Atta-Krah, A.N., and Reynolds L. (1999). Alley Farming (The Tropical Agriculturist Series) MacMillan, CTA, IITA. Malaysia, p. 110.

Kara, O. and Bolat, I. (2008). The effect of different land Uses on Soil Microbial biomass carbon and nitrogen in Bartuin Province. Turkish Journal of Agric and Forestry. 32; 281- 288.

Keeney, D.R., Nelson, D.W. (1982). Nitrogen-Inorganic forms. In: Page et al. (Eds.), Methods of soil Analysis, part 2nd

, pp. 642-698. American Society of Agronomy, Madison.

Lal, R. (1989). Agroforestry systems and Soil Surface Management of a Tropical Alfisol. III: Water Runoff, Soil Erosion and Nutrient Loss. Agroforestry Systems 8:97 – 111.

Ley R. E., Lipson D.A. and Schmidt S. K. (2001). Microbial biomass levels in banen and vegetated high attitude talus soils. Soil Sci. Soc. AMJ. 65:111-117.

Martikainen, P. J. and Palojarvi, A. (1990). Evaluation of the fumigation -extraction method for the determination of microbial C and N in a range of forest soils. Soil Biol. Biochem. 22:297-802.

Ogban, P. I. and Ekerette, I. D. (2001). Physical and chemical Properties of the Coastal Plain sand soils of south Eastern Nigeria. Nig. J. Soil Res. 2:6-14.

Rowell, D.L. (1994), Soil Science methods and applications. Longman scientific and Technical Singapore.

Sharma, P. Rai, S.C., Sharma, R. and Sharma, E. (2004). Effects of Landuse change on soil microbial C. N. and P in Himalaya watershed. Redobiologia 48:83-92.

Udo, E. J., Ibia, T. O., Ogunwale, A., Ano, O., Esu, I. E. (2009). Manual of soil, Plant and water analysis. Lagos, Sibon book Limited Nigeria.

Udo, E. J. and Ogunwale, J. A. (1986). Laboratory manual for the analysis of soils, plants and water samples. 2nd edition. Ibadan University Press, p. 45.

Vance, E.D., Brookes, P.C., and Jekinson, D.S. (1987). Microbial biomass measurements in forest soils: the use of chloroform fumigation-incubations methods for strongly acid soils. Soil Biol. Biochem 19:697-702.


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Walkley, A. and Black, A. I. (1934). An examination of the Degjiareff method for determining soil organic matter, and proposed modification of the chronic acid titration method. Soil Sci. 37:29-38.

Wu, J., Joergensen, R.G., Pommerening, B., Chaussad, R. and Brookes, P.C. (1990). Measurement of soil microbial biomass Ca by fumigation extraction-an autoclo claved procedure. Soil Biology and Biochemistry 22: 1167-1169.


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AN ASSESSMENT OF SOCIO-ECONOMIC STATUS OF COMMUNITI ES IN NATIONAL PARKS OF NORTH-EASTERN NIGERIA

Buba Zacharia Yaduma

Department of Forestry and Wildlife Management, Modibbo Adama University of Technology, Yola, Adamawa State

ABSTRACT

The study examined the socio-economic status of communities in 3 (three) national parks located in the north-eastern Nigeria. Structured questionnaire was used for the study. Oral interviews were also carried out among the respondents and park staff. The respondents were selected by random sampling method. Multiple regression models were used to analyse the collected data. The results indicated that some socio-economic indicators were positive and significant at P≤ 0.01 and P≤ 0.05 levels. However, many other indicators were not significant across the three parks. Inspite of this positive significance in some of the parks’ localities, the park managers should still improve the living standards of the communities whenever necessary.

INTRODUCTION The modern approach to conservation recognises the importance of achieving social

and economic development alongside the proper protection of the natural and cultural heritage (Akosim et al., 2007). The Park authority needs to give special attention to approaches that sustain the local communities in and around the park support zone areas. This implies that development options should be particularly geared towards those areas which can provide sustainable benefits to local people as well as to meet wider economic aspirations. What the situation is at present in the support zone of the National Parks in the northeast zone of Nigeria has been documented by Buba (2012), who recorded a low standard level of living (LSL) among the park communities. According to him, this LSL may have given rise to cross illegal poaching and grazing with attendant environmental consequences.

There is therefore a growing concern nationally and even globally, over the destruction and eventual disappearance of valuable fauna and flora species on the tropical forests. Estimates suggest that the annual bush meat harvest from Africa’s tropical forest may now exceed one million tones (Tim, 2009). Other activities such as bush burning, grazing, farming, fishing and extraction of none timber forest products are also carried out illegally in the National Parks (Akosim et al., 2010).

With the age of Nigeria National Parks ranging from 12 to 32 years, it is expected that the envisaged social and economic benefits derivable from the existence of the National Parks would have started actualizing. Study by Marguba (2002) showed that residents in the support zones carry out some illegal activities such as poaching and grazing in the National Parks, an indication that they are not benefiting as expected from the existence of the Parks. This is in line with the findings of Buba (2012), who reported that the Parks’ contributions to the buffer zones communities were discouraging and insignificant. The report recorded a low level of living standard (LSL) across the 3 (three) parks to range from1.98 in Amchaka community to 2.24 in Gashaka community (Buba, 2012). The report also showed that the local dwellers appeared not to be discouraged by the low composite index provided by the parks.

It becomes pertinent to examine the socio-economic indicators of the dwellers in relation to their composite index of level of living standard (CILLS) as reported by Buba (2012). This is to ascertain as to what extent the CILLS affects the communities, hence their non-aggressive attitudes towards the parks’ managers, apart from porching and grazing.

Yaduma, B. Z. (2017). An Assessment of Socio-Economic Status of Communities in National Parks of North-Eastern Nigeria. Journal of Environment and Sustainable Development, 3(1): 56-70


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MATERIALS AND METHODS Study Location

The study was conducted in the support zones of national parks in north east Nigeria. These Parks are: Chad Basin National Park (CBNP), Gashaka-Gumti National Park (GGNP) and Yankari National Park (YKNP). Chad Basin National Park covers an area of 2,258 square kilometers. The park is dotted across Borno and Yobe States and the sectors are Chingurmi-Daguma, Bade-Nguru wetlands and Kilboa Forest (Bulatura Oases). The Parks is geographically situated between latitude 11°0' to 13°00'N and Longitude 13°00' to 15°20'E (Marguba, 2002).

Gashaka-Gumti National Park is the largest of the eight National Parks in Nigeria, covering an area of 6,731 square kilometers. It lies between latitude 6° 55' and 8° 05' and longitude 11° 11' and 12° 13'. The Park boundaries and land mass fall within Adamawa and Taraba States.

Yankari is the nation’s first game reserve with an area of 2,244.10 sq. km. The Park lies within the Sudan Savannah vegetation zone with a vegetation complex known as Bukea africana/Combretum glotinosum type while the swamp flood plain of Gashi and Yashi support mosaic vegetation. It is situated within Duguri, Pali and Gwana Districts of Alkaleri Local Government Area of Bauchi State on coordinates 09° 45'N and 10° 30'E. The Park boundaries and land mass fall within Bauchi State of Nigeria and shares boundary with Plateau and Gombe States (Marguba, 2002).

Structured questionnaire for the support zone dwellers and interview with parks’ managements were the tools used in this study. Purposive sampling method was used in selecting National Parks and Support Zone Communities. Random sampling method was used in selecting respondents in the support zone communities. In CBNP, five communities, namely: Danguma, Bulatura, Amchaka, Chingurmi and Yusufari were selected. In GCNP, the following communities were selected: Tikobi, Gumti, Gashaka and Mayo-Salbe; while Maina-Maji, Yelwa-Dukuri, Pali, Yello and Baggos were selected from YKNP.

Six hundred (600) copies of the questionnaires were distributed; however, only four hundred and fifty eight were returned. The questionnaire was designed to collect data on socio-economic indicators: health, schools, schools, water, road, electricity, employment, housing, ownership of mobility, electronics, agricultural productivity and income earnings of the respondents. Data Analysis

The relationship between calculated composite index of living standard as reported by Buba (2012) and socio-economic indicators was determined using multiple regression models (Ogunleye 2002; Ogwumike et al., 2005 and Gbadegesin et al., 2005). The computed composite index of living standard was the dependent variable while the socio-economic indicators were the independent variables. Data were fitted to four functional forms of regression equations in order to select the lead equation. The four functional forms are: (a) Linear function: This is the simplest of all functional forms and is conveniently used

in developing basic statistical and econometric concepts. This can be expressed as: Y = b0 + b1x1 + b2x2 + b3x3 + b4x4 +. . . . . . . . .bll xll + ui

(b) Exponential function: This is the function in which the logarithmic operator is attached to the dependent variable and expressed as: Logy = b0 + b1x1 + b2x2 + b3x3 + b4x4 +. . . . . . . . . bll xll + ui

(c) Semi logarithm function: Semi-log function can be expressed as Logy = b0 + b1x1 + b2x2 + b3x3 + b4x4 +. . . . . . . . . bll xll + ui

(d) Double log function: (Cobb-Douglas production function). In double logarithmic equations, the regression coefficient is the elasticity of the dependent variables with


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respect to the independent variables with which the coefficient are associated. This is expressed as: Logy = In b0 + b1 In x1 + b2 In x2 + b3 x In x3 + b4 In x4 + . . . . bll In xll + ui The transformation of the function gives Y = b0 + b1x1 + b2x2 + b3x3 + b4x4 +. . . . . . . . .bll xll + ui Where: Y = Composite Index of Level of Living Standard (CILLS) x1 = Health (Unit = three point scale ranging from 1 to 3) x2 = Schools " x3 = Roads " x4 = Water " x5 = Electricity " x6 = Employment " x7 = Housing " x8 = Ownership of mobility " x9 = Electronics " x10 = Agricultural productivity " x11 = Income "

RESULTS

Relationship between the Socio-economic Indicators and Composite Index of Level of Living Standard in CBNP

In Daguma community, the result of the regression analysis as indicated in Table 1 shows that the double-log function gave the best goodness of fit out of the four functional forms tried. The result further indicated that out of the eleven (11) independent variables used in the study, only one of them (school) was significant and positively related to CILLS. The result showed that school was significant at 5% level. Health, water, employment, housing, ownership of mobility, agricultural productivity and income were not significant even though they were positively related to the CILLS. Electricity and electronics had negative signs but were not statistically significant.

Table 1: Estimate of Summary Parameters of Four Functions for Daguma community Variable Coeff. Var. F Value R2 Adjusted R2 Constant 0.30Ns

(0.62) 1.66 0.48 0.18

Health 0.18Ns (0.32)

School 0.76* (0.35)

Road -0.04Ns (0.24)

Water 0.05Ns (0.22)

Electricity -0.23Ns (0.28)

Employment 0.19NS (0.23)

Housing 0.17Ns (0.43)

Ownership of mobility 0.15Ns (0.34)

Electronics -0.16Ns (0.27)

Agricultural productivity 0.05Ns (0.34)

Income 0.31Ns


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(0.44) NB: *Significant at P ≤ 0.05%, **Significant at ≤ 0.01%, NS Not Significant and all values in parenthesis are Standard error

In Bulatura community, regression analysis (Table 2) shows that the linear function gave the best goodness of fit, out of the four functions used. The analysis showed that out of the eleven (11) independent variables used in the study, two of them (school and electronics) were statistically significant at 5% level. Health, road, water, electricity, employment, housing, electronics, agricultural productivity and income though were positively related to Index of living standard, were however not statistically significant. Ownership of mobility had negative sign, but was not statistically significant.

Table 2: Estimate of Summary Parameters of Four Functions for Bulatura Community Variable Coeff. Var. F Value R2 Adjusted R2 Constant 0.06 Ns

(0.44) 3.09 0.63 0.42

Health 0.07 Ns (0.06)

School -0.24* (0.08)

Road 0.08 Ns (0.14)

Water 0.18 Ns (0.11)

Electricity 0.24Ns (0.15)

Employment 0.14 Ns (0.13)

Housing 0.02 Ns (0.28)

Ownership of mobility -0.41 Ns (0.21)

Electronics 0.42* (0.21)

Agricultural productivity 0.10 Ns (0.18)

Income 0.15Ns (0.18)

NB: *Significant at P ≤ 0.05%, **Significant at ≤ 0.01%, NS Not Significant and all values in parenthesis are Standard error

Result of the regression analysis for Amchaka community (Table 3) shows that the Linear function produced the best goodness of fit among the four functions used. The result indicated that out of the eleven (11) independent variables used in the study, two of them (housing and electronics) were statistically significant at 1% level. Health, road, housing, ownership of mobility and agricultural productivity were positively related to CILLS but were not statistically significant. Road, water, electricity, employment had negative signs but were not statistically significant. Table 3: Estimate of Summary Parameters of Four Functions for Amchaka Community Variable Coeff. Var. F Value R2 Adjusted R2 Constant 0.15Ns

(0.56) 2.02 0.53 35.40


School 0.19Ns (0.10)

Road -0.01Ns (0.14)

Water -0.07Ns


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(0.14) Electricity -0.04Ns

(0.19)

Employment -0.13Ns (0.12)

Housing 0.73** (0.28)


Electronics -0.71** (0.27)




Result of estimate of parameters of four functions for Chingurmi community, as

indicated in Table 4 shows that the semi-log functions had the best goodness of fit out of the four functions used. The result revealed that out of the eleven (11) independent variables used in the study, seven (7) were statistically significant at 5% level and three (3) at 1% level. Health and electronic were positively related to index of living standard but not statistically significant. Electronics had negative sign but not statistically significant.

Table 4: Estimate of Summary Parameters of Four Functions for Chingurmi Community Variable Coeff. Var. F Value R2 Adjusted R2 Constant 0.43*

(0.18) 87..56 0.98 0.97

Health 0.33* (0.09)

School 0.21* (0.10)

Road 0.26** (0.05)

Water 0.13* (0.04)

Electricity 0.27** (0.04)

Employment 0.14* (0.06)


Ownership of mobility 0.25** (0.09)


Agricultural productivity 0.50* (0.11)

Income -0.22* (0.06)


Estimate of parameters of four functions were carried for Yusufari community. The

result (Table 5) shows that the double-log function produced the best goodness of fit out of


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the four functions. The result further indicated that out of the eleven (11) independent variables used for the study, road, water and electricity were statistically significant. Health, school, housing, ownership of mobility, agricultural productivity and income were positively related to index of living standard but were not statistically significant. Employment and electronics had negative signs but not statistically significant. Table 5: Estimate of Summary Parameters of Four Functions for Yusufari Community Variable Coeff. Var. F Value R2 Adjusted R2 Constant -0.24Ns

(0.31) 3.37 0.67 0.47



Road 0.29* (0.13)

Water -0.26** (0.09)

Electricity 0.26* (0.11)







NB: *Significant at P ≤ 0.05%, **Significant at ≤ 0.01%, NS Not Significant and all values in parenthesis are Standard error Relationship between the Socio-economic Indicators and Composite Index of Level of Living Standard in GCNP

Result of regression analysis of four functions for Tikobi community Table 6 showed that the semi-log function had the best goodness of fit. Out of the eleven (11) independent variables used in the study two of them (water and electronics) were statistically significant at 5% level. Health, school, electricity, employment, housing, ownership of mobility and agricultural productivity were positively related to index of living standard, but not statistically significant. Road, housing, agricultural productivity and income had negative signs but were also not statistically significant. Table 6: Estimate of Summary Parameters of Four Functions for Tikobe Community Variable Coeff. Var. F Value R2 Adjusted R2 Constant 1.56**

(0.08) 16.64 0.89 0.83

Health -0.06Ns (0.24)


Road -0.14Ns


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(0.11) Water 0.29*

(0.13)


Employment 0.04Ns (0.17)

Housing -0.08Ns (0.10)

Ownership of mobility -0.03Ns (0.23)



Income -0.25Ns (0.18)

NB: *Significant at P ≤ 0.05%, **Significant at ≤ 0.01%, NS Not Significant and all values in parenthesis are Standard error.

In Gumti community (Table 7), the regression analysis using four functions indicated that the semi-log function gave the best goodness of fit. Only water out of the eleven independent variables used for the study was statistically significant at 5% level. Health, road, employment, housing, ownership of mobility, agricultural productivity and income were positively related to index of living standard but were not statistically significant. Electricity has a negative sign but not statistically significant. Table 7: Estimate of Summary Parameters of Four Functions for Gumti Community Variable Coeff. Var. F Value R2 Adjusted R2 Constant -0.17Ns

(0.14) 15.97 0.80 0.75



Road 0.08Ns (0.07)

Water 0.06* (0.02)

Electricity -0.02Ns (0.05)




Electronics 0.14Ns (0.05)





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Result of regression analysis of four functions for Gashaka community as showed in

Table 8 indicates that the double log function gave the best goodness of fit. Nine of the independent variables out of eleven (health, school, road, water, electricity, ownership of mobility, agricultural productivity and income) were statistically significant at 1% level. Housing and electronics are positively related to index of living standard but were not statistically significant. Table 8: Estimate of Summary Parameters of Four Functions for Gashaka Community Variable Coeff. Var. F Value R2 Adjusted R2 Constant -0.66**

(0.01) Infty 1.00 1.00

Health 0.13** (0.01)

School 0.25** (0.01)

Road 0.05** (0.01)

Water 0.18** (0.01)

Electricity 0.18** (0.01)

Employment -0.03** (0.01)


Ownership of mobility 0.78** (0.01)


Agricultural productivity 0.14** (0.01)

Income -30** (0.01)


The result of regression analysis of four functions for Mayo-Salbe community in Table 9 indicated that the exponential function gave the best goodness of fit. Two of the eleven independent variables (electricity and ownership of mobility) were statistically significant at 5% level while road was statistically significant at 1% level. Health, school, employment, agricultural productivity and income were positively related to the composite index of living standard but were not statistically significant. Water, housing and electronics had negative signs but were not statistically significant. Table 9: Estimate of Summary Parameters of Four Functions for Mayo-Salbe Community Variable Coeff. Var. F Value R2 Adjusted R2 Constant -0.49*

(0.23) 55.68 0.95 0.93

Health 0.09Ns (0.05


Road 0.19**


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(0.07) Water -0.03Ns

(0.03)



Housing -0.24Ns (0.16)

Ownership of mobility 0.43* (0.16)




NB: *Significant at P ≤ 0.05%, **Significant at ≤ 0.01%, NS Not Significant and all values in parenthesis are Standard error Relationship between the Socio-economic Indicators and Composite Index of Level of Living Standard in YKNP

The result of regression analysis for Maina-Maji community using four functions produced the best goodness of fit. Housing and electronics were statistically significant at 5% level while income was significant statistically at 1% level. Health, road, water, electricity, employment, ownership of mobility and agricultural productivity were positively related to composite index of living standard but were not statistically significant. School and water had negative signs but were not significant (Table 10). Table 10: Estimate of Summary Parameters of Four Functions for Maina Maji Community Variable Coeff. Var. F Value R2 Adjusted R2 Constant -0.41**

(0.15) 11.62 0.88 0.80


School -0.06Ns (0.02)

Road 0.05Ns (0.03)

Water -0.02Ns (0.02)



Housing 0.16* (0.05)




Income 0.12** (0.04)



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The result of regression analysis using the four functions for Yelwa-Dukuri

community indicated in Table 11 that the exponential function provided the best goodness of fit. Two (housing and agricultural productivity) out of the eleven (11) independent variables were statistically significant at 1% level. Health, school, road, water, electricity, employment, ownership of mobility, electronics and income were positively related to the composite index of living standard. Table 11: Estimate of Summary Parameters of Four Functions for Yelwa-Dukuri Community Variable Coeff. Var. F Value R2 Adjusted R2 Constant -0.24Ns

(0.17) 8.67 0.84 0.74



Road 0.03Ns (0.030)

Water 0.08Ns (0.02)



Housing 0.14** (0.05)



Agricultural productivity 0.06** (0.02)



In Pali community, result of the estimated coefficient for eleven (11) independent variables using four functions showed in Table 12 that the Double log function gave the best goodness of fit. The result indicated that school, housing and agricultural productivity out of the eleven (11) independent variables used for the study were statistically significant at 5% level. Health, road, water, electricity, employment, ownership of mobility, electronics and income were positively related to composite index of living standard but were not statistically significant. Table 12: Estimate of Summary Parameters of Four Functions for Pali Community Variable Coeff. Var. F Value R2 Adjusted R2 Constant 0.15Ns

(0.18) 8.14 0.83 0.73


School 0.07* (0.07)

Road 0.03Ns (0.07)

Water 0.05Ns (0.04)


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Housing 0.37* (0.10)



Agricultural productivity 0.10* (0.05)



In Yello community, the result of regression analysis using four functions indicated in Table 13 that the Double log function provided the best goodness of fit. School, housing and income were statistically significant at 5% level while electronics was statistically significant at 1% level. Ownership of mobility and agricultural productivity were positively related to composite index of living standard, they were however not statistically significant. Health and water had negative signs but were not statistically significant. Table 13: Estimate of Summary Parameters of Four Functions for Yello Community Variable Coeff. Var. F Value R2 Adjusted R2 Constant 0.27Ns

(0.15) 14.75 0.90 0.83

Health -0.08Ns (0.10)

School 0.14* (0.06)

Road -0.05Ns (0.7)

Water 0.06Ns (0.03)



Housing 0.37* (0.08)


Electronics 0.11** (0.04)


Income 0.13* (0.05)


Estimate of coefficient for eleven (11) independent variables for Baggos community using four functions as showed in Table 14 indicates that the exponential function produced the best goodness of fit. School, road, electricity and electronics out of the eleven (11) independent variables studied were statistically significant at 5% level. Health, electricity,


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housing, ownership of mobility, agricultural productivity and income were positively related to composite index of living standard. Water and employment had negative signs but were not statistically significant. Table 14: Estimate of Summary Parameters of Four Functions for Baggos Community Variable Coeff. Var. F Value R2 Adjusted R2 Constant -0.36*

(0.08) 98.96 0.98 0.97


School 0.03* (0.01)

Road 0.08* (0.02)

Water -0.01Ns (0.02)









DISCUSSION In CBNP of Daguma community, school was the only independent variable found to

be significant and positively related to composite index of level of living standard. This implies that the major contribution of CBNP management to the community was in the area of school provision. The positive and non-significant relationship of the variables such as health, water, employment, housing, ownership of mobility, agricultural productivity and income revealed that the park management might have made some contributions in these areas, which are however not significant yet. The negative and non-significant relationship of electricity and electronics suggest that the majority of the respondents do not have any form of mobility or electricity. This finding agrees with the report of Buba (2012), which recorded insignificant economic amenities in the areas.

In Bulatura community, school and electronics were statistically significant at P ≤ 0.05 (5%). However, school had a negative and significant relationship suggesting that (1) school is a necessary function of CILLS; (2) that the preponderance of the respondents was of the opinion that the school facilities were inadequate in all respect. Electronics had a positive and significant relationship indicating a positive influence of the park on the income of the respondents, which made it possible for them to acquire electronic gadgets. All other independent variables except ownership of mobility had positive sign but not significant, revealing that their incidence in the community has not reached the expected level. Ownership of mobility had negative sign and no significant relationship implying that majority of the respondents may not have any form of mobility.


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Result of the regression analysis for Amchaka community showed that only housing (0.73) and electronics (-0.71) had significant relationship among the independent variables. Housing was positive and significant at 5%. This suggests that housing is a function of CILLS and that the Park had made a significant contribution by providing houses to the community. Electronics had a negative sign and significant relationship at 5% suggesting that although it is a function of CILLS the majority of the respondent may not own any electronic gadget. Other independent variables had either positive or negative signs with no significant relationship. This suggest that little or no contribution had been made by the park management to the community in these areas, which include health, school, road, water, electricity, employment, ownership of mobility, agricultural productivity and income.

In Chingurmi community, six (6) independent variables were statistically significant at 5% level. These include health, water, employment, agricultural productivity and income while three (3) were significant at 1% level. These include road, electricity and ownership of mobility. This indicated that the nine independent variables above were provided at a reasonable level in the community by the park management. The result also revealed that the impact of the park management in the area of housing and electronics is yet to be felt in the community.

Results of the regression analysis on data collected from Yusufari community indicated that only water as an independent variable had significant relationship but with a negative sign. This suggests that though water is important in determining CILLS of the community, majority of the respondents were possibly of the opinion that no provisions were made for water. The result further showed that no significant provision has been made in all other independent variables. This is similar to the publication of Marguba (2002).

In Tikobi community of GCNP, the result showed that water (0.29) and electronics (0.43) were statistically significant at 5% level. Both had positive sign. This implies that the park management impact on socio-economic indicators was highest in the area of water (drilling of bore holes) in line with the report of Saidu (2010). All the other independent variables were not significant and had either positive or negative signs. The implication is that those with positive signs and not significant indicated that not much has been done in those areas while those with negative sign suggests that nothing perhaps has been done in those areas.

The result of the study in Gumti community indicated that only water (drilling of bore-holes) was statistically significant at 5% level and had positive sign. This implies that the park management contribution to the socio-economic well-being of the people in the community is mainly in the area of water provision through drilling of bore-holes.

In Gashaka community, the result revealed that health (0.13), school (0.25), road (0.05), water (0.18), ownership of mobility (0.78) and agricultural productivity (0.14) had positive sign and were statistically significant at 1% level. The result suggests that the park management had made significant impact in the provision of the above socio-economic indicators. The result further revealed that employment (-0.03) and income (-0.30) had negative signs but statistically significant. The result indicated that both employment and income are functions of CILLS, it further reveals that the preponderance of the respondents fall below the poor category group as reported by Buba (2012).

Result of the regression analysis for Mayo-Salbe community indicated that electricity (0.44) and ownership of mobility (0.43) were statistically significant at 5% level, while that of road were statistically significant at 1% level. The implication of the results is similar to those discussed under Gashaka community for health, school and road.

In Maina-Maji community of YKNP, the result revealed that housing (0.16) and electronics (0.06) were statistically significant at 5% level, while income (0.12) was significant at 1% level. The result suggests that while the park had made positive impact on


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housing and electronics, greater impact was made in the upliftment of the income of the respondents.

Result of the study in Yelwa-Dukuri community indicated that housing (0.14) and agricultural productivity (0.06) were positive and statistically significant at 1% level. The result suggests that the park management had made outstanding impact on the provision of housing and agricultural productivity in the community.

The study in Pali community revealed that school (0.07), housing (0.37), and agricultural productivity (0.01) were statistically significant at 5% level and had positive signs. The implication of the result is that reasonable contributions had been made by the management of the park in the above areas.

In Yello community, the result indicated that school (0.14), housing (0.37), and income (0.13) had positive signs and statistically significant at 5% level while electronics (0.11) was statistically significant at 1% level and also has a positive sign. The implication of the result is similar to that of Pale community.

The result of the study for Baggos community revealed that school (0.03), road (0.08), electricity (0.12) and electronics (0.04) were statistically significant at 5% level and had positive signs. The result suggests that the four socio-economic indicators are functions of CILLS and that the management of the park had impacted positively on the well-being of the people through its provisions of the four socio-economic indicators (school, road, electricity and electronics). This finding corroborates the report of Marguba (2002) and Akosim et al. (2010), which positively appraised Nigeria national parks.

CONCLUSION

The provision of socio-economic facilities in the communities across the three support zones was inconsistent. Some socio-economic indicators were significantly positive, while many others were not significant across the various communities. This trend may not impact positively on local dwellers socio-economic well-being. More socio-economic facilities should therefore be provided to spread evenly across all the support zones communities.

REFERENCES

Akosim, C., Yaduma, Z. B., Gawaisa, S. G. and Mamman, G. S. (2007). Evaluation of the Relative Importance of Five Principal Forest Reserves for Biodiversity Conservation in Adamawa State, Nigeria, p.56.

Akosim, C., Bode, A. S., Kwaga, B. T. and Dishan, E. E. (2010). Perception and Involvement of Neighboring Communities of Kainji Lake National Parks Towards the Parks Conservation Programme. Journal of Research in Forestry, Wildlife and Environment, 2 (1&2).

Buba, Z. V. (2012). Analysis of Socio-Economic Benefits of North-East Nigeria National Parks to the Support Zones Communities. Unpublished Ph.D Thesis, Modibbo Adama University of Technology, Yola, 154pp.

Gbadegesin, A., Olopoenia, R. and Jerome, A. (2005). Statistics for the Social Sciences. Ibadan: University Press Ibadan. pp. 1-17.

Marguba, B. (2002). Nigeria National Parks their Significance and Potentials to the Nation, in the Magazine of the Nigeria National Parks 1(1): 7-10.

Ogunleye, O. A. (2002). An Introduction to Research Method in Education and Social Sciences. Ibadan: Sunshine International Publications (Nig.) Ltd. pp. 58-78.

Ogwumike, O. F., Ajayi, D. and Abanihe, U. (2005). Data Collection. In: Statistics for the Social Sciences. Ibadan: Ibadan University Press, pp. 19-23.


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Saidu, B. A. (2010). Conservation of Wildlife Resources in Relation to Sustainable Rural Development in Neighbouring Communities of Kainji Lake National Park. B. Tech. Thesis, Federal University of Technology, Yola, p.21.

Tim, P. (2009). Regeneration and Environment: Socio-economic Wellbeing of Local Communities. Available at mhtml//www.wlga.clilc/nationalparks/ (Accessed 8th January, 2009).


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SIZE COMPOSITION AND GROWTH PATTERN OF BY-CATCH MAR INE CRABS Callinectes amnicola OFF THE ATLANTIC COAST, SOUTHEAST NIGERIA

James Philip Udoh

Department of Fisheries and Aquatic Environmental Management, University of Uyo, Akwa Ibom, Nigeria; [email protected], [email protected]

ABSTRACT

A total of 352 specimens of Callinectes amnicola from off-shore marine environment landed at Oron along the Cross River estuary were sampled from February to November and analysed for size composition and growth pattern. Carapace length-weight relationship indicated negative allometry in pooled populations; while males displayed positive allometry. Crab lengths and condition factor displayed bimodal trend with the minor and major peaks in March and October, respectively. Two growth patterns were observed: juvenile recruitment at 1.5-2.5 cm carapace length (CL) in February to March and adult migration at about 5.5 cm CL in May/June for further growth at sea till they attain sexual maturity and spawn in November/December. Sex ratio between male and female marine C. amnicola showed parity. Intersexual variation indicated homogenous distribution in crab lengths; while females were significantly heavier than males. Crabs showed high tendency (> 70%) towards right-handedness. Crabs of three colour morphotypes (brown, olive brown and olive green) were encountered; with the dominance of crabs of the green morphotype (60-80%); indicative of high environmental variability. Comparison of crab sizes indicated that crabs of the Qua Iboe River estuary are heavier and longer than crabs of the same species in adjoining estuaries and from off-shore marine environment. Regionally, C. amnicola crabs exploited in the Lagos area in southwest Nigeria are bigger than those from southeast Nigeria. Interpopulation differences observed might be attributable to environmental variabilities such as salinity and bottom soil characteristics. Hence the C. amnicola in these areas are of the same stock and could be subjected to similar management and conservation regulations. KEYWORDS : Allometric equation, conservation, management of blue crab, morphological variation.

INTRODUCTION Callinectes amnicola (De Rochebrune, 1883) is one of the most common swimming (portunid) crabs found in the brackish wetland and lagoons of West Africa (William, 1974; Fischer et al., 1981), where they are cherished and commonly consumed. Crabs have a high food value such as high ash, mineral and crude fibre content (Oduro et al., 2001). Udofia et al. (2013) noted that marine crabs (Callinectes amnicola) in southeast Nigeria are particularly rich in protein (whole crab meat: 60-48%; cheliped: 35-23%; crab legs: 39-45%), higher in males than females, respectively. Thus, consumption of fish and shellfish which form a substantial proportion of the diet of coastal communities, contribute significant and positive impact on protein quality by complementing the limiting amino acids in vegetable-based diets.

Crabs have a great diversity, wide distribution and inhabit muddy bottoms in mangrove areas and river mouths (Defelice et al., 2001) and form an important link of transferring energy between benthic and pelagic food chains within the estuarine system where they serve as food for many fishes and shellfishes (Warner, 1977; Baird and Ulanowicz, 1993; Davis, 2009). Crabs are non-target species in artisanal and trawl fisheries in West Africa and are common component of the invertebrate fauna. Crab fisheries in Nigeria are mostly locally exploited by women and children (<16 years) using traps made of basket, bicycle wheels and clay pots (Akin – Oriola et al., 2005). There is a growing interest with specialized groups of fish mongers and women who serve as the major intermediaries in

Udoh, J. P. (2017). Size Composition and Growth Pattern of By-Catch Marine Crabs Callinectes amnicola off the Atlantic Coast, Southeast Nigeria. Journal of Environment and Sustainable Development, 3(1): 71-88.


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the booming market for by-catch crabs from off-shore trawlers; most of which make quick sales on landing at jetties and beaches. The new market complements and probably, stimulates the inshore crab artisanal fishery.

Aspects of the biology of C. amnicola in Nigeria have been reported for Lagos lagoon (Fagade, 1969; Fagade and Olaniyan, 1973; Emmanuel, 2009), New Calabar River (Chindah et al., 2000), Badagry lagoon (Lawal – Are and Kusemiju, 2002), Warri River (Arimoro and Idoro, 2007; Imo River, IRE (Udoh et al., 2009), Cross River (Udoh et al., 2011) and Qua Iboe River estuaries, QIRE (Udoh and Nlewadim, 2011 a,b) in Nigeria. The C. amnicola crabs in southeast Nigeria exhibit brown, olive green, olive brown and orange green colour morphotypes and three moult stages. Generally the overall sex ratio of the crab populations in the IRE and QIRE slightly favour males and females (1:0.89 and 1:1.94, respectively), and comprise largely adult crabs (82 - 92%), in intermoult stage (86 - 87%); with a tendency towards right-handedness (77 - 80%). The crabs were 109.85 ± 1.36 and 126.89 ± 49.45 g, 58.83 ± 2.78 and 62.48 ± 7.81 carapace length (mm), and 117.00 ± 5.65 and 124.50 ± 17.50 carapace width (mm), respectively; with the green morphotypes being larger in proportion and significantly longer and heavier than other crab morphotypes (Nlewadim et al., 2009; Udoh and Nlewadim, 2011a). Male crabs were also observed to be heavier and longer than female crabs (p < 0.05).

Ovigerous females with matured gonads (stages IV and V) constituted 10.95% of the crab population while gonadosomatic index, % were 2.72 ± 0.14 (0.00 – 49.55) and 6.25 ± 0.65 (0.00 – 79.54) and hepatosomatic index, % - 4.61 ± 0.35 (0.00 – 156.27) and 4.91 ± 0.37 0.00 - 82.39), for adult males and females, respectively in the IRE (Nlewadim et al. 2009). Udoh and Nlewadim (2011b) established that cheliped palm depth serves as a secondary sexual character being the character which affords high discriminatory values between crab sexes. However, Udoh et al. (2011) observed a preponderance of females over males (1:3.05) while females were significantly heavier but not significantly longer, than males, in the Cross River estuary. Furthermore, Udoh and Jimmy (2015) described C. amnicola primarily as carnivores, with a tendency for carnivore-detritivore in IRE to omnivore-carnivore in QIRE, relative to abundance of food/prey items in its environment. The above reports suggest that interpopulation variabilities of C. amnicola in IRE and QIRE estuaries and other locations might just be phenotypic in nature and attributable to salinity differences. Udoh (2016) also described the primary dietaries and food preferences of the marine C. amnicola to include mud (12.20%), sand grains (13.17%) and fine particulate organic matter, FPOM (10.30%), coarse particulate organic matter, CPOM (9.08%), plant materials (23.20%) and occasional consumption of crustaceans in large quantities (20.25%). The secondary diet items are fin-fishes (9.50%) and protozoa (1.79%), with incidental inclusion of insects (0.51%); giving a calculated trophic value of 2.8±0.34. Results from Udoh and Jimmy (2015) and Udoh (2016) suggest that C. amnicola in the estuarine and marine habitats in southeastern Nigeria share similar dietaries and exhibit omnivory with strong tendencies for detritivory and carnivory, in response to intra-specific competition and food availability.

Other reported studies on C. amnicola deal with their taxonomy and distribution (Powell, 1983, 1985; Jonathan and Powell 1989), nutritional composition (Fineman-kalio 1987; Idoniboye-Obu and Ayinla 1991; Alfred-Okiya 2000; Oduro et al., 2001; Udofia et al., 2013), ecology (Okafor 1988; Lawal-Are and Kusemiju, 2000; Arimoro and Idoro, 2007), Morphometrics (Udoh et al., 2011; Akin-Oriola et al.,2005), and food and feeding (Chinda et al., 2000; Lawal-Are and Kusemiju, 2000; Arimoro and Idoro, 2007).

Large gaps still exist in our knowledge of population biology of C. amnicola including population characteristics and reproductive ecology of estuarine and off-shore marine populations of the species. Thus, the aim of this research is to examine the size composition, length–weight relationships and growth patterns of C. amnicola caught as by-catch of trawlers


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on the high sea along the Atlantic coast and landed at the Oron beach along the Cross River, Nigeria and to compare values with their estuarine counterparts in the southeast Nigeria.

MATERIALS AND METHOD Crab samples for this study (n = 352) were purchased bi-monthly from fishmongers at Oron beach in the Cross River Estuary, Nigeria (Fig. 1), between February and November, 2011. The crabs were caught by trawlers in the marine waters in the Atlantic Ocean and landed at Oron beach, among other beaches. The climate of the study area comprise two seasons: the wet season (February- August) and dry season (September-February). Specimens were fixed in 10% formalin after collection prior to analysis. Schneider (1992) facilitated crab identification. Sex determination and developmental stages were based on morphology of abdomen: narrow in males and broad in females. The T-shaped abdomen readily distinguished both immature and mature stages of crab (Nlewadim et al., 2009; Udoh and Nlewadim, 2011a). The modal length of the youngest brood in the catch samples (i.e., 4.4 cm CL) was used as the cut-off length in determining the index of recruitment (% juveniles) as against crab abdominal measurement (Udoh, 2016).

Fig. 1. The coastal zone of southeastern Nigeria showing sampling point (white dot) along the Cross River estuary (Inset: Map of Nigeria showing the study area); cropped from Nigeria Satellite Atlas, NigSat-1 (Udoh, 2016)

Carapace length (CL mm) and carapace width (CW mm) were measured to 0.1 mm, using sliding jaw vernier calipers, and body total weights (TW) taken to the nearest 1.0 g using electronic balance. Condition factor was determined as: K = W.100/TL3; where, W = body weight, TL3 = cube of total length (Udoh et al., 2009). Moult sign was also noted in each crab based on the appearance of the exoskeleton (van Engle, 1958; Milikin and William, 1984). The percentage occurrence of heterochely or handedness (position of the major chelae) was observed in both sexes. Abdominal measurements such as male abdominal length and width and female abdominal length and female 4th and 6th abdominal width were taken as previously described (Udoh and Nlewadim, 2011b; Udoh et al., 2011). Length- weight relationship was expressed as W =aLb (Bagenal and Tesch, 1978) where W is total body weight of crab in grammes, and L is carapace length (cm) or carapace width (cm).


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RESULTS

Population characteristics, composition, size and abundance of marine C. amnicola crabs off Cross River estuary, Oron C. amnicola occurred throughout the study period; a total of 352 crabs were collected comprising 179 males and 173 females giving a sex ratio of 1:0.97. Generally the distribution conforms to unity (1:1), with a preponderance of females particularly in June through November. The only deviation from unity was recorded in April when males significantly outnumbered females (χ2 = 5.7692; p<0.05). The highest and least occurrences of marine crabs were recorded in the months of February and June, respectively. The monthly variation in sex ratio is shown in Table 1.

Crabs sampled exhibited a high composition of adults (46.15 to 100%), averaging 70.16% (100% of crabs sampled in the month of June were adults (Table 1). The crabs were 2.20 to 7.70 cm CL (51.77 ± 0.28), 1.17 to 33.25 cm CW (107.82 ± 0.56) in length and 5.32 – 577.2 g (79.95 ± 49.05) in weight. The class size distributions were not significantly different between both sexes (Fig. 2); displaying a bimodal distribution with medium and larger-sized groups (5.0 and 7.0 cm CL, 9.5 and 12.5 cm CW; 25-45 and 80 g). Males peaked at broad ranges (4.0-5.5 and 6.0-7.0 cm CL; 9.5-10.0 and 12.5-14.5 cm CW and 25-45 and 95-105 g) while females peaked at narrow ranges (4.5-5.0 and 6.0-7.0 cm CL; 8.5-9.5 and 12.0-12.5 cm CW; 25-35 and 85-95 g). Generally, crabs whose lengths are longer than the mean, 5.5 cm CL (Fig. 3a) populate the marine fishery. Figure 3 also shows the population structure by sex and adult/juvenile recruitment.

There was intersexual variation in total weight, carapace length and carapace width of crabs. Sexual dimorphism was expressed in the mean total weights for male and female crabs: 72.41 g (46.67-123.06 g) and 84.97 g (32.89-105.21 g), respectively, indicating that female crabs were12.55 g heavier than their male counterpart (p < 0.05). On a temporal scale, sexual dimorphism was in favour of females in the dry season months of November to March; and in favour of males in the wet season, June to October (Fig. 3c). The mean carapace length and carapace width indicate that female crabs were longer (about 1.0 cm CL and 4.0 cm CW) than their male counterparts (p > 0.05); with corresponding means of 5.3 and 5.2 cm CL, 10.8 and 10.4 cm CW, respectively (Table 1, Fig. 2). The largest total weight for the female (577.2 g), having 11.57 and 6.17 cm carapace width and length, respectively, was recorded in the month of September. The largest male (198.6l g) having 14.68 cm CW and 7.04 cm CL was recorded in the month of August. The smallest total weight in the male (5.32 g), had 2.64 cm CL and 5.02 cm CW and was recorded in the month of April while the smallest female (6.18 g) recorded 2.2 cm CL and 5.03 cm CW, in the month of March. The monthly variation in condition factor of C. amnicola did not show any temporal significant difference with month, p > 0.05 (Fig. 3d) or with crab size (p > 0.05). Mean condition factor peaked in March and October, steeped in September and remained stable the remaining period of the study, irrespective of sex, but highest for females in November (p >0.05). Crabs exhibited heterochely with a tendency for right-handedness in both sexes (Table 1; Fig. 4). Intersexual variation in heterochely was non-significant (χ2 = 0.11146; p = 0.7385).

Table 1: Demographic traits of marine C. amnicola crabs off Cross River estuary, Nigeria

Traits Feb Mar Apr May June Jul Aug Sept Oct Nov Total

Carapace length (cm) 4.95 5.52 4.73 5.91 6.26 5.5 5.81 5.6 4.20 4.30 5.18 Carapace width (cm) 9.37 10.6 9.14 12.24 12.40 10. 10.7 11. 10.40 10.80 10.78 Mean total weight (g) 41.7 86.5 46.9 86.80 92.77 56. 74.4 41. 109.8 77.03 79.95 % Female 39.6 55.5 30.7 44.44 61.54 56. 58.0 56. 56.67 43.33 50.90 % Males 60.3 44.4 69.2 55.56 38.46 43. 41.9 43. 43.33 56.67 49.10 Sex ratio 1:0.6 1.12 1.0.4 1:0.8 1:1.6 1:1. 1:1. 1:1. 1:0.8 1:1.3 1:0.9Heterochely


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- % Crabs with bigger left chelae 26.0 50.0 35.0 21.74 0.00 0.0 22.2 35. nd nd 24.44 - % Crabs with bigger right chelae73.9 50.0 65.0 78.26 100.0 100 77.7 65. nd nd 75.56 % Crabs with one chela cut off 4.17 8.33 16.1 28.13 28.57 50. 25.0 33. nd nd 24.21

% Immature 0.00 0.00 7.70 2.78 0.00 0.0 6.45 3.3 10.00 10.00 4.03 % Pre-pubertal 45.2 26.6 30.7 25.00 0.00 28. 1. 3.3 10.10 13.40 20.3% Pubertal 3.77 2.22 15.3 8.33 0.00 3.1 6.13 0.0 1.67 1.67 4.23 % Adult 47.1 71.1 46.1 63.89 100 68. 74.1 70. 63.33 60.00 66.4% Brown 3.77 15.5 2.56 2.56 0.00 0.0 0.00 3.2 33.33 10.00 7.10 % Olive brown 20.7 22.2 19.9 16.67 23.08 9.3 12.9 6.6 16.67 36.67 18.5% Olive green 71.7 62.2 76.9 83.33 76.92 90. 87.1 93. 53.3 31.1 72.6% Early pre moult 64.1 33.3 64.1 13.89 0.00 43. 22.5 3.3 nd nd 30.6% Inter moult 28.3 64.4 35.7 83.33 100 56. 74.1 96. nd nd 67.3% Post moult 3.77 2.22 0.00 2.78 0.00 0.0 6.45 0.0 nd nd 1.90 Male abdominal length, cm 3.51 3.71 3.35 4.17 4.40 3.7 3.94 3.7 2.25 3.50 3.63 Male abdominal width, cm 3.09 3.37 3.08 3.67 3.87 3.2 3.30 3.2 2.11 2.11 3.11 Female abdominal width 4, cm 2.65 3.46 3.14 3.74 3.88 3.5 3.80 3.2 2.25 3.5 3.31 Female abdominal width 6, cm 3.33 4.08 3.47 3.90 4.17 3.8 4.06 3.8 2.31 3.6 3.66 Female abdominal length, cm 3.49 3.79 3.44 3.88 3.90 3.5 3.94 1.2 2.02 2.29 3.15

nd = no data *Significant difference at 5% level

Moulting, colour morphotype, developmental stages and abdominal measurements of marine blue crabs off Cross River Estuary, Nigeria Results also showed the proportion of crabs sampled by sex, moult and developmental stage (Table 1). Crabs of early premoult, intermoult, and post moult were encountered being 30.64%, 67.36% and 1.902% in proportion, respectively (Table 1). However, at the terminal or pubertal moult, the final ecdysis and onset maturity, the mature female abdomen becomes broad and rounded. Crabs encountered were of brown, olive brown and olive green colour morphotypes in proportions of olive green crabs being the highest averaging 72.66% followed by olive brown crabs 18.45%, respectively (Fig. 5). Pre-pubertal crabs encountered occurred as post moult. Adult crabs mostly occurred as intermoult and early premoult but greater in male than female crabs of immature (4.03%), prepubertal (20.30%), pubertal (4.23%) and adult (66.46%) were encountered during the survey. Abdominal measurements in both males and females showed increasing trend from February to September, lower in male abdominal measurements but higher in females (Table 1). Fig. 6 shows the mean lengths and weights of crabs based on their demographic traits such as colour, and moulting and developmental stages. The Fig. 6 indicates that intermoult crabs (79.32 g) were (significantly) heavier than early premoult crabs (27.48 g; p < 0.05) and post moult distribution of marine crabs off Cross River length and weight classes of marine C. amnicolaestuary, Nigeria crabs off Cross River estuary, Nigeria crabs (76.05 g; p > 0.05). Also intermoult (5.76 cm CL, 11.45 cm CW) and post moult crabs (5.73 cm CL, 12.12 cm CW) were homogeneous in carapace lengths and widths but significantly longer (p < 0.05) than early premoult crabs (4.27 cm CL, 8.21 cm CW). The Fig. 6 also indicates that adult post moult brown crabs recorded the highest mean length and weight, about 25.79 g heavier and 1.50 cm CL longer than their closest rival, the adult intermoult brown crabs. This was followed by adult intermoult olive green crabs. The least mean length was recorded among immature male postmoult olive green crabs.


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Fig. 2: Mean carapace length, width and weight Fig. 3 Monthly distribution of condition factor,

Length- Weight Relationship

The scattered plot of relationship between length and weight is shown in Fig. 7. The overall carapace width/length–weight values for male, female and combined sexes are given as Y = a + bX. In this study:

Male: Log TW = 3.235 + 1.998 Log CW; Log TW = 1.793+ 1.870 Log CL

Female: Log TW = 2.783 + 2.105 Log CW; Log TW = 1.835 + 1.881 Log CL

Combined sexes: Log TW = 2.988 + 2.055 Log CW; Log TW = 1.813 + 1.876 Log CL

.


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Fig. 7: Length-weight Relationship of marine C. amnicola off southeast coast of Nigeria

Fig. 4. Heterochely in marine C. amnicola crabs off Cross River estuary, Nigeria indicates tendency towards right-handedness in both sexes

Fig. 5. Samples of Callinectes amnicola (a), female (b), and male (c), indicating brown (BR) and olive brown (OB) colour morphotypes

Fig. 6. Length and weight profile of marine C. amnicola crabs off Cross River estuary, Nigeria by colour morphotype, and moult and development stages Table 2: Regression analyses of carapace length/width with weight of marine C. amnicola crabs off Cross River estuary at Oron, Nigeria


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Month Sex N Carapace width–weight relationship Carapace length–weight relationship a b r r2.100 tb a b r r2.100 tb

Feb ♂ 32 2.171 2.514na 0.828 68.59 2.29* 1.758 1.929na 0.845 71.38 3.70** ♀ 21 2.915 2.178na 0.843 71.09 2.67* 1.748 2.014na 0.833 69.34 2.83* ♀♂ 53 2.538 2.321na 0.818 66.84 3.84** 1.827 1.909na 0.831 69.05 4.73**

Mar ♂ 20 3.402 1.973na 0.956 91.38 4.58** 1.612 2.034na 0.942 88.65 3.98** ♀ 25 2.719 2.248na 0.960 92.19 4.73** 1.409 2.230na 0.970 94.03 5.43** ♀♂ 45 2.903 2.162na 0.957 91.51 6.60** 1.467 2.164na 0.961 92.28 6.88**

Apr ♂ 27 3.204 1.873na 0.950 90.20 5.17** 1.641 1.909na 0.940 88.31 4.77** ♀ 12 1.212 2.518ia 0.928 86.12 1.768ns 1.212 2.320ia 0.888 78.90 1.93 ns ♀♂ 39 3.043 1.957na 0.927 85.90 5.34** 1.585 1.957na 0.927 85.90 5.32**

May ♂ 20 2.709 2.144na 0.924 85.40 3.41* 1.597 1.990na 0.919 84.41 3.53** ♀ 16 2.136 2.548na 0.613 37.62 1.42 ns 1.671 1.949na 0.939 88.20 3.53** ♀♂ 36 2.591 2.241na 0.726 52.76 3.11** 1.625 1.975na 0.925 85.59 5.03**

Jun ♂ 10 2.332 2.261na 0.911 82.90 1.97* 1.767 1.846na 0.871 75.95 2.03* ♀ 16 4.491 1.712na 0.617 38.06 2.32* 3.113 1.453na 0.485 23.56 2.21* ♀♂ 26 4.762 1.634na 0.697 48.60 2.86* 3.290 1.391na 0.573 32.78 2.41*

Jul ♂ 14 1.079 3.654pa 0.694 48.23 -2.55* 2.190 1.722na 0.904 81.75 2.71* ♀ 18 3.635 1.878na 0.918 84.35 3.38** 1.969 1.839na 0.909 82.55 3.24** ♀♂ 32 2.242 2.440na 0.688 47.32 2.38* 2.051 1.793na 0.906 82.04 4.37**

Aug ♂ 13 2.364 2.237na 0.960 92.17 3.29** 1.801 1.864na 0.924 85.45 2.89* ♀ 18 2.501 2.237na 0.717 51.38 2.14* 1.735 1.912na 0.724 52.46 2.45* ♀♂ 31 2.369 2.275na 0.843 71.10 3.13** 1.771 1.887na 0.831 69.00 3.64**

Sept ♂ 13 4.689 1.559na

na 0.705 49.74 1.84** 2.766 1.444ia 0.463 21.44 2.01 ns

♀ 17 7.442 1.236na

na 0.396 15.71 1.73* 3.538 1.286ia 0.515 26.57 1.64 ns

♀♂ 30 6.340 1.338na

na na na 0.509 25.94 2.54* 3.242 1.338na 0.476 22.70 2.66*

Total ♂ 149 2.783 2.105na 0.841 70.77 7.711 1.793 1.870na 0.885 78.39 7.87 ♀ 143 3.235 1.998na 0.822 67.65 7.646 1.835 1.881na 0.866 74.92 8.41 ♀♂ 292 2.988 2.055na 0.828 68.51 10.837 1.813 1.876na 0.874 76.33 12.30

♀ = female ♂= male ♀♂= both *Significant difference at 5% level **Significant difference at 1% level

ns No significant difference at 5% level na negative allometry pa positive allometry ia isometric allometry

Fig. 8: Mean distribution of regression co-efficient “b” by sex of marine crabs off Cross River estuary, Nigeria

The length - weight relationships for males, females and combine sexes of C. amnicola were generally low, 1.3 to 2.4, less than 3 (Table 2) indicating that the crabs exhibited negative allometric growth. The correlation co-efficient r was 0.885, with a coefficient of


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determination, r2, of 65-80% showing a high positive correlation between carapace length/width and total weight in the crab species. The mean distribution of regression co-efficient “b” did not show intersexual variation (Fig. 8) while calculations with carapace width yielded better “b” values in the marine crabs.

DISCUSSION C. amnicola occurred throughout the sampling period. It is a delicacy that is highly patronized by low and high income class groups in the area and is mostly sold fresh. The morphology of marine C. amnicola crabs sampled was similar to those made of estuarine species in southwest, east and southeast of Nigeria (Lawal-Are, 2003; Arimoro and Idoro, 2007; Nlewadim et al., 2009; Abowei and George, 2010; Nwosu, 2010). C. pallidus and C. marginatus were not encountered during the sampling period may be due to their rarity or low abundance in the fishery area and/or gear inefficiency. Fischer et al. (1981) confirm their co-occurrence with C. amnicola in the fishery area. The length frequency distribution in this study was mainly bimodal with medium and larger-sized groups (Fig. 2). Similar bimodal size distributions were reported for C. amnicola in Imo River Estuary (Nlewadim et al., 2009), Qua Iboe River Estuary (Udoh and Nlewadim, 2011a) and Cross River Estuary (Udoh et al., 2011) in the southeast coast of Nigeria. Unimodal size distribution in crabs was reported by Lawal-Are and Kusemiju (2000) with dominance of medium-size crabs in Badagry lagoon (Lagos, Nigeria) and Kwei (1978) in Mukwe and Sakumo lagoons in Ghana. The absence of smaller-sized crabs in this study does not necessarily suggest that sampling gear captured large crabs and fish allowing the escape of small crabs; because usually smaller crabs are discarded at sea by the fishers while only marketable sizes are landed. This explains the catch comprising mostly adult crabs. Previous studies in the area also indicated a high composition (80 - 90%) of adults (Nlewadim et al., 2009; Udoh et al., 2009, 2011; Udoh and Nlewadim, 2011b). Generally, most of the crabs sampled were longer than the mean length (Fig. 3a, b) with potential for reproductive investment. Wilcox (2004) demonstrated that tagged hatchery crabs attained almost 12.5 cm carapace width at the age of 6 months. At this size, the crab is approaching maturity and about to contribute reproductively to the fishery.

The length-weight relationship and growth pattern of the crabs were estimated in this study and compared with others as follows:

Male: Log W = −0.92 + 3.52 Log CL (southwest-Lagos lagoon; Akin-Oriola et. al., 2005; C. pallidus) Log W = −23.32 + 3.4050 Log CL (southeast -Warri River; Arimoro and Idoro, 2007) Log TW = −5.83 + 2.840 Log CL (southeast- Imo River estuary; Udoh and Nlewadim, 2011b) Log TW = −6.60 + 3.17 Log CL (southeast- Qua Iboe River estuary; Udoh Nlewadim, 2011 b) Log TW = −2.04 + 2.18 Log CL (southeast- Cross River estuary; Udoh et al., 2011) Log TW = 1.793+ 1.870 Log CL (southeast- marine; this study) Female: Log W = 0.51 +2.53 Log CL (southwest-Lagos lagoon; Akin-Oriola et al., 2005; C. pallidus) Log W = Log 53.3861 + 2.2852 Log CL (southeast -Warri River; Arimoro and Idoro, 2007) Log TW = 2.600 + 1.65 Log CL (southeast-Imo River estuary; Udoh and Nlewadim, 2011b) Log TW = -4.040 + 2.17 Log CL (southeast-Qua Iboe River estuary; Udoh and Nlewadim, 2011b) Log TW = - 2.213 + 2.33 Log CL (southeast- Cross River estuary; Udoh et al., 2011) Log TW = 1.835 + 1.881 Log CL (southeast- marine; this study) Combined Sexes: Log W = − 0.18 + 3.01 Log CL (southwest-Lagos lagoon; Akin-Oriola et al., 2005; C. pallidus)

Log W = Log 52.3483 + 2.4137 Log CL (southeast -Warri River; Arimoro and Idoro, 2007) Log TW = −4.820 + 2.47 Log CL (southeast- Imo River estuary; Udoh and Nlewadim, 2011b) Log TW = −5.503 + 2.711 Log CL (southeast- Qua Iboe River estuary; Udoh and Nlewadim, 2011b) Log TW = −2.305 + 2.37 Log CL (southeast- Cross River estuary; Udoh et al., 2011) Log TW = 1.813 + 1.876 Log CL (southeast- marine; this study)


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The logarithmic carapace width – weight relationship of C. amnicola are as follows: Male: Log TW = 3.235 + 1.998 Log CW (southeast- marine; this study) Log TW = −3.84695 + 2.7806 Log CW (southeast-Cross River estuary; Udoh et al., 2011) Female: Log TW = 2.783 + 2.105 Log CW (southeast- marine; this study) Log TW = −1.509 + 1.6476 Log CW (southeast- Cross River estuary; Udoh et al., 2011) Combined sexes: Log TW = 2.988 + 2.055 Log CW (southeast- marine; this study) Log TW = −2.593 + 2.1688 Log CW (southeast- Cross River estuary; Udoh et al., 2011)

From the above comparisons, the carapace length-weight relationships of C. amnicola are generally negative allometry in females and pooled populations, being below three, that is, as the carapace length increases, the plumpness reduces or flattens out dorso-ventrally; while males display positive allometry. Fig. 2 indicates that increasing carapace length is accompanied by increasing width and reducing weight. Akin-Oriola et al. (2005) recorded positive allometric growth in Cardiosioma armatum (i.e., body proportion change with growth) and isometric growth in Callinecties pallidus, i.e., the body proportions do not change as the organism grows.

Figure 3 suggests two growth patterns: juvenile recruitment and adult migration. The figure shows that larger-sized crabs enter the marine fishery in large numbers at about 5.5 cm CL in May/June and grow to 6.5-7.0 cm CL in August/September and continue further growth at sea till they spawn in November/December; typically several weeks to three months after mating (Hines, 2003). Usually, the inseminated females initiate brood incubation at higher salinities, and hatch their eggs at the mouth of the estuary or out at sea onto the continental shelf. Smaller crabs are recruited into the marine fishery at 1.5-2.5 cm CL in February to March when the sea expectedly experiences lower salinities and food resources appear to be rich; the recruits grow up to 5.0 cm CL in May/June in highly saline sea water and till they mate and are inseminated to produce eggs and thereafter, disperse larvae out at sea. Wilcox (2004) notes that mating occurs primarily in relatively low-salinity waters, in areas where female crabs normally go to molt and from May through October.

The deviation in sex ratio between males and females of C. amnicola are linked to several causative factors. Such as spatial preference of females for deeper waters, efficiency of fishing gear, selection pressure from fishers and consumer preferences for males, since males are larger and more valued in the market (Archambault et al., 1990; Murphy et al., 2001; Mendonca et al, 2010) and schooling by sex (Devi, 1985). Studies show that crab species usually present differentiated distribution according to the environmental conditions, leading to male dominance in much lower salinities (like in Imo river estuary; Nlewadim et. al., 2009) while females are present in higher numbers in more saline environment (like in this study and Qua Iboe River estuary, Nigeria as reported in Udoh et al. 2011), since they migrate to open sea for spawning (Archambault et al., 1990; Murphy et al., 2001; Mendoca et al., 2010). Several authors have recorded crab sex ratios that were male-biased (Snowden et al., 1991; Sumpton et al., 1994) and female-biased (Devi, 1985; White, 1999, Lawal-Are and Kusemiju, 2000; Wakefield, 2002, Meye et al., 2003; Akin-Oriola et al; 2005; Arimoro and Idoro, 2007; Lawal –Are and Bilewu, 2009; Abowei and George, 2010). The sex ratios obtained in this study are therefore normal for the marine environment.

Intersexual variation in weight and length of marine crabs was observed in this study similar to results of previous researchers. Such variation could be linked to food availability (Pollock, 1982; Pollock and Beyer, 1981); oxygen depletion which makes habitat unusable for blue crabs, create water column stratification thereby forcing crabs to move into shallow waters (Pollock and Shannon, 1987) and female commitment to reproduction after puberty which accounts for the reason why males tended to be heavier and longer than their female counterparts (Olmi and Bishop, 1983). Previous studies in the area indicate that males attain


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larger sizes than females (p < 0.05) as observed in Qua Iboe River estuary (Udoh et al., 2011), Imo River estuary (Nlewadim et. al., 2009) and Cross River estuary; Udoh et al., 2011). In contrast, this study recorded female marine crabs longer and heavier than their male counterparts. Similar observation was recorded in the months of January, February and March in the Cross River estuary (Udoh et al., 2011). The size difference between male and females, firstly, serve to protect the female against predators and other male competitors during mating; and secondly, it is advantageous that female mate with a large, capable male since they store more seminal fluid and spermatophores, mate more frequently and release larger volume of more potent ejaculate to ensure successful fertilization or reproductive investment, since females spawn once in their lifetime (Jivoff, 1997, 2003; Fischer and Wolf, 2006).

The condition factor (K) in this study varied between 4.01% and 11.51% (6.29±2.04), 3.72% and 16.65% (6.75±3.90), and 3.11% and 9.74% (5.79±1.76), for male, female and both sexes combined, respectively, as illustrated in Fig.3d. The mean condition factors displayed bimodal trend with the minor and major peaks in March and October, respectively; with the minimum in September. The highest value recorded in November result from abundance of berried females at that time of sampling. Flores-Vergara et al., 2004 and Taylor and Venn (1979) remarked that K of shellfishes including crabs are affected by endogenous activity such as gametogenic cycle and exogenous parameters such as water temperature, pH, oxygen level and food availability. Hence, the profile of the condition indices portrays the spawning cycle during which gonads formed in their abdominal cavities are extruded creating a lumen. It signals that the female attains the minor K peak in March and starts spawning in April, attaining its least K in May; thereafter it absorbs more water and abundant nutrient during the rainy season (Etim, 1990; Yildiz et al., 2006; Yıldız et al., 2011) to build fresh tissue, fill the lumen created in gonad after the release of gamete (Taylor and Venn, 1979) and to increase gametogenesis. Gonads consist mainly of protein and fat; these constituents are accumulated during gametogenesis whereas they decrease after spawning (Wolowicz et al., 2006). This amassed body condition peaks in November and is then invested in the main spawning and release of gamete between November and December. Hence, juvenile recruits of the March spawning enter the fishery in July/August (10-11% abundance) and those of the November/December spawning, in February-April (14-25% of total catch) as observed by Udoh (2016). Further important implications of the fluctuations in the condition indices is that sales and harvesting of crabs attract better pricing when crabs are plump and condition indices are high such as in September to December. In addition, at times of low food availability shellfishes use energy reserves in their body thereby reducing their nutritive quality and harvest values.

Nlewadim et al. (2009) and Udoh et al. (2011) established that carapace length (CL), carapace width (CW) and total weight (TW) of crabs were significantly (p < 0.05) influenced by sex, moult stage, colour morphotypes, and development stage. Udoh and Nlewadim (2011b) further assert that as the carapace length increases, the body weight and carapace width, and cheliped dimensions (palm depth, palm length, finger length and gape) reduce.

The high tendency (> 70%) towards right-handedness observed in this study is in conformity with previous reports on C. amnicola close to the study area, in Imo River Estuary, Qua Iboe River Estuary (Udoh and Nlewadim, 2011a) and Cross River Estuary (Udoh et al., 2011). The incidence of occurrence left and right chelae of the same diameter (isochely) was negligible (< 0.1%). However, Akin-Oriola et al. (2005) recorded chelae dimensions of the same diameter in Callinectes pallidus while Cardiosoma armatum showed slight left-handedness, prominent in males (P < 0.05) than in females (Akin-Oriola et al., 2005). Devi and Smija (2014) observed that adult males were heterochelous whereas females exhibited both heterochely and isochely in almost equal proportion (53 and 47%, respectively) in freshwater crab Travancoriana schirnerae in the wetlands of Mananthavady in Kerala, India. The significance of heterochely is related to signaling and defense. Large claws and male


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major chelae play important roles in crab territorial (offence and defense), sexual behaviour and in female may indicate reproductive vigour as well as ability (Daniels, 2001). Udoh and Nlewadim (2011b) established that asymmetry of palm depth reflect developmental instability from endogenous genetic or exogenous factors resulting from graded distribution and differential growth during development (otherwise known as growth gradient), in favour of male right-handedness within the populations. The b exponent of cheliped dimensions in males, females and combined indicates negative allometry (P < 0.05). Cheliped palm depth affords high discriminatory values between sexes and hence, serves as a secondary sexual character in C. amnicola (Udoh et al., 2009; Udoh and Nlewadim (2011b). Monitoring the chela palm diameter affords maturity estimation in male C. amnicola which Udoh et al. (2009), report exhibits early maturation to avert recruitment over-fishing. This agrees with the assertion of Haefner (1990) that heterochely decreases with increase in size and with age.

Three moult stages (early premoult, intermoult and post-moult) were encountered in this study similar to previous reports. Moulting plays a major role in growth increment and size distribution in crabs. Warner (1977) observed that premoult crabs achieve between 3 and 44% growth increment in carapace width, decreasing as the crab becomes larger. Adult post moult (brown) crabs in this study were about 18 g heavier and 2 cm CL longer than adult intermoult (brown) crabs; crabs exhibited about 65.35, 25.85 and 28.37% growth in total weight, carapace length and carapace width from early premoult to intermoult stages, respectively (Fig. 8); much higher than the 20.0, 2.0 and 2.0% growth reported respectively for same species in Qua Iboe River estuary (Udoh and Nlewadim (2011a). This is probably because the moulting mechanism in marine hyperosmotic euryhaline crabs such as the ones in this study affords high size definition (Hines et al., 1987), as evidenced in the clear modes displayed in the size frequency of both sexes (Fig. 2), medium range recruitment (10-25% as reported by Udoh, 2016) and spread over the size ranges 2.5-8.0 cm CL. Udoh and Nlewadim (2011a) and Udoh et al. (2011) observed that crabs in (oligohaline) Imo and (mesohaline) Qua Iboe River estuaries at reduced salinities exhibit low size definition of moulting and spread over similar size ranges 2.7 to 8.7 cm CL. Intermoult crabs > early premoult crabs > post moult crabs in weight as affirmed by Udoh and Nlewadim (2011a). While in this study, intermoult ≡ post moult > early premoult crabs by carapace length; Udoh and Nlewadim (2011a) observed that intermoult ≡ early premoult > post moult crabs by carapace length in the Qua Iboe River estuary, southeast Nigeria.

Blue crabs are usually grayish in colour, which allows them to blend with the muddy and sandy buttom of the shallow estuaries. They exhibit different color morphotypes of the carapace in relation to environmental variation of their habitat (McGraw and Naylor, 1992; McGaw et al., 1992). This study conforms to observations of previous studies (Nlewadim et al., 2009; Udoh et al., 2011) in the occurrence of three morphotypes (brown, olive brown and olive green) with the dominance of crabs of the green morphotype (60-80%) in the estuarine and marine biotopes southeast Nigeria. Portunid crabs of the green morphotype are known to withstand environmental stress (McGraw and Naylor, 1992; McGaw et al., 1992), oxygen depletion and toxic pollutants (Reid and Aldrich, 1989) better than crabs of other morphotypes. Equally as in previous studies (Nlewadim et al., 2009; Udoh et al., 2011), crabs of the green morphotype were significantly longer and heavier than crabs of other colour morphotypes (p < 0.05). Orange green crabs were rarely encountered and not recorded in this study.

Spatial and seasonal variations have been reported for estuarine crabs in southeast Nigeria (Nlewadim et al., 2009; Udoh et al., 2009, 2011; Udoh and Nlewadim, 2011a) similar to observations made for their marine counterparts in this study. By comparison, the crabs of the Qua Iboe River estuary are heavier (126.39; 9 to 323 g) and longer (6.2; 2.7 – 8.7 cm CL) than crabs of the same species in Imo (109.85; 4 - 307g and 5.9; 1.5- 8.1 cm CL) and Cross River (81.24; 4.5 – 195.0 g and 5.5; 2.3 – 8.5 cm CL) estuaries and from off-shore marine environment (79.95; 5.32 – 577.2 g and 5.2; 2.2 – 7.7 cm CL). Abowei and George (2010)


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also sampled C. amnicola of 1.79 – 146.72g and 1.1 – 7.4 cm CL from Okpoka Creek, southeast Nigeria. However, larger-sized crabs (3.30 – 348.5 g; 2.8 – 6.6 cm CL) of the same species are reportedly exploited in the Lagos area from Lagos, Badagry and Lekki lagoons and their adjacent creeks in southwest Nigeria (Fischer et al., 1981; Lawal–Are and Kusemiju, 2000; Emmanuel, 2008; Akin-Oriola et al., 2005; Lawal-Are and Bilewu, 2009). Environmental differences and bottom qualities of estuaries may account for these variations. It is possible that these preferred habitats provide suitable salinity high enough for carapace change and copulation. It is also established that portunid crabs including Callinectes species show preferences for shallow waters composed of fine and very fine sand (sometimes on mud and gravel) bottoms close to the discharge of estuaries (Charcur and Negreiros-Fransozo, 2001; Jamieson, 2002) and for areas with submerged aquatic vegetation like sea grasses which provide structural refuge from predation upon juveniles and molting individuals, and for its food resources. Ajao et al. (1996) describe the Lagos barrier-lagoon complex as a generally low swampy area, shallow with depth of 1.5-3 m, microtidal environment with often restricted circulation; and with high quality coarse and medium sand which act as filtration bed for nursery grounds, while the Strand Coast comprising Imo, Qua Iboe and Cross-River estuaries exhibit fine sand, silt and clay suitable for crab ecology (Ezenwa et al. (1990). Seitz et al. (2003) also present evidence that unvegetated habitats that are near marshes and characterized by high clam density appear to be critical to blue crab populations. Ekpo and Udoh (2013) reported that the estuaries accommodate large populations of juveniles, who retreat therein to take refuge, escape from predators and feed, grow and reproduce. Naturally, blue crabs exhibit a migratory life cycle, with juveniles dispersing to lower salinities (like Imo and Cross River estuaries) to feed and grow, reaching maturity in the upper reaches of the estuaries, and with inseminated mature females then migrating down the estuary to return to high salinities to incubate and hatch broods of eggs (Hines, 2003). Seasonal variations indicate that crab total weight and carapace length/width were higher (p < 0.05) in the dry months (November to March) than in the wet (April to October). Figure 3, particularly 3c, illustrates that the bimodal peaks occur first (minor) in the raining season and second (major) in the dry season. Similar observations were reported by Udoh et al. (2009, 2011) and Nlewadim et al. (2009). This may be attributed to the mass catch of ovigerous crabs in the dry season month of November when ovigerous C. amnicola migrate to higher salinity for carapace change and mating. Abowei and George (2010) also reported a mass catch of C. amnicola between December and January in the Okpoka creek, Niger Delta. Generally, abundance of crabs fall as dry season gives way to the raining season and estuary water is diluted, prompting seaward migration of adult crabs.

CONCLUSION The trawl by-catch marine crabs Callinectes amnicola from the Atlantic coast, off southeast Nigeria, show similar phenotypic affinity in size composition, length–weight relationship and growth pattern with estuarine population of the same species in the study area. Interpopulation differences might be attributable to salinity differences; hence the C. amnicola in these areas are of the same stock and could be subjected to similar management and conservation regulations. High populations of green crabs in the study sites are also indicative of high environmental variability.

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Yildiz, H., Berber, S., Acarlı, S. and Vural, P. (2011). Seasonal variation in the condition index, meat yield and biochemical composition of the flat oyster Ostrea edulis (Linnaeus, 1758) from the Dardanelles, Turkey. Italian Journal of Animal Science 2011; 10:e5; doi:10.4081/ijas.2011.e5.

Yildiz, H., Palaz, M. and Bulut, M. (2006). Condition indices of Mediterranean mussels (Mytilus galloprovincialis L. 1819) growing on suspended ropes in Dardanelles. Journal of Food Technology, 4: 221- 224.


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EFFECT OF ORGANIC FERTILIZATION ON YIELD PRODUCTIVI TY OF CASSAVA (Manihot esculenta Crantz) IN UYO, SOUTHEASTERN NIGERIA

Opara, A.C.,1 Ikeh ,A.O2 and Etokeren, U.E3

1Department of Soil Science and Land Resources Management, University of Uyo, Uyo, Akwa Ibom State, Nigeria

2 Department of Crop Science, University of Uyo, Uyo, Akwa Ibom State Nigeria. 3Department of Agricultural Technology, Akwa Ibom State College of Arts and Science

Nung Ukim, Ikono.Akwa Ibom State Corresponding Author: [email protected]/ [email protected]

ABSTRACT

The rain fed experiment was carried out at National Cereals Research Institute Uyo Station in 2012 and 2013 to evaluate the effect of organic fertilization on yield productivity of cassava in Uyo southeastern Nigeria. The experiment was laid out in a randomized complete block design (RCBD), replicated three times. The treatments six (four organic fertilizer levels, viz; 2, 4, 6 and 8 t/ha and two control treatments, viz; 400kg/ha recommended rate of inorganic fertilizer and no soil amendment. Growth and yield parameters were assessed. The application of 8 t/ha of poultry manure (PM) produced the highest storage yield (27.19 and 28.11 t/ha) in 2012 and 2013 cropping seasons, respectively. This was followed by storage roots of 26.95 and 27.80 t/ha, respectively, harvested from 6 t/ha of PM plots. The least storage root yield; 11.03 and 10.73 t/ha was recorded from control (no soil amended) plots. The result showed that application of PM at the rate of 8 t/ha produced 1 – 59 % and 1 – 62 % more storage yield than other treatment. Comparing the yield obtain from 8 t/ha of PM and recommended rate of NPK. The result revealed that 8 t/ha of PM plots out-yielded NPK plots with 13% and 14 % storage root in 2012 and 2013 cropping season. The 8 t/ha of PM plots out-yielded 6 t/ha plots with only 1 % storage yield in both cropping seasons. Plots of NPK had the highest production cost (N335500) and (N334900) in 2012 and 2013 cropping seasons, respectively. The least production cost (N245500) and (N250700), respectively was recorded from control (no soil amendment) plots. Comparing the results net returns the application of 8 t/ha of PM gave the highest net returns (N2816950) and (N 3063200), respectively. This was followed by N2816250 and N3047500, respectively recorded from plots of 6t/ha of poultry manure. Control (no soil amendment) had the least net returns (N1022950) and (N1036900), respectively. Result of cost/benefit ratios revealed that application of 6 t/ha of PM gave the highest economic benefit with cost/benefit ratio of 9.95 and 10.56, respectively. Plots of NPK had cost/ benefit ratio of 7.07 and 7.66 in 2012 and 2013 cropping seasons, respectively. The least cost/benefit ratio 4.17 and 4.14 was obtained from control (no soil amendment) plots. The study therefore concluded that application of 6t/ha of PM could guarantee high productivity of cassava in the study area.

Keywords: Cassava, organic fertilizer, yield, productivity, Southeastern Nigeria

INTRODUCTION Cassava (Manihot esculenta Crantz) maintains a prominent positive position among tropical crops. The crop is one of the most dominant and main crop components in crop mixtures in south-eastern Nigeria and it is gradually gaining importance as an industrial crop (Mouneke and Mbah, 2007). Nigeria’s annual production of cassava is estimated at 49 million tonnes. About 90 percent of it is used as food (Awoyinka, 2009). Cassava is used for food, livestock feed and industrial materials. About 70% of total cassava produced is processed into a wide range of products, these include chips and flour. The chips are dried and stored or milled into stable forms before storage. Cassava flour is used in preparing varieties of

Opara, A.C., Ikeh, A.O. and Etokeren, U. E. (2017). Effect of Organic Fertilization on Yield Productivity of Cassava (Manihot esculenta Crantz) in Uyo, Southeastern Nigeria. Journal of Environment and Sustainable Development, 3(1): 89-96.


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confectionery. In bread making, cassava flour is used as partial substitute to wheat flour without loss of bread quality (Eggleston et al., 1993).

Cassava is used in the food industry in many preparations, including sauces, gravies, custard powder, baby foods, tapioca, glucose, confectionery and bakery products. It is also used for jelly or thickening agent. It is used extensively in the manufacture of adhesives, dextrins and paste and as filler in the manufacture of paints. In the textile industry, it is used for wrapper sizing, cloth and felt finishing. It is also used in the manufacturing of drugs and ethanol and as bio-fuel. In the South Eastern States of Nigeria, especially in Ibibio land it is used in the preparation of local dishes like “edita-iwa”, “ayan-ekpang”, and “asa-iwa,” (Ekpe and Obiefuna, 1998).

Cassava supplies a good percentage of daily energy calories to man and livestock as well as raw materials to industries. Continuous cropping on lands in Nigeria has greatly depleted soil nutrients and rendered such lands unproductive and hence decline in cassava storage yield. In modern farming technique, fertilizers are applied to improve soil fertility status so that maximum optimum crop yield.

The current trend in farming system of southern Nigeria is that peasant farmers are intensifying cultivation to meet the demand of the ever increasing population of the zone. However, Continuous cropping without judicious soil conservation had been reported to degrade the soils. Inorganic fertilizers are expensive and scare in Nigeria. It also contributes to environmental pollution and soil degradation. In recent years, there has been more dependence on the use of local and cheap organic sources of nutrients for cultivation of cassava and other crops (Ikeh, et al., 2013 and Ikeh et al, 2015). The above reasons have necessitated research on increasing effectiveness of organic manures and wastes for enhanced productivity of cassava. Also, research and development activities on cassava are not commensurate with the crops increasing importance of the crops as food and industrial raw materials (Akata, 2015). It has therefore become necessary to carry out research on how to reduce the farmer’s dependence on inorganic fertilizers by using some of these organic wastes which are always available and inexpensive, environmentally friendly and ecologically sound as well as promoting sustainability in crop production under the low external input agriculture. Application of manures at appropriate rates had been reported to improve soil physical and chemical properties, likewise growth and yield of maize, fluted pumpkin, pepper, yam etc (Idem et al., 2012; Ikeh et al., 2012; Ikeh et al., 2016). This study was therefore designed to compare poultry manure rates with the recommended rate of inorganic fertilizer for cassava in Nigeria.

MATERIALS AND METHODS The experiment was conducted at National Cereals Research Institute Uyo Out-Station during the 2012 and 2013 planting season. Uyo is situated in the humid tropical rain forest zone of South East Nigeria and lies between latitudes 4o33' and 6o33' North and longitude 7o35' and 8o25’ East (UCCDA, 1989). Annual rainfall ranges from 2000 -3500m. The rainfall is bimodal, rains starts in March and ends in November with a short period of relative moisture stress in August (UCCDA, 1989) often referred to as “August break”. The average temperature of the area is 27oC. Temperatures are highest in the month of February through April while relative humidity is 77-95%, lowest in January and highest in July (Peters et al. 1989; Enwezor et al, 1990). The area receives ample solar radiation during the dry months of November to February but there is usually cloud cover during the cropping season of March to October (Enwezor et al, 1990).

The site was cleared manually with machetes. Ridges were constructed with spade after marking out the field with tape, rope and pegs for proper spacing. The ridges were constructed one metre apart and three metre long. Composite soil samples were collected at


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two soil depths (0 – 30 cm) using soil auger before planting. The soil samples were carefully put in polyethylene bags and labeled before being taken to the laboratory for analysis. The entire experiment occupied 30 m x 15m plot size. Each plot size was 3m x 3m. Each plot and block were separated one from the other at one metre apart respectively. The experiment was laid out in Randomized Complete Block Design (RCBD). The treatments were four levels (2, 4, 6 and 8 t/ha) of organic fertilizer (poultry manure) and two control treatments (400 kg/ha recommended rate of inorganic fertilizer and no soil amendment) Planting was done on March in both cropping seasons. Cassava stems cuttings measured 25cm was inserted on the crest of the ridge in a vertical position at spacing of 1m x 1m. Cassava variety used for the experiment was TMS 01/1368 (Pro-Vitamin variety) or popularly known as yellow root. Weeding was done three times using native weeding hoe at 1, 3 and 5 months after planting (MAP). The organic fertilizer (poultry manure) was incorporated into the soil during tillage according to treatment levels two weeks before planting. While at 2 MAP NPK fertilizer was applied using the ring method on treatment basis. The cassava root were harvested manually at 11 MAP by cutting the stems 20cm above soil level and pulling roots out carefully before detaching the roots, and the weight of the fresh storage root yields were determined with aid of weighing balance. All the growth and yield data collected were subjected to Analysis of Variance (ANOVA) and treatment means that indicated significance at 5 percent level of probability were compared using Least Significant Difference.

RESULTS The soil analysis showed that the soil was acidic with pH value of 5.50 and 5.30 at 2012 and 2013 cropping seasons, respectively. The organic carbons were low in both cropping seasons. The available P (mg/kg) was high in both cropping seasons (Table 1). The percentage nitrogen of 0.06 was far below 0.20% recommended by Udoh et al (2005). The exchangeable bases, Ca, Mg, Na and K were low in both cropping seasons. The particle size analysis indicated high fraction of sand, 88.80% and 84.00% in 2012 and 2013 cropping seasons, respectively, with clay portion of 7.00% and 10.80% respectively (Table 1). The result of fertilizer rates showed significant difference (P<0.05) (Table 2). The application of 8t/ha of poultry manure produced tallest plants in all the months, irrespective of cropping seasons. The shortest plant on average was recorded in control in all the months under investigation. At 6 months after planting, application of 8 t/ha of poultry manure had 3 - 49 % and 1- 43 % taller plant than other treatments in 2012 and 2013 planting seasons, respectively.

The effect of fertilization showed significant differences (P<0.05) in both cropping seasons, with the application of 8 and 6 t/ha of poultry manure producing highest number of leaves on average compared to other treatments (Table 3) The least number of leaves per plant was recorded in control treatment (Table 3). At 6 MAP, application of 8 t/ha of poultry manure had 1 – 43 % and 4 – 48 % more number of leaves per plant than other treatment. Among the fertilizer treatments, treatment of poultry manure at 8 t/ha produced significant highest leaf area in all the sample months, followed by treatment that received 6 t/ha of poultry manure while the least leaf area in all the sample months under study was recorded in control treatment.

The effect of fertilization on the number of tubers per stand showed significant difference (P<0.05), over control treatment (Table 5). The application of 8 t/ha of Poultry manure produced 7.40 and 7.51 tubers on average in 2012 and 2013 planting seasons, respectively. Treatment that received 400kg/ha of NPK had 6.33 and 6.01 storage roots per


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plant in 2012 and 2013 planting seasons, respectively. The least number of tubers on average; 3.67 and 3.34 in both planting seasons was recorded in control treatment.

The result of fertilization on the yield of cassava showed significant increase in tuber yield over the control treatment. The result also showed that increase in the rate of organic fertilizer result to corresponding increase in storage root yield. The application of 8 t/ha of Poultry manure produced highest storage root yield, 27.19 and 28.11 t/ha in 2012 and 2013 cropping seasons, respectively. This was followed by application of 6 t/ha of poultry manure; 26.95 and 27.80 t/ha, respectively. Application of 400 kg/ha of NPK produced storage root yield of 23.55 and 24.18 t/ha, respectively. The least tuber yield, 11.03 and 10.73 t/ha was obtained in control treatment. The result indicated that treatment of 8 t/ha of poultry manure had 1 – 59 % and 1 – 62 % higher storage root yield than other treatment. Comparing the yield obtain from 8 t/ha of poultry manure and recommended rate of NPK. The result revealed that 8 t/ha of poultry manure had 13 and 14 % more storage root yield than NPK.

Results of production cost and economic returns presented in Table 6 showed that NPK plots had the highest cost of production (N335,500) and (N334,900) in 2012 and 2013 cropping seasons, respectively. The least cost of production (N245,500) and (N250,700), respectively was recorded from control (no soil amendment plots). The study showed that application of NPK resulted to 8-27 % and 7 – 25 % increase in production cost in both cropping seasons. The plots of 8 t/ha of poultry manure gave the highest net returns to management (N2,816,950) and (N3,063,200), respectively. The least net revenue (N1,022,950) and (N1,036, 900), respectively was obtained from control (no soil amendment) plots. The plots of 6 t/ha of poultry manure gave the highest cost/benefit ratio (9.95) and (10.56) in 2012 and 2013 cropping season, respectively. The least cost/benefit ratio (4.17) and (4.14) respectively was recorded from control (no soil amendment plot).

DISCUSSION The soil analysis before planting showed that the soil is sandy loam. It is also noted that the soil has low pH which means it is acidic soil. From the recommendation of Ibia and Udo (2009), the soil is also low in total nitrogen, organic matter content and available potassium. The significant effect of organic fertilizer application may be attributed to the low initial nutrient status of the experimental site. This agreed with the findings of Ibia and Udo (2009). They noted that crops respond more to fertilizer application in soil with very low nutrient content than soil with high nutrient reserve. The result of soil analysis after harvesting showed increase in soil pH. This result agreed with finding of Ikeh et al (2016) who reported soil acidity caused an unavailability of the nutrient elements to crops which was checked by the liming potential of organic manure. The significant response of growth and yield parameters evaluated to fertilization could be that the nutrients taken up by the plant were well utilized in cell multiplication, amino acid synthesis and energy formations hence increase in photosynthesis. The products of photosynthesis were then translocated to the sinks (fruit and growing buds).

The application of poultry resulted to increase in the growth and yield of the cassava. This observation agrees with the report Ikeh et al. (2013) and Ikeh et al (2015), that application of organic manure improved the soil chemical and physical properties which enhance crop growth and development. The variations observed in vegetative traits and yield of cassava under the different rates of organic manure (poultry) could be due to differences in the concentrations of macro and micro elements. This was in line with the findings of Akata (2015) increase in organic manure level resulted to significant increase in the growth and yield. The significant response of parameters (growth and yield parameter) evaluated to organic manure (poultry) levels may be an indication that the nutrients, taken up by the plant were well utilized in cell multiplication, amino acid synthesis and energy formation hence


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increase in photosynthesis. The products of photosynthesis were then translocated to the sinks (growing bud and storage roots). The highest cost of production in the system was observed from treatment that received NPK in both cropping seasons. This may be attributed to the high cost of NPK. Similarly highest benefit cost ratio was obtain from poultry manure rate at 6 t/ha in both cropping seasons

CONCLUSION

The results of the field experiment show that application of 8 t/ha of poultry manure produced the highest storage root yield and net returns to management, followed by 6 t/ha of poultry manure while the least was recorded in control. The study therefore recommended 6 t/ha of poultry manure for high productivity of cassava in the study area.

REFERENCES

Akata, O. R (2015) Influence of Organic Fertilizers on Soil Fertility, Weed Dynamics and Performances of Cassava Varieties in Uyo, Akwa Ibom State. Unpublished Ph.D Thesis of Department of Crop Science, University of Calabar, Cross River State, Nigeria.

Awoyinka, Y. A. (2009). Effect of Presidential Initiatives on Cassava Production Efficiency in Oyo State Nigeria. Ozean Journal of Applied Sciences 2(2): 185-193.

Ikeh, A. O., Ndaeyo, N. U., Akpan, E. A., Udoh, E. I., Akata. O. R. (2013). Evaluation of Complementary Use of Organic Manure for Sustainable Water Yam Production in Uyo, Southeastern Nigeria. American Journal of Research Communication, 1(2):33-48.

Ikeh, A. O. Etokeren, U. E., Akpan, E. A. and Essien, I. E (2015). Effect of Composted Pig Excreta Rate on performance of some Elite Yam Genotype in Kaolinitic

ultisol of southeastern Nigeria. Journal of forestry, Environment and sustainable Development, 1(2): 120-128.

Eggleston, G., Omoaka, P.E. and Arowoshegbe, A.U. (1993). Four Starch and Alternative (Wheatless) Bread Making Quality of Various Cassava Clones. Journal of Science and Food Agriculture, 62:61-66

Ekpe, E. O. and Obiefuna. J. C. (1998). Effect of Cassava Maize Intercropping System, Time of Harvesting, Fertilizer Level on Top Growth and Tuber Yield on Four Cassava Morphotypes. Nigeria Journal of Crop and Soil Science, 4(1): 54-70.

Enwezor, W. O., Udo, E. H., Ayotode, K. A., Adepetu, J. A. and Chude, V. O. (1990). A Review of Soil and Fertilizer Use Research in Nigeria. Vol. 4 Middle Belt Zone Federal Ministry of Agric. and Natural Resources, p. 217.

Ibia, T. O. and Udo, E. J. (2009). Guide to Fertilizer Use for Crops in Akwa Ibom State, Nigeria. Sibon Books Limited, Festac, Lagos, Nigeria. pp. 101.

Idem, N. U. A., Ikeh, A. O. Asikpo, N. S. and Udoh, E. I. (2012). Effect of Organic and Inorganic Fertilizer on Growth and Yield of Fluted Pumpkin (Telfaria Occidentalis, Hook.F) in Uyo, Akwa Ibom State. Nigeria Journal of Agriculture and Social Research 12 (2):74-84.

Ikeh, A. O. Ndaeyo, N. U., Uduak, I. G., Iwo, G. A., Ugbe, L. A., Udoh, E. I., Effiong G. S. (2012) Growth and Yield Responses of Pepper (Capsicum frutescens L.) to varied Poultry Manure Rates in Uyo, Southeastern Nigeria. ARPN Journal of Agricultural and Biological Science 7(9):735-742.

Ikeh, A.O., Udounang, P.I., Essien, I.E., Etokeren, U.E. and Ndaeyo, N.U. (2016). Response of Maize to Different Crop Residue Ash Source in Acid Coastal Plain Soil of Southeastern Nigeria. Journal of forestry, Environment and sustainable Development, 2(1): 80-87.


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International Institute Tropical Agriculture (IITA, 1990). Cassava in Tropical Africa: A Reference Manual. Chayce Publication Services, United Kingdom Edition. 196p.

Muoneke, C. O. and Mbah, E. U. (2007). Productivity of Cassava/Okra Intercropping Systems as Influenced by Okra Planting Density. African Journal of Agricultural Research 2 (5): 223-231.

Peters. S. W., Usoro, E. J., Obot, U. W. and Okpon, S. N. (eds). (1989), Akwa Ibom State: Physical Background, Soil and land Use and Ecological Problems. A Technical Report of the Task Force on Soils and Land Use Survey, Akwa Ibom State. pp. 198-191.

Tisdale, S. A. and Nelson, W. L. (1975). Soil Fertility and Fertilizers. Macmillan Publishing Company Inc. (3rd ed.) N. Y.

UCCDA (1988). Year Report. Uyo Capital City Development Authority. Uyo Akwa Ibom State.

Udoh, D. J., Ndon, B. A. Asuquo, P. E. and Ndaeyo, N. U. (2005). Crop Production Techniques for the Tropics. Concept Publication Lagos, 48-49, 211-216

Table 1: Soil Physico-chemical Properties of the Experiment Site before Planting.

2012 2013 Soil Properties Soil depth (cm)

0-30 0-30

pH 5.50 5.30 Total N (%) 0.06 0.04 Organic carbon (%) 1.18 1.10 Available P (cmolkg-1) 61.33 59.26 Exchangeable bases (cmol/kg) Exchangeable Ca (cmol/kg) 2.16 2.01 Exchangeable Mg (cmol/kg) 1.31 1.30 Exchangeable Na (cmol/kg) 0.05 0.05 Exchangeable K (cmol/kg) 0.08 0.07 Effective Cation exchange Capacity(ECEC) (cmol/kg) 6.84 6.37 Exchangeable acidity (cmol/kg) 2.85 2.80 Based saturation (%) 65.19 59.19 Particles Analysis (%) Sand 88.80 84.00 Silt 4.20 5.20 Clay 7.00 10.80

Table 2: Plant Height (cm) of Cassava as Influenced by Organic Fertilizer Levels Poultry Manure (t/ha)

2012 Months after planting


2 4 6 2 4 6 0 41.18 88.11 95.74 45.55 81.23 108.90 2 77.79 112.50 148.86 73.50 109.59 141.75 4 79.39 143.33 176.89 77.37 151.40 180.85 6 85.67 150.23 183.60 99.28 152.66 189.70 8 86.25 156.48 189.04 101.29 153.34 191.65 NPK (400kg/ha) 96.60 112.19 175.11 88.10 145.13 181.05 LSD (P<0.05) 4.51 5.98 6.60 4.05 6.09 7.88


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Table 3: Number of Leaves per Plant of Cassava as Influenced by Organic and Inorganic Fertilizers

Poultry Manure (t/ha)



2 4 6 2 4 6 0 22.45 56.09 101.12 25.12 41.65 99.10 2 41.43 82.50 134.89 33.10 76.50 146.05 4 56.10 98.09 155.81 55.30 90.41 161.34 6 61.60 110.11 176.90 70.18 102.11 181.09 8 61.90 114.34 178.76 77.05 120.67 189.44 NPK(400kg/ha) 26.98 108.19 165.11 29.01 99.13 178.19 LSD (P<0.05) 5.01 6.77 8.85 4.99 6.12 6.91

Table 4: Leaf Area (Cm2) of Cassava as Influenced by Organic Fertilizer Levels

Poultry Manure (t/ha) 2012 Months after planting


2 4 6 2 4 6 0 88.81 95.87 102.17 79.91 92.73 110.37 2 109.67 129.90 125.19 99.78 127.80 124.00 4 112.78 137.00 136.12 106.09 138.45 133.19 6 118.90 145.54 146.11 118.12 141.54 145.25 8 120.05 145.89 146.90 119.80 143.67 146.77 NPK(400kg/ha) 91.90 138.34 137.10 87.99 133.45 136.15 LSD (P<0.05) 3.90 5.17 6.78 4.06 7.10 7.45

Table 5: Yield and Yield Component of Cassava as Influenced by Organic Fertilizer Levels

Poultry Manure (t/ha)

Number of tubers/plant

Storage Root yield (t/ha)

Number of tubers/plant

Storage Root yield (t/ha)

0 3.67 11.03 3.34 10.73 2 6.51 18.47 5.98 19.55 4 7.25 21.50 7.33 22.90 6 7.30 26.95 7.50 27.80 8 7.40 27.19 7.51 28.11 NPK(400kg/ha) 6.33 23.55 6.01 24.18 LSD (P<0.05) 2.18 3.11 2.05 3.56


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Table 6: Cost of Production and Economics Returns to Managements (N) as Influenced by Organic Fertilization

2012 2013

Treatment Total Cost of Production

(N)

Storage Root Yield (t/ha)

Gross Returns

(N)

Net Returns (N)

Cost/ Benefit Ratio

Total Cost of Production (N)

Storage Root Yield (t/ha)

Gross Returns

(N)

Net Returns (N)

Cost/ Benefit Ratio

0 245500 11.03 1268450 1022950 4.17 250700 10.73 1287600 1036900 4.14 2 25500 18.47 2124050 186950 7.33 268000 19.55 2346000 2078000 7.75 4 264500 21.50 2472500 2208000 8.35 279000 22.90 2748000 2469000 8.85 6 283000 26.95 3099250 2816250 9.95 288500 27.80 3336000 3047500 10.56 8 309900 27.19 3126850 2816950 9.09 310000 28.11 3373200 3063200 9.88

NPK 335500 23.55 2708250 2372750 7.07 334900 24.18 2901600 2566700 7.66

Cost of production includes: land preparation, planting material/planting, organic fertilizer/application, weeding, harvesting and transportation. A tone of cassava storage roots was sold at N115, 000.00 and N120, 000.00 based on prevailing market price in 2012 and 2013.

Table 7: Chemical Analysis of Poultry Manure used in the study

Mineral Elements (%) 2012 2013 Nitrogen 2.37 2.48 Phosphorus 2.11 2.32 Potassium 0.52 0.62 Calcium 6.82 7.12

Magnesium 3.11 3.25 Sodium 0.19 0.21


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OCCURRENCE OF CERCOSPORA LEAF SPOT DISEASE OF OKRA IN ITU, AKWA IBOM STATE, NIGERIA.

Nneke, N. E. Department of Crop Science,

University of Uyo, P.M.B. 1017, Uyo, Akwa Ibom State ([email protected], 07031110980)

ABSTRACT

The occurrence of Cercospora leaf spot disease of okra was studied in Itu Local Government Area of Akwa Ibom State, Nigeria in 2014 and 2015 wet season (March-October). Five okra farms in each Clan of Itu Local Government Area (Itam, Itu, Ayadehe and Oku Iboku Clans) were sampled. The transect sampling method was used. Okra plants found at every 90cm along the X transect were observed for the occurrence of cercospora leaf spot disease. Results showed significant (p≤0.05) differences among the locations. The highest disease incidence was in Ikot Ntuen (66.6%) in Oku Iboku Clan and the lowest incidence was in Ika (16.6%) also in Oku Iboku Clan. The leaf spot disease pathogen as seen under the microscope had the following characteristics: conidiophores were dark, simple, arising in clusters and bearing conidia successively on new growing tips, the conidia were hyaline, filiform and multispetate. Based on the above characteristics, the pathogen was identified as Cercospora species.

Keyword: Occurrence, leaf spot disease, Cercospora species okra, Akwa Ibom State.

INTRODUCTION Okra, Abelmosclus esculentus (L) Moench belongs to the family Malvaceae and originated in Abyssinia before it was taken to North Africa, the eastern Mediterranean Arabia and India (Anon, 2008). It is one of the important vegetables, mainly grown for its tender fruits in many countries of the world. Okra seeds are good source of protein, vegetable oil and also rich in Vitamin A and B, phosphorus and iodine, which play significant role in human diet (Baloch, 1994; Yadar and Dhankhar, 2001; Khushk et al, 2003). Okra is a power house of valuable nutrients, soluble and insoluble fibre, which helps to lower serum cholesterol, risk of heart disease, keeps the intestinal tract healthy and decrease colorectal cancer (Broek et al, 2007).

Okra plant however, suffers from a number of insect pests and diseases. Among them is leaf spot which is a serious fungal disease, that may be found in okra growing areas (Jha and Dubey, 2000; Kochhar, 2005; Jiskani, 2006). The optimum temperature and pH for the growth of Cercospora sp, the causal agent of okra leaf spot disease has been found to be 28°C and pH 6.5 respectively. Excellent sporulation was observed at 25-30°C and pH levels of 5.5 to 6.5 (Maheshwari et al., 2000).

The symptoms of Cercospora leaf spot disease firstly start as light brown spot, and then turn to concentric dark brown spots, varying in size and becoming necrotic. These spots spread to cover large areas of infected leaves. In the case of severe infection, infected leaves become brown and die (Cho and Moon, 1980; Werner, 1987; Tohyama et al., 2003; Antonijevic et al., 2007). In some cases, heavy infection has led to total loss of yield (Rizzolli and Acter, 2006). Okra leaf spot could therefore, be a very serious production problem.

Available literature indicate that limited study has been done on this leaf spot disease. Therefore, this study was conducted in Itu Local Government Area of Akwa Ibom State to

Nneke, N. E. (2017). Occurrence of Cercospora Leaf Spot Disease of Okra in Itu, Akwa Ibom State, Nigeria. Journal of Environment and Sustainable Development, 3(1): 97-101.


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survey the okra crop, for identification of the leaf spot disease and its causal agent, as well as estimate its incidence level.


Study Area: Akwa Ibom falls within the tropical rainforest zone of Nigeria and is located on latitude 4°31' and 5° 31'N, longitude 7°31' and 8°30'E and 65m above mean sea level. The mean annual temperature is 27°C, the mean annual rainfall is 2701mm and falls between March and November, which are also the peaks in bimodal pattern. The mean monthly sunshine is 3 hours 31 minutes (Meterological Garden, 2012).

Sampling Technique Five okra farms in each of the four Clans (Itam, Itu, Ayadehe and Oku Iboku) of Itu were randomly selected and sampled in the wet season of 2014 and 2015 (September). Information recorded for each farm was name of farm location and the size of the farm. Two diagonal transects, the lengths of which depended on the size of the farms, were taken across each farm. Okra plants at every 90cm along the transects were examined for the incidence of Cercospora left spot disease. All the farms sampled were okra monocrop plants of the same age range in the upland.

Disease incidence was assessed by visual observation of sampled plants. A single spot or lesion is sufficient to establish occurrence (incidence) of the disease. Incidence was established by the presence of brown, leaf spots on the lamina of leaves.

Disease incidence was computed from the relationship given by Waller et al (1998), thus:

Numberofdiseasedplants

Totalnumberofplantssamples3

100

1

Collection of diseased leaf sample Okra leaves showing brown leaf spot were collected in the wet season (September), 2015 from farms in which the disease surveys were conducted. Two leaves each were collected from one Clan in the survey area. A total of 8 (eight) leaves were collected from the four clans in Itu Local Government Area. Data recorded for each farm were name of the farm location and the disease severity on the leaves. The leaves were taken to the plant pathology laboratory in the University of Uyo in labeled sampling bags and preserved in a refrigerator for laboratory analysis.

4. Preparation of Potato Dextrose Agar The samples were picked from the sample bag using a sterilized forceps, placed on a sterilized work bench and the spots were cut into sections using a sharp scalpel. The cut sections (3-5mm2) were sterilized in 10% sodium hypochlorite solution for two minutes and rinsed in three successive changes of sterile distilled water.

Thirty nine grammes of PDA was suspended in 1000ml of distilled water and heated to boil in order to dissolve the medium completely. It was thereafter sterilized by autoclaving at 121°C at 15 bars pressure for 15 minutes. When the medium had cooled to about 40°C, it was dispensed into petri-dishes and allowed to set.

5. Isolation of the Pathogen The leaf sections were dried between two layers of filter paper and three leaf sections from each Clan were equidistantly plated on potato dextrose agar (PDA) medium in 9cm petri dishes. All the inoculated plates were incubated at 26 ±20C for one week and observed


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daily for fungal growth in the medium. Pure culture of any fungal growth was obtained by sub-culturing into fresh PDA medium. 6. Microscopic Examination Small amount of the fungal mycelium in each pure culture was stained with methylene blue on a glass slide and observed with the aid of a research compound microscope at 10 x 40 x magnification. Morphological characteristics of the fungus such as shape and nature of conidiophores, as well as shape, colour and septation of conidia were noted. Identification of the leaf spot disease of okra pathogen was according to Barnett and Hunter, (1972).

RESULTS AND DISCUSSION Disease Incidence Results showed significant (p≤0.05) difference among the locations. Table 1 shows the mean disease incidence of okra in Itu Local Government Area in 2014 and 2015. At all the 20 farms, the highest disease incidence was in Ikot Ntuen (Oku Iboku Clan) and Obot Etim I (Itu Clan) with incidence of 66.6% and 62.2% respectively. The lowest disease incidence occurred in Ika (Oku Iboku Clan) with 16.6%. The Cercospora leaf spot disease incidence for other locations varied from 20.5% to 50.0%.

Table I: Mean disease incidence on okra plant (Abelmoschus esculentus) in 2014 and 2015 in Itu Local Government Area, Akwa Ibom State. S/No. Location Total crop sampled No. of plants diseased Mean

incidence Itam Clan 2014 2015 2014 2015 1 Mbak Atai 120 136 60 68 50.0 2 Obong Itam 140 148 30 42 24.0 3 Ikot Ayan Itam 100 108 52 28 38.9 4 Ekit Itam 110 130 51 45 40.4 5 Enen Atai 120 136 56 40 38.0 Mean 38.4 Itu Clan 6 Itu Hill 150 162 75 69 46.2 7 Obot Etim I 136 120 90 70 62.2 8 Obot Etim II 122 142 40 56 36.1 9 Obot Itu I 108 132 30 42 29.8 10 Obot Itu II 190 170 40 56 26.9 Mean 40.2 Oku Iboku Clan 11 Ikot Ntuen 142 146 90 102 66.6 12 Ika 140 148 20 28 16.6 13 Ikot Abaiyad 182 170 70 74 40.9 14 Ikot Essien I 114 110 30 34 28.6 15 Ikot Essien II 148 140 42 54 33.4 Mean 37.2 Ayadehe Clan 16 Ayadehe I 120 136 61 67 50.0 17 Ayadehe II 150 130 20 36 20.5 18 Afaha I 124 132 39 25 25.2 19 Afaha II 140 148 30 42 24.9 20 Afaha III 150 162 70 50 38.7 Mean 31.8 Among the Clans, the highest disease incidence was recorded in Itu (40.20%) and the lowest incidence was obtained in Ayadehe (31.8%). The remaining Clans (Itam and Oku Iboku) had incidence status of 38.4% and 37.2%, respectively (Table 1).


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Identification of the Pathogen Under the microscope, the morphological characteristics of the furgus were observed: conidiophores were dark, simple, arising in clusters and bearing conidia successively on new growing tips, the conidia were hyaline, filiform, and multiseptate (several celled). Based on the above characteristics, the fungus was identified as Cercospora species.

DISCUSSION The percentage disease incidence varied with locations. The four Clans in Itu Local Government Area (Oku Iboku, Itu, Ayadehe and Itam) were represented in the maximum incidence level of the Cercospora leaf spot disease. Therefore, the disease is an important disease in Itu Local Government Area of Akwa Ibom State. Similar symptoms of leaf spot disease have been reported by Antonijevic et al. (2007) and Werner (1987).

The fungus, Cercospora species a member of the order Moniliales, was isolated and identified as the cause of okra leaf spot disease. The pathogen decreases the photosynthetic activity of infected leaves by turning them to dark brown in colour whereas photosynthesis can only take place in green tissues. Jayapal and Mahadevan (1968) also found a quick decline in the sugar content of banana leaves due to Cercospora infection. Therefore, the effect of Cercospora on infected leaves vary from one plant species to another.

CONCLUSION AND RECOMMENDATION

The results of the survey showed that the highest disease incidence was obtained in Ikot Ntuen and Obot Etim I while the lowest disease incidence was recorded in Ika and Ayadehe II. The leaf spot disease pathogen had dark and simple conidiophores arising in clusters and bearing conidia successively on new growing tips, the conidia were hyaline, filiform and multiseptate. Thus, the pathogen was identified as Cercospora species. It is recommended that farmers in Itu Local Government Area should procure resistant varieties of okra to leaf spot disease for planting such as lady’s finger.

REFERENCES

Anon, (2008). FAOSTAT. Food and Agricultural Organization Statistics, Rome. pp. 7-10.

Antonijervic, D. P. Fakulet, B., Zemun, M. and Mitrovic P. (2007). Leaf spot of oil seed rape Plant Doctor, 35(4): 443-449.

Baloch, A. F. (1994). Vegetable Crops. Horticulture National Book Foundation. Islamabad. pp. 489-537.

Barnett, H. L. and Hunter, B. B. (1972). Illustrated Genera of Imperfect Fungi. Burgess Publishing Company, Minneopolis, Minnesota. 124 p.

Broek, R. V., Lacovino, G. D. Paradela, A. L. and Gali, M. A. (2007). Alternative Control of Erysiphe cichoaearum on okra crop. Ecossistema, 27:23-26.

Cho, J. T. and Moon, B. J. (1980). The occurrence of strawberry black leaf spot caused by Alternaria alternata. Korean Journal of Plant Protection, 19(4): 221-226.

Jayapal, R. and A. Mahadevan (1968). Biochemical changes in banana leaves in response to leaf spot pathogens. Indian phytopath, 21: 43-48.

Jha, A. K. and S. G. Duley (2000). Occurrence of collar rot of Abelmoshus esculentus in plateau region of Bihar. J. Res. Psirsa Agri. Univ, 12 (1): 67-72.

Jiskani, M. M. (2006). Okra diseases and IPDM. http//www. pakissan.com.


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Khushk, A. M., U. Shar and M. A. Memon (2003). The cultivation of Okra in Sindh and its economic view, PARC. Technology Transfer Institute, Tandojam. Publication in Sindh Zarat 136:17-18.

Kochhar, R. (2005). Florida plant disease management guide: Okra http.edifan; ufl edu/pdf.

Maheshwari, S. K., Singh, D. V. and Singh, S. B. (2000). Effect of temp and pH on growth and spoulation of Alternaria alternata causing Alternaria leaf spot of dolichos bean. Annals of Plant Protection Sciences, 8(1): 33-35.

Meteorological Garden (2012). Department of Geography and Regional Planning, University of Uyo, Nigeria. pp. 14.

Rizzolli, W. and Acter, A. (2006). Efficacy of some fungicides against Atternaria altermata on apple. Atti delle Gionate Fitopatologiche, pp. 92-102.

Tohyama, A. K., Hayashi, K. Taniguchi, N. Naruse, C. Ozawa, Y. Shishiyama, J. and Tsuda M. (2003). A new post-harvest disease of okra pods caused by Alternaria alternata. Annals of the Phytopathological Society of Japan, 61 (4): 340-345.

Waller, J. M; Rtichie, B. J. and Holderness, M. (1998). Plant Clinic Handbook. IMi Technical handbooks No. 3, CAB International. 94p.

Werner, M. (1987). Necrotic leaf spot of apple caused by fungi of the genus Altermaria. Ochrona Roslin, 31(10): 6-7.

Yadar, S. K. and Dhankhar, B. S. (2001). Correlation studies between various field parameters and seed quality traits in okra. Seed Research, 29: 84-88.


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EFFECT OF ADHESIVES ON THE STRENGTH PROPERTIES OF PARTICLE BOARD MANUFACTURE FROM SAWDUST OF DIFFERENT WOOD SP ECIES.

D. N. Izekor and I. Edealo

Department of Forest Resources and Wildlife Management, Faculty of Agriculture, University of Benin, P.M.B.1154, Benin City, Nigeria.

ABSTRACT

The study examined the effect of adhesives on the strength properties of particle board manufactured from sawdust of different wood species. The species used for the study were Triplochiton scleroxylon, Nauclea diderichii and Ceiba pentandra. The sawdust from these species were mixed with different three adhesives namely top bond, hard bond and bull bond and compressed under high temperature and pressure to produced particle boards. The results obtained for physical properties of particle board produced from sawdust of Triplochiton scleroxylon after 24 hours of water absorption were 35.80, 42.70 and 44.31%, that of Nauclea diderrichii were 34.28, 38.21 and 41.07% while Ceiba pentandra had mean values of 49.06, 39.54 and 60.34% respectively. The modulus of rupture for particle board produced from sawdust of Triplochiton scleroxylon were 0.19, 0.35 and 0.77 N mm-2, its modulus of elasticity values were 318.20, 531.89 and 1399.30N mm-2. Nauclea diderrichii had modulus of rupture values of 0.22, 0.40 and 0.43N mm-2 while its modulus of elasticity values were 629.37, 1006.07 and 1141.30N mm-2. Similarly, Ceiba pentandra had a modulus of rupture value of 0.40, 0.42 and 0.70N mm-2 while its modulus of elasticity values were 416.94, 1206.03 and 1125.05N mm-2 respectively. The results of analysis of variance on the effects of adhesives on the strength properties of particle board produced from sawdust of different wood species were significant at 0.05% probability level. Therefore, the manufacture of particle board from sawdust should be based on species with known physical and mechanical properties. Key words: Effect, adhesives, strength properties, particle board, wood species.

INTRODUCTION Wood composites describes a unique group of materials that combine two or more physically different materials with the aim of achieving enhanced properties that cannot be attained when each material is used individually. Composites panels such as particle board, oriented strand board, plywood, laminated veneer etc. have become more desirable and attractive to use because they combined material properties in ways not found in natural materials such as lumber. Wood composites have light weight with high stiffness properties and can be engineered to meet specific applications. Adhesives used for binding wood materials in the composites industry include phenol formaldehyde, urea formaldehyde and melamine formaldehyde. Phenol formaldehyde is the most widely used adhesive because of its good mechanical properties and moisture resistance characteristics (Mu, et al., 2004; Lei, et al., 2006).

Particle board is an engineered wood product manufactured from lignocellulosic materials in the form of discrete wood fragments with synthetic adhesive which bond the wood together under heat or pressure (Bowyer, et al., 2007). Several particle board manufacturers use raw materials from industrial wood residues such as sawdust, wood shavings, offcuts and slabs (Nemli and Aydln, 2007; Nemli et al., 2008). A significant amount of log input into the sawmills end up as mill residues in the form of sawdust and wood flakes. These enormous sawmill residues could be utilized as potential raw materials for engineered wood products such as particle board. This study was therefore designed to assess the effect

Izekor, D. N. and Edealo, I. (2017). Effect of Adhesives on the Strength Properties of Particle Board Manufacture from Sawdust of Different Wood Species. Journal of Environment and Sustainable Development, 3(1):102 – 108.


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of adhesives on the strength properties of particle board manufacture from sawdust of different wood species.

MATERIALS AND METHODS The study was carried out at the Forest Product Research and Utilization Department of Forestry Research Institute of Nigeria, Ibadan. The materials used for the study were sawdusts collected from three different timber species namely Triplichiton scleroxylon, Nauclea diderichii and Ceiba pentandra, the adhesives used were Topbond, Hardbond and Bullbond. Instruments used were 2.00 mm sieve and electronic weighing balance. The sawdusts were sieved through 2.00 mm mesh to obtained fine particles of wood flour dried to 2% moisture content. The fine particle of wood flour was used for the production of wood composite.

A weighed portion of the wood flour was thoroughly mixed with adhesive (60% sawdust and 40% adhesive) and fed into the mould to form a mat. The mould was coated with engine oil to prevent sticking and ease removal of the board from the mould. The formed mat was pre-pressed manually in order to reduce its thickness and kept in the hot press for 15minutes at a temperature of 100 – 140°C and a pressure of 1.325N mm-2. The board was thereafter removed from the hot press and allowed to cool before it was demoulded. The board was then trimmed to a dimension of 200mm x200mm and cut into the required test samples using the circular saw. The samples were thereafter kept in a controlled laboratory before testing.

Test for Physical Properties The wood composites of Triplochiton scleroxylon, Nauclea diderichii and Ceiba pentandra measuring 100mm x 100mm x6mm were subjected to physical property test in accordance to ASTM Standard (2005). The parameters tested were thickness swelling, water absorption, linear expansion and shrinkage. The specimen was weighed before and after immersion in water using electronic weighing balance. Water absorption and thickness swelling were evaluated by submerging the product into distilled water. The thickness swelling percentage of the specimen was measured after 24 hours of water immersion.

Water absorption percentage was evaluated using the equation below:

WA7%9 = W: −W<

W:

…………………………… . . ………… . . ……………equation1

Where: WA = Water absorption (%) W1 = Initial weight before treatment W2 = Final weight after treatment Thickness swelling percentage was calculated using the equation below:

TS7%9 = T: − T<

T:x100 ……………………………………… .……………… . equation2

Where: TS = Thickness swelling percentage T1 = Initial thickness before treatment (mm) T2 = Final thickness after treatment (mm)


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Test for Mechanical Properties Test for mechanical properties such as modulus of rupture (MOR) and modulus of elasticity (MOE) were carried out using Hounsfield Tensiometer machine. The MOR and MOE were calculated using the equation below:

ModulusofRupture7MOR9 = 3PL

2bd:…………………………………………equation3

Where: P = load at which the material failed (N) L = board span between the supports (mm) b = width of the board sample (mm) d = thickness of the board sample (mm)

ModulusofElasticity7MOE9 = ∆PL3

4bdF∆s…………………………… .……… . . equation4

Where: P = load that break the board sample (N) L = span of the board sample between the support (mm) b = width of the board sample (mm) d = thickness of the board sample (mm) ∆s = the deflection at the beam center at proportional limit Data analysis All statistical analysis was carried out as a factorial experiment in a completely randomized design by means of one way analysis of variance to determine the significant differences among the treatment means. Separation of means was carried out using Duncan New Multiple Range Test (DMRT). This was done in order to know the difference between means and to chose the best treatment combination from the factors considered. Analysis of variance was carried out to estimate the relative importance of the various sources of variations such as thickness swelling percentage, water absorption, linear expansion, heat test (weight loss, thickness loss, length reduction), modulus of rupture and modulus of elasticity. The main effects considered were those due to adhesive types and wood species

RESULTS AND DISCUSSION Physical Properties The mean values of water absorption obtained for particle board produced from sawdust of Triplochiton scleroxylon were 35.80, 42.70 and 44.31% respectively. Particle board from Nauclea diderichii had a mean value of 34.28, 38.21 and 41.07% respectively while particle board manufactured from sawdust of Ceiba pentandra had a mean value of 49.06, 39.54 and 60.34% respectively after 24 hours of water absorption (Table 1). The mean value obtained for thickness swelling percentage for particle board manufactured from sawdust of Triplochiton scleroxylon were 5.69, 37.06, 29.40% respectively. Particle board from Nauclea diderichii had thickness swelling percentage of 2.89, 28.12 and 15.31% respectively while particle board from sawdust of Ceiba pentandra had thickness swelling percentage of 20.90, 23.70 and 46.28% respectively (Table 1).

The percentage weight loss of particle board manufactured from sawdust of Triplochiton scleroxylon were 0.99, 1.58 and 6.11%.; those of Nauclea diderichii were of 0.91, 5.24 and 7.32% respectively, while particle board of Ceiba pentandra had percentage weight loss of 5.35, 8.15 and 12.10% respectively. The mean value obtained for thickness loss for particle board manufactured from sawdust of Triplochiton scleroxylon were 15.12, 22.10 and 47.20%. Particle board of Nauclea diderrichii has percentage thickness loss of


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22.93, 32.94 and 39.05% while Ceiba pentandra has thickness loss percentage of 17.31, 21.95 and 31.34% respectively.

The results obtained for linear expansion and length reduction of particle board produced from sawdust of the different wood species are also presented in Table 1. The results showed that particle board manufactured from sawdust of Triplochiton scleroxylon had a mean linear expansion of 0.24, 1.09 and 1.17%. Particle board of Nauclea diderichii has a mean linear expansion of 1.21, 1.56 and 2.65% while particle board of Ceiba pentandra has a mean linear expansion of 1.28, 1.75 and 2.87% respectively. Similarly, particle board manufactured from sawdust of Triplochiton scleroxylon had a mean linear reduction of 4.79, 0.44 and 1.47%. Particle board of Nauclea diderichii had a mean length reduction of 1.24, 0.79 and 0.12% while particle board of Ceiba pentandra had a mean length reduction of 1.75, 1.47 and 0.53% respectively (Table 1).

The variations in the values obtained for particle board produced from sawdust of the different wood species using different adhesives could be largely attributed to the adhesive content of the different bond used for its manufacture (Ashori and Nourbakhsh, 2008). Also, the variation in the density of the different wood species used in the manufacture of the particle board has a profound effect on the observed differences in its physical properties (Wong et al., 2003). With respect to water absorption, it was observed that after 2-hour and 24-hour period post immersion, particle board showed increase in percentages of water absorption. Similar results in this regards were observed by Calegari et al., (2007). The highest percentages of water absorption for these particle boards can be related to the high silica content and lower content of lignin present in the wood materials (Calegari et al., 2007). Such components usually interfere with the particle adhesion and gluing processes. The results of the analysis of variance carried out at 5% level of probability to test for the effect of the adhesives on the different wood species with constant mixing ratio on particle were significant. Also, the interaction between adhesives and particle board of the different wood species with constant mixing ratio was significant at 5% level of probability (Table 2).


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Table 1: Physical Properties of Particle Board

Sawdust 60%

Adhesive 40%

Water Absorption (%)

Thickness Swelling (%)

Linear Expansion (%)

Weight Loss (%)

Thickness Loss (%)

Linear Reduction (%)

Hard bond 44.31±0.63 5.69±0.25 0.24±0.12 0.99±0.09 15.12±0.27 4.79±0.15 Triplochiton scleroxylon

Top bond 35.80±0.46 37.06±0.23 1.09±0.40 1.58±0.12 22.10±0.74 0.44±0.05

Bull bond 42.70±0.53 29.40±0.36 1.17±0.45 6.11±0.15 47.20±0.61 1.47±0.57 Hard bond 34.28±0.23 2.89±0.24 1.21±0.60 0.91±0.30 22.93±0.83 1.24±0.90 Nauclea diderichii

Top bond 38.70±0.51 28.12±0.16 1.56±0.12 5.24±0.12 32.94±0.57 0.79±0.45

Bull bond 41.07±0.09 15.31±0.41 2.65±0.32 7.32±0.30 39.05±0.97 0.12±0.06 Hard bond 49.06±0.15 20.90±8.39 1.28±0.12 5.35±0.24 17.31±0.47 1.75±0.70 Ceiba pentandra

Top bond 39.54±0.72 23.70±5.90 1.75±0.21 8.15±0.35 21.95±0.45 1.47±0.85

Bull bond 60.34±0.68 46.28±13.43 2.87±0.76 12.10±0.17 31.34±0.48 0.53±0.08

Table 2: Analysis of Variance for Physical Properties of Particle Board

Source of Variance

Degree of Freedom

Water Absorption

Thickness Swelling

Linear Expansion

Weight Loss

Thickness Loss (%)

Linear Reduction

Wood species 2 1403.23* 3824.24* 7.51* 1650.45* 371.78* 672.35* Adhesives 2 220.14* 931.63* 15.48* 1790.15* 2235.96* 1274.97* W.spp*adhesives 4 764.65* 2452.17* 28.47* 64.32* 386.05* 526.08* Error 18 Total 26


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Mechanical Properties The mean values obtained for the mechanical properties of particle board produced from sawdust of different wood species are presented in Table 4. The mean values obtained for modulus of rupture produced from sawdust of Triplochiton scleroxylon were 0.19, 0.35 and 0.77N mm-2 while the mean values obtained for modulus of elasticity were 318.20, 531.89 and 1399.30 N mm-2 respectively. Similarly, the mean value obtained for modulus of rupture for sawdust produced from Nauclea diderichii were 0.22, 0.40 and 0.43N mm-2 while the mean values of modulus of elasticity for the same species were 629.37, 1006.07 and 1141.30N mm-2 respectively. Also, the mean values obtained for modulus of rupture for particle board produced from sawdust of Ceiba pentandra were 0.40, 0.42 and 0.70N mm-2 while the values obtained for its modulus of elasticity were 416.94, 1206.03 and 1125.05N mm-2 respectively (Table 4).

The variations in the strength properties of the particle board could be attributed to the differences in the adhesive content of the bond use in its production. Similar trend on the strength properties of particle board has earlier being reported (Lehmann, 1970; Ashori and Nourbakhsh, 2008). The authors reported that the strength properties of the particle board increased with increasing adhesive content.

The results of the analysis of variance carried out at 5% level of probability to test for the effect of adhesive on the different wood species were significant. Also, the interaction between the different adhesive and wood species was significant at 5% level of probability (Table 5). Table 4: Mechanical Properties of Particle Board Wood Species Adhesives MOR (N mm-2) MOE (N mm-2) Topbond 0.77±0.16 1394.30±145.43 Triplochiton scleroxylon

Hardbond 0.35±0.12 531.89±288.39

Bullbond 0.19±0.07 318.20±167.38 Topbond 0.40±0.02 1141.30±51.66 Nauclea diderrichii

Hardbond 0.43±0.05 1006.07±7.48

Bullbond 0.23±0.04 629.37±85.83 Topbond 0.42±0.05 1125.00±43.00 Ceiba pentandra

Hardbond 0.70±0.08 1206.03±196.13

Bullbond 1.40±0.02 416.94±27.68 Table 5: Analysis of Variance for Mechanical Properties of Particle Board Source of Variance

Degree of Freedom

MOR MOE

Wood species 2 8.13* 4.42* Adhesives 2 25.70* 65.58* W.spp*adhesives 4 15.82* 10.15* Error 18 Total 26

CONCLUSION

There was a general trend in the pattern of variations on the effect of adhesive on the strength properties of particle board produced from sawdust of the different wood species. The mean values obtained for water absorption, thickness swelling, linear expansion and weight loss percentages were highest in Ceiba pentandra followed by Nauclea diderichii and lowest in Triplochiton scleroxylon. However, thickness loss percentages was highest in particle board


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produced from Triplochiton scleroxylon followed by Nauclea diderichii and lowest in Ceiba pentandra. The highest linear reduction percentage was observed in Triplochiton scleroxylon followed by Ceiba pentandra and lowest in Nauclea diderichii. The modulus of rupture values obtained was highest in particle board produced from sawdust of Ceiba pentandra, followed by Triplochiton scleroxylon and Nauclea diderichii. While modulus of elasticity values was highest in particle board produced from Nauclea diderichii followed by Ceiba pentandra and lowest in Triplochiton scleroxylon. The interaction between the different adhesives and wood species used for the manufacture of particle boards in this study were significant. Therefore, the manufacture of particle board from sawdust should be based on species with known physical and mechanical properties.

REFERENCES

Ashori, A. and Nourbakhsh, A. (2008). Effect of press ime and resin content on physical and mechanical properties of particle board made from the underutilized low-quality raw materials. Industrial Crops and Products 28: 225 – 230.

American Society for Testing and Materials (2005). Standard Terminology for adhesives ASTM International D.907.

Bowyer, J.L; Shmulsky, R. and Haygreen, J.G. (2007). Forest Products and Wood Science In: Chows, S. and Steiner, P. (1979). Comparison of curing and bonding properties of particle board and waferboard type phenolic resins. Forest Products Journal 29 (11): 49 – 55.

Calegari, L., Haselein, C.R; Scaravelli, T.L., Santini, E.J; Stangerlin, D.M. and Gatto, D.A. (2007). Descenpenho fisico-mechanico de paineis fabricados com bamboo (Bambusa vulgari Schr) em combinacao cam Madeira Cerne 13 (1): 57 – 63.

Lei, Y., Wu, Q. and Lian, K. (2006). Cure kinetics of acqueous phenol formaldehyde resins used for orientedstrandboard manufacturing: Analytical Technique. Journal of Applied Polymer Science 100: 1642 – 1650.

Lehmann, W.F. (1970). Resin efficiency in particle board as influenced by density, atomization and resin content. Forest Product Journal 20: 48 – 54.

Melo, R.R. and Del Menezzi C.H.S. (2010). Influencia da massa especifica nas propriedades fisico-mechanicas de paineis aglomerados. Silva lusitana 18(1): 59 – 73.

Mu, Q., Wei, C. and Fengs, S. (2004). Studies on mechanical properties of Sisal fibre/phenol formaldehyde resin in-situ composites. Polymer Composites 30: 131 – 137.

Nemli, G. and Aydln, A. (2007). Evaluation of the physical and mechanical properties of particle board made from the needle litter of Pinus pinaster Ait. Industrial Crops and Products 26: 252 – 258.

Nemli, G., Yiidlz, S., Derya, G.E. (2008). The potential for using the needle litter of Scotch pine (Pinus sylvestris L.) as a raw material for particle board manufacturing. Bioresopurce Technology 99: 6054 – 6058.

Wong, E.D., Yang, P., Zhang, M., Wang, Q., Nakao, T., Li, K.F. and Kawai, S. (2003). Analysis of the effect of density profile on the bending properties of particle board using finite element method. European Journal of Wood and Wood Products 61: 66 – 72.


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IMPACT OF CRUDE OIL SPILLAGE ON MAIZE PLANT ( Zea mays L.) IN UPENEKANG IN IBENO LOCAL GOVERNMENT AREA OF AKWA IB OM

STATE, NIGERIA

Ndeh, E. S., Okafor, J. O., Akpan, U. G. and Olutoye, M. A. Department of Chemical Engineering, School of Engineering and Engineering Technology, Federal University of Technology, Minna, Niger State, Nigeria.

[email protected]

ABSTRACT This study was carried out to find out the effect of crude oil spill on corn samples obtained from oil spill farms in Upenekang in Ibeno, Akwa Ibom State. The samples were obtained from different distances 10, 23, 30, 46 and 52m in the oil spilled farm. The effects of the crude oil spill on nutrient content of corn samples as well as the concentrations of toxic heavy metal pollutants were investigated. The concentrations of Zinc, lead, copper, chromium, iron and manganese metals analyzed for in this work using standard methods were high in the corn samples obtained from the oil spill farm at the spill site. Heavy metal concentrations of zinc, copper, chromium, iron and manganese observed in the corn samples at different distances at the spill farm were all higher than 2.04, 1.97, 0.02, 0.46 and 0.06mg/kg respectively observed in the control sample indicating oil spill contamination in the corn samples obtained at the spill farm. A one-way analysis of variance (ANOVA) showed no significant effect of distance from which samples were collected on the level of heavy metal concentrations in the corn samples collected in the study area.

Keywords: Crude oil spill, Upenekang, Corn, heavy metals, ANOVA.

INTRODUCTION Corn (Zea mays L.) is a cereal crop cultivated for food, feed and industrial purposes (United States Agency for International Development, 2010). It is one of the main staple cereals in Nigeria (Oyewo, 2011), and an important source of carbohydrate in human food. A useful quality of Vitamin C can be derived from corn while the yellow grain contains vitamin A (Agoda et al., 2011). Industrially, corn is used as livestock feed and also serves as raw material for starch, flour and alcohol production (Oyewo, 2011). Corn contributes enormously to the growth of agricultural sector.

Crude oil spills are caused by a multitude of factors in the Niger Delta. Oil spills constitute a unique class of environmental problem. The United State Environmental Protection Agency, (2000) recognizes oil pollution as resulting from accidental oil spills and natural oil seepage. In essence, there are diverse causes of oil spills. According to Ahman (1997) in a paper at the opening session of a workshop during an Environmental Day states that the “immediate causes of the spillage range from break up or damage to oil tankers or storage vessels to sabotage by aggrieved people”. In addition to blowout, local oil spills can occur as a result of improper handling or mishaps such as burst pipes or from continuous seepage from the jetties during the loading of vessels. Poorly maintained infrastructure fails under high pressure. Accidents may occur and pipelines running over ground get ruptured. The burgeoning trade in stolen oil means that local people tap into lines and wells damaging them or leaving them leaking. Sabotage of pipes is common, often by local people hoping to get cash compensation. Drilling accidents have been a growing concern as more areas of the continental shelves are opened to drilling. Normally, the drill hole is loned with a steel casing to prevent lateral leaking of oil, but occasionally, the oil finds an escape route before the casing is complete. This is what happened in Santa Barbara in 1979 when a spill produced 200–square kilometres (about 80-square miles) oil slick. Alternatively, drillers may unexpectedly hit a high-pressure pocket that causes a blow out (Carla, 2002).

Ndeh, E. S., et al. (2017). Impact of Crude Oil Spillage on Maize Plant (Zea mays L.) in Upenekang in Ibeno Local Government Area of Akwa Ibom State, Nigeria. Journal of Environment and Sustainable Development, 3(1): 109 – 114.


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Spills may also be due to failing equipment, in which case oil companies are clearly responsible. But where the spillage is attributed to sabotage, the companies and government blame local people and criminal gangs. Oil spills in Nigeria occur due to corrosion of pipelines and tankers (accounting for 50% of all spills), sabotage (28%), and oil production operations (21%, with 1% of the spills being accounted for by inadequate or non-functional production equipment (Nwilo and Badejo, 2007). The reason that corrosion accounts for such a high percentage of all spills is that as a result of the small size of the oilfields in the Niger Delta, there is an extensive network of pipelines within the fields, as well as numerous small networks of flow lines (the narrow diameter pipes that carry oil from wellheads to flow stations) allowing many opportunities for leaks. The transport of huge quantities of oil creates opportunities for major oil spills through a combination of human and natural hazards (Nwilo and Badejo, 2007).

Oil spill on crops causes severe damage to plant community due to high retention time of oil occasioned by limited flow. Crops like pepper and tomatoes may wilt and die off due to blockage of stomata by oil spill thereby inhibiting photosynthesis, transpiration and respiration. In fact, germination, growth performance and yield of these crops are stifled by oil spillage. Accumulation of metal pollutants in the leaves and roots of higher plants have been reported by Bargali et al. (2003). Similarly, Singh and Mishra (1987) observed that in aquatic habitats free oil emission coats and destroys algae, zooplanktons and interferes with the photosynthetic process and kills different species of fish. Also soluble poisonous fractions of the oil such as toluene kills different fish samples, aquatic birds and oysters while accumulation of refinery effluents prevents germination and growth of plants (Bossert and Bartha, 1984).

Plants that are sensitive to soil contaminants are often used as bio-indicators of soil contamination. Among crop species recommended by United State Environmental Protection Agency (USEPA) as bio-indicators are radish (Raphanus sativus), carrot (Daucus carota), rice (Oryza sativa), turnip (Brassica rapa), soybean (Glycine max), oats (Avena sativa), cabbage (Brassica campestri), corn (Zea mays), tomato (Lycopersicon esculentum), bean (Phaseolus aureus, Phaseolus vulgaris), onion (Allium cepa), sorghum (Sorghum bicolor) and lettuce (Lactuca sativa) (Fletcher, 1991). Seed germination and seedling growth are sensitive to soil contamination or pollution by toxic substances (Asli and Houshmandfar, 2011). The most notable effect of soil contamination on seed germination and seedling growth is reduced elongation of the primary root (Ogbo, 2009). Thus, seedling growth is often used as an indicator of plants’ ability to survive environmental pollution, including that of hydrocarbon soil contamination (Njoku et al., 2009).

Alaimo et al. (2000) reported that oil spills have degraded most agricultural lands in the state and turned hitherto productive areas into wastelands. According to Okonta and Douglas (2001), crude oil contaminated soil have adversely affected plant growth. The higher the level of soil contamination with oil, the worse the detrimental effects of oil on plants growth. Crude oil has also been reported to adversely affect crops even at low soil contamination concentration (Akujobi et al., 2011).

MATERIALS AND METHODS Study Site: The study area was Upenekang in Ibeno Local Government Area of Akwa Ibom State located in the Niger Delta region of Nigeria. The Niger Delta region consists of nine states which make up the south-south geopolitical zone in Nigeria, of which Akwa Ibom State is a part. It extends over an area of about 7.5% of Nigeria’s total landmass. The coastline extends for 560km, roughly two-thirds of the entire coastline of Nigeria (NDDC, 2004). Ibeno clan consists of twenty-three villages. It stretches about forty kilometres from Ikot-Abasi in the West to the mouth of Cross River in the East. It is bordered by Oron and Eket in the North East and by Eket Central and Oniong Eket in the North West, as well as


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by the Atlantic Ocean in the South. It lies between the latitudes 8o.00 and 8o.15 east of the Greenwich Meridian. It is located in the transitional zone between the swamp forest and the rainforest region. Ibeno is divided into two sub areas by the Qua Iboe River. The area across the river is made up of six villages. Most of the villages are further separated from one another by small creeks and marshlands. The area lies about ten metres above sea-level and houses occasional creeks and sand banks. The original thick mangrove swamp is giving way in some places to scanty bushes due to the effect of pollution (Etuk, 1977).

The Qua Iboe River and the Atlantic Ocean constitute natural waterways which is the most important traffic route in the area. The mouth of the Qua Iboe River is about 100 meters wide and its estuary is about 39 kilometres wide at its entrance. The physical conditions of Ibeno significantly influence the economic activities of the people; the activities of the oil companies have also influenced the economic life of the people. The principal occupation of the people is agriculture, such as farming and fishing. Oil spillage is the main hazard in this area.

Collection of Samples: Corn samples were obtained at distances 10, 23, 30 46 and 52m in oil contaminated farm. The corn samples obtained outside the spill site served as the control samples. All the corn samples obtained at the study area were properly packaged in polybags and taken to laboratory for analysis.

Determination of Sodium (Na), Potassium (K), Calcium (Ca) and Magnesium (Mg): A standard solution of Na, K, Ca and Mg were prepared from the corn samples. The prepared corn samples were aspirated using a flame photometer (GallenKamp BKL - 210) with the filter of Na, K, Ca and Mg in place and the readings of elements in the sample solutions were recorded as described by Salami and Egwin (1997).

Determination of Heavy Metals (zinc, lead, copper, chromium, iron and manganese): Corn samples were cut into pieces and dried in an oven. It was then crushed using a grinder and sieved into powder form using sieves. 3g of each sample was weighed with electronic weighing balance into a 250ml beaker. 10ml of hydrochloric acid was measured using measuring cylinder into the beaker containing the samples and kept for 2-3 minutes. Then 30ml of Nitric Acid was measured also and added into the beaker of the sample. The beaker was then heated on a hot plate for about 10 – 15 minutes at a temperature of between 65°C to 70°C to digest in the fume cupboard and the beaker removed from the hot plate and kept to cool (Ademoroti, 1996). After cooling, the digested sample was filtered into another beaker using funnel with filter paper, distilled water was added into the filtrate to make up to 100ml and ready for analysis. The digested solutions were analyzed for the presence of zinc, lead, copper, chromium, iron and manganese using atomic absorption spectrophotometer (Unicam 939 AAS) with different lamps in position (Ademoroti, 1996).

Statistical Analysis: Results were subjected to analysis of variance (ANOVA) with the least significant difference and significant means compared at 0.05 level of probability level as described by Oyeka, (1996).

RESULTS AND DISCUSSION The characterization of the corn samples obtained from the crude oil spilled farmland at distances 10, 23, 30, 46 and 52m were observed to be low in nutrients (K, Ca, Mg and Na) concentrations but high in heavy metals (Zn, Pb, Cu, Cr, Fe and Mn) concentrations when compared with the control corn sample (Table 1) as a result of crude oil spill on the farmland. Corn samples obtained at 10, 23, 30, 46 and 52m had zinc concentrations of 27.43, 36.88, 18.18, 11.62 and 14.19mg/kg respectively and higher than 2.06mg/kg observed in the control sample. Lead concentrations of 10.45, 7.35 and 5.88mg/kg were observed in corn samples at distances 10, 23 and 30m while its concentration at 46m, 52m and the


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control sample was not detected indicating that the oil spill did not affect the soil spot where these corn plants were grown. Also, copper concentration in the corn samples obtained at 52m in the oil spilled farm was not detected while those obtained at 10, 23, 30 and 52m were 23.94, 11.85, 6.31 and 15.82 mg/kg which were higher than 1.97 mg/kg observed in the control sample. Chromium, iron and manganese also followed the same trend (Table 1) with high concentrations in the corn samples of the oil spilled farm. However, low concentrations of chromium were observed in the control sample.

Table 1: Heavy Metal concentrations in Corn samples Obtained at different distances from oil spilled farm in Upenekang.

Samples Distances (m)

K mg/kg

Ca mg/kg

Mg mg/kg

Na mg/kg

Zn mg/kg

Pb mg/kg

Cu mg/kg

Cr mg/kg

Fe mg/kg

Mn mg/kg

S1 10 4.42 0.82 0.62 1.08 27.43 10.45 23.94 29.04 15.63 9.02

S2 23 0.88 0.53 0.38 1.43 36.88 7.35 11.85 18.97 2.06 4.71

S3 30 0.57 1.61 3.05 2.41 18.18 5.88 6.31 10.78 8.11 5.69

S4 46 2.61 8.49 11.70 5.53 11.62 ND 15.82 ND 2.67 1.80

S5 52 3.60 5.79 7.12 1.71 14.19 ND ND 1.38 14.91 2.32

S6 Control 21.04 47.51 38.00 18.21 2.06 ND 1.97 0.02 0.46 0.06

Potassium, calcium, magnesium and sodium contents in corn samples were low when compared with the control sample. This decrease in the concentration of these nutrients essential for the corn growth could be attributed to contamination of the soil with crude oil spill which polluted the soil and also retards nutrient uptake of the corn (Table 1). The spilled oil pollutes the soil and renders it less useful for agricultural production and also affects soil microbial activities (Siddiqui and Adams, 2002). The effects of crude oil on the growth and performance of plants have been reported to be disastrous to agricultural production (Nicolloti and Eglis, 1998). Some of the effects include the interference of plant uptake of nutrients by crude oil and the unfavourable soil conditions which hinders soil microbial activities due to pollution by crude oil (Gudin and Syratt, 1975). It has been reported that plants and soil microbes compete for little nutrients available in soils that are low in nutrients like that polluted with crude oil which suppress the growth of plants (Baker, 1970). In this study, corn samples obtained from the oil spilled farm were observed to be low in nutrient concentrations when compared with the corn sample obtained from non-oil contaminated farm. Crude oil contaminated soil inhibit and retard plant growth due to high content of heavy metal presence in the soil and the plant (Wang et al., 2004). Okonta and Douglas (2001) also reported that crude oil contaminated soil adversely affected plant growth in their study area. The higher the level of contamination by crude oil, the greater it’s detrimental effects on plants growth (Akujobi et al., 2011). Analysis of variance carried out on the results of the corn characterization is presented in Table 2. Table 2: One-Way analysis of variance of influence of distance away from spill on the level of Heavy Metals in Corn samples obtained from the study area Source of variance SS df MS F Between group Within group

563.75

5953.63

5

54

112.75

110.25

1.02

Total 6517.38 59


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Table 2 shows that the calculated F-value of (1.02) was obtained after testing for significance at 0.05 alpha level with 5 and 54 degrees of freedom. The calculated F-value (1.02) was less than the table F-value (2.45). Hence, the result was not significant, and this means that even though there exists difference in the level of heavy metals in corn samples obtained from the study area (Upenekang) spill site based on different distances (10m, 23m, 30m, 46m, 52m and that of the control group), the differences among the different distances are not significant and this means that there is no significant influence of distance away from spill on the level of heavy metals in corn samples obtained from the study area (Upenekang) spill site.

CONCLUSION Assessment of nutrients content (K, Mg, Ca and Na) in corn samples obtained from different distances 10, 23, 30, 46 and 52m in the oil spill farm were observed to be low but high in heavy metals (Zn, Pb, Cu, Cr, Fe and Mn) when compared to the control sample. These observations are indicators that the corn samples at the spill farm were contaminated and unsuitable for consumption as negative health implications may be observed over a period of time. Obviously, animals that graze on these corn plants would take up these heavy metals resulting in accumulation into the animal tissues, which man consumes. This indirectly may affect human health. From the analysis of variance, it was observed that there is no significant influence of distance away from spill on the level of heavy metals in corn samples obtained from the study area.

REFERENCES Ademoroti, C. M. A. (1996). Standard Methods for Water and Effluents Analysis, Foludex

Press Ltd, Ibadan, Nigeria. pp. 36-80. Agoda, S., Atanda, S., Usanga, O., Ikotun, I. and Isong, I. (2011). Post Harvest Food Losses

Reduction in Maize Production in Nigeria. African Journal of Agricultural Research, 6, 4833-4839.

Ahman, H. (1997). Floods. A Paper Presented at the Opening session of Workshop on Management of the Environment at University of Nigeria, Enugu Campus.

Akujobi, C., Onyeagba, R., Nwaugo, V. and Odu, N.N. (2011). Protein and Chlorophyll Contents of Solanum Melongena on Diesel Oil Polluted Soil Amended with Nutrient Supplements. Current Research Journal of Biological Sciences, 3 (5), 516-520.

Alaimo, M., Dongarra, G., Melati, M. R., Mona, F. and Varrica, D. (2000). Recognition of Environmental Trace Metal Contamination using Pine Needles as Bioindicatiors. Environ. Geol. 39 (8), 914-924.

Asli, D. and Houshmandfar, A. (2011). Response of Seed Germination and Seedling Growth of Safflower and Corn to Gasoline and Diesel Fuel Mixture. Advances in Environmental Biology Journal, 5 (1), 81-86.

Baker, J. M. (1970). The Effects of Oils on Plants. Environmental Pollution. 1:27-44. Bargali, R., Monaci, F. and Agnorelli, C. (2003). Oak Leaves as Accumulators of Airborne

Elements in an Area with Geochemical and Geothermal Anomalies. Environ. Pollut. 124: 321-329.

Bossert, I. and Bartha, R. (1984). The Fate of Petroleum in Soil Ecosystem. In: Petroleum Microbiology (ed. Atlas, R.M.) Macmillan Publishers, N.Y., pp: 435- 475.

Carla, W. M. (2002). Environmental Geology. Fifth Edition. McGraw Hill Higher Education, U.S A.308p.Ofomata, G. (1997). The Oil Industry and the Nigerian Environment Environmental Review Vol.1, No.1.

Etuk, U. U. (1977). The Impact of Mobil Oil Company on the Economic Life of Eket People. Unpublished BSc. Thesis, Department of Sociology. University of Calabar.


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Fletcher, J. (1991). A Brief Overview of Plant Toxicity Testing, In: Plants for Toxicity Assessment’ Goruch, J. W., Lower, W. R., Lewis, M. A., Wang, W. ASTM, Philadelphia, PA.

Gudin, C. and Syratt, W. (1975). Biological Aspects of Land Rehabilitation Following Hydrocarbon Contamination. Environmental Pollution. 8,107-112.

Nicolotti, G. and Eglis, S. (1998). Soil contamination by crude oil: impact on the Mycorrhizosphere and on the Revegetation Potential of Forest Trees. Environmental Pollution. 99, 37-43.

Njoku, K., Akinola, M. and Ige, T. (2009). Comparative Effects of Diesel Fuel and Spent Lubricating Oil on the Growth of Zea Mays (Maize). American-Eurasian Journal of Sustainable Agriculture, 3, (3), 428-434.

Nwilo, P. C. and Badejo, O. (2007). Impact of oil spills Along the Nigerian Coast. Dept. of Surveying and Geo informatics, Faculty of Engineering, Unilagos Akoka-Lagos, Nigeria.

Ogbo, E. M. (2009). Effect of Diesel fuel Contamination on Seed Germination of Four Crops Plants- Arachis hypogeal, Vigna unguiculata, Sorghum bicolour and Zea Mays. African Journal of Biotechnology, 8, (2), 250-253.

Okonta, I. and Douglas, O. (2001). Where Cultures Feasts: Forty Years of Shell in the Niger Delta. Benin: ERA/FOEN.

Oyeka, C. A. (1996). An Introduction to Applied Statistics, 7th Edition, Nober Avocation Publishing Company, Enugu, pp. 218-246.

Oyewo, I. O. (2011). Technical Efficiency of Maize Production in Oyo State. Journal of Economics and International Finance, 3, 211-216.

Siddiqui, S. and Adams, W. (2002). The Fate of Diesel Hydrocarbons in Soils and Their Effects on Germination of Perennial Ryegrass. Environmental Toxicology. 17 (1): 49-62.

Singh, K. K. and Mishra, L.C. (1987). Effects of Fertilizer Factory on Soil and Crop Productivity. Water Air Soil Pollution, 33, pp. 309-320.

United States Agency for International Development (USAID), (2010). Package of Practices for Maize Production. Washington DC, 1-23.

United State Environmental Protection Agency (USEPA), (2000). Introduction to Phytoremediation. USA: Environmental Protection Agency, p. 5.

Wang, W., Wang, A., Chen, L., Liu, Y. and Sun, R. (2002). Effects of pH on Survival, Phosphorus concentration, Adenylate Energy Charge and Na+, K+ ATPase Activities of Penaeus chinensis Osbeck Juveniles, Aquatic Toxicology, 60, 75-83.


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SPATIO-TEMPORAL VARIATIONS IN THE BENTHIC MACRO-INVERTEBRATE COMMUNITIES OF STUBBS CREEK, SOUTH-EAS TERN

NIGERIA

Obot, O. I1* and Nicholas Eteobong2 1Department of Fisheries and Aquatic Environmental Management, University of Uyo,

PMB 1017, Akwa Ibom State, Nigeria. 2Nigeria Institute for Oceanography and Marine Research, 3 Wilmot Point Road,

Victoria Island, Lagos State, Nigeria. *Corresponding author: [email protected]; +2347081554411

ABSTRACT Benthic macro-invertebrates provide a more accurate understanding of changing aquatic conditions than chemical and microbiological data. Despite their importance in the aquatic environment, particularly in the Stubbs creek, information on their distribution, abundance and seasonality in relation to its environmental quality is still lacking. The benthic macro-invertebrates of Stubbs creek, was investigated from September 2011 to August 2013. Using a Van-veen grab, samples were collected from three different stations along the creek. Five classes of benthic macro-invertebrates were encountered: Bivalvia (86.70%), Clitellata (4.61%), Maxillopoda (3.90%), Gastropoda (2.48%), and Insecta (2.31%). Only, Gastropoda showed a significant seasonal variation (p<0.05). Of the ten species of benthic macro-invertebrates encountered, Pisidium casertanum was the most frequent; occurring in all the months throughout the sampling period while Iphigenia laevigata and I. rostrata were the least frequent; occurring just once (May, 2013 and November, 2012 respectively) each throughout the study period. Gammarus lacustris, Hexacylloepus sp and Tubifex tubifex were present in all the stations. Station 3 had the lowest values for all the diversity indices. Shannon-wiener diversity and species evenness were highest at station 2 while Margalef species diversity was highest at station 1. Low Margalef species diversity (1.125-1.2) across the stations is an indication of impact of perturbation stress on the benthic macro-invertebrate communities. The presence of T. tubifex in all the stations indicated organic pollution from anthropogenic sources. This study recommends that government and organized private sectors operating in this environment, adopt ecological surveillance and mitigation measures in order to prevent further pollution and guarantee restoration. Keywords: Benthic macro-invertebrate, frequency, abundance, Stubbs Creek, Nigeria

INTRODUCTION Benthic macro-invertebrates, otherwise called benthos are animals without backbone that inhabit the bottom substrate (e.g. sediments, debris, logs, aquatic macrophytes, filamentous algae) in aquatic habitat for at least part of their life cycle (Ajao and Fagede, 2002). They provide a more accurate understanding of changing aquatic conditions than chemical and microbiological data (Ravera, 2000; Ikomi et al., 2005). Macro benthic invertebrates are important and integral part of aquatic ecosystem as they form the basis of the trophic level and any negative effects caused by pollution in the community structure can in turn affect trophic relationships. These can include those that feed on them directly or indirectly such as fish and bird population respectively (Sharma and Chowdhary, 2011).

Benthic macro-invertebrates include arthropods, crustaceans, molluscs, aquatic worms and larval forms of aquatic insects. They form part of the aquatic food chain and are used to assess water quality (Nkwoji et al., 2010). Macro-invertebrates are used as indicators of pollution as invertebrate community change in response to changes in physicochemical factors and available habitats (Sharma and Chowdhary, 2011). The structure of benthic

Obot, O. I and Eteobong, N. (2017). Spatio-Temporal Variations in the Benthic Macro-Invertebrate Communities of Stubbs Creek, South-Eastern Nigeria. Journal of Environment and Sustainable Development, 3(1): 115-124.


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communities in running water ecosystem is determined by a dynamic array of biotic and abiotic factors (Austen and Widdicombe, 2006). Olomukoro and Egborge (2003) reported that species of polychaetae were restricted to a particular station of the same river because their occurrence may be governed by niche preference and feeding habit. Studies on benthos of Nigerian creeks include; Edokpayi et al. (2010) on Ogbe creek, Emmanuel and Ogunwebmo (2010) on Abule-Agege creek, George et al. (2010) on Okpoka creek, Olomukoro and Azubuike (2009) on Ekpan creek and Woke and Aleleye-Wokoma (2007) on Elechi creek. The Qua-Iboe River estuary is located on the southeastern coast of Nigeria where it empties into the Atlantic Ocean. The estuary is associated with many creeks and several channels; notable among them is Stubbs creek. Despite the importance of benthic macro-invertebrate in the aquatic environment, particularly in the Stubbs creek, information on the distribution, abundance and seasonality of benthic macro-invertebrates in Stubbs creek sediment in relation to its environmental quality is still lacking. This study is aimed at bridging that gap.


Study Area Stubbs creek is located within latitude 4.57oN and Longitude 7.98oE. It is a tidal creek. The invasive nipa palm (Nypa fruticans) has overtaken the mangrove of this creek. Human activities going on within and around this creek include sand mining, farming, fishing, laundry, disposal of excreta, bathing, swimming and timber transportation. Three sampling stations were chosen (Fig.1). Stations 1 and 2 were at areas of increased human perturbation, while station 3 was a relatively calm spot. Station 1 is located at the point where Stubbs creek empties into Qua-Iboe River (4o33'47"N and 7o59'7"E). The vegetation along the creek is mainly Nypa fruticans. Station 2 is located along Stubbs creek (4o34'25"N and 7o59'17"E). From this point, farming lands with human settlements could be observed. Station 3 is located along Stubbs creek (4o33'22"N and 7o59'9"E). Although close to a bridge, the station was observed to be serene.

Figure 1: Map of sampling stations (1-3) Sample Collection Monthly sampling at the stations for 24 months (September 2011 – August 2013) was carried-out. Benthic samples were collected with the aid of a Van Veen grab of 0.5 m2


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surface area. At each station, two grab hauls were collected, sieved with mesh sizes 0.5 mm (Holme and Melntyre, 1984) and stored in a pre-labelled container. It was then fixed with 10% formalin for further analysis in the laboratory.

In the laboratory, sorting, counting and identification with microscope was carried out. Identification keys such as Day (1967) and Pennak (1978), WHO (World Health Organization) (1984), and Brown, (1994) were used for identification of samples. Rainfall data was obtained from the Meteorological Unit, Department of Geography, University of Uyo, Nigeria. Statistical analyses: The means, ranges, percentages and one way Analysis of Variance (ANOVA) at probability level of p<0.05 of the data generated were determined using SPSS (version 19) package. Microsoft Excel 2010 was used for graphical illustrations. The community structure (Margalef species diversity, Shannon-wiener index and species evenness) was analysed using PAST (version 2.12) software.

RESULTS The monthly variation of benthic macro invertebrate in Stubbs creek sediments is presented in Table 1. Pisidium casertanum was recorded in all the months throughout the sampling period, with the lowest value of 10 in June, 2013 and highest value of 34 in March and September 2012. It was the most frequent, throughout the study period, followed by Gammarus lacusta, which was present during thirteen of the twenty-four months. Iphigenia laevigata and I. rostrata were the least frequent, occurring just once (May, 2013 and November, 2012 respectively) each throughout the study period.


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Table 1: Monthly variation of macro-invertebrates in Stubbs creek

Species

Sep-11 Oct Nov Dec Jan-12 Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Jan-13 Feb Mar Apr May Jun Jul Aug-13

Anodonta grandis 4 4 2 0 0 0 0 2 0 2 0 0 8 0 0 0 0 0 0 0 0 0 0 0

Iphigenia laevigata 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0

Iphigenia rostrata 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0

Pisidium casertanum 46 54 40 24 50 34 68 26 30 28 62 56 68 50 26 44 34 32 26 42 28 20 34 30

Tubifex tubifex 2 0 2 2 0 2 0 0 0 2 0 0 0 0 0 0 0 6 20 10 6 0 0 0

Tympanotomus fuscatus 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0

Tympanotomus radula 0 2 2 0 4 0 0 0 0 0 0 0 0 0 8 0 0 2 2 0 0 0 0 0

Hexacylloepus sp 0 0 0 0 0 0 0 0 2 4 2 0 0 0 0 0 4 2 0 0 0 0 0 0

Hydropsyche sp. 0 0 0 0 0 0 2 0 6 0 0 0 0 0 0 0 2 0 0 0 0 2 0 0

Gammarus lacusta 2 0 0 6 2 8 0 6 0 2 2 0 0 4 2 0 2 2 2 0 4 0 0 0

JOFESD Vol. 3 No. 1 Published March, 2017

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Table 2 is the spatial variation of benthic macro-invertebrates in the study area. Tubifex tubifex, Hexacylloepus sp and Gammarus lacusta were present in all the sampling stations. Pisidium casertanum was the most abundant species but occurred only in station 3. It was followed by Tubifex tubifex and Gammarus lacusta.

Table 3 gives the relative class abundance and species composition trend of benthic macro-invertebrate in Stubbs creek. Class bivalvia was the most abundant and constituted 86.7 % while insecta was the lowest abundant and constituted 2.31 %. Clitellata and maxillopoda had the lowest species composition of 10 % each, while Bivalvia had the highest species composition of 40%.

Table 2: Spatial variation of macro-invertebrates in Stubbs creek Class Family Species Station 1 Station 2 Station 3 Bivalvia Unionidae Anodonta grandis 2 18 2 Bivalvia Donacidae Iphigenia laevigata 2 0 0 Bivalvia Donacidae Iphigenia rostrate 0 0 2 Bivalvia Spaeriidae Pisidium casertanum 0 0 952 Clitellata Tubificidae Tubifex tubifex 32 10 10 Gastropoda Potamididae Tympanotomus fuscatus 0 0 8 Gastropoda Potamididae Tympanotomus radula 0 0 20 Insecta Elemidae Hexacylloepus sp 6 4 4 Insecta Hydropsychidae Hydropsyche sp. 0 12 0 Maxillopoda Gammaridae Gammarus lacusta 14 20 10

Table 3: Number and Percentage Composition of Macro-Benthos Class in Stubbs creek Taxa Total Number

(No./0.5m2) Relative Abundance

(%) Total Number

of Species Species Composition (%)

Bivalvia 978 86.7 4 40

Clitellata 52 4.61 1 10

Gastropoda 28 2.48 2 20

Insecta 26 2.31 2 20

Maxillopoda 44 3.9 1 10

Figure 2 is a graphical presentation of rainfall for the period of study. The rainfall data obtained from the Meteorological unit, Department of Geography, University of Uyo, Nigeria, showed a seven months wet season period, which stretched from April to October, and a dry season extending from November to March.

Figure 2: Rainfall data during the period of study obtained from the Meteorological Unit, Department of Geography, University of Uyo

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Figure 3 is a graphical presentation of class seasonal variation of benthic macro-invertebrates in Stubbs creek. Although there were differences in the occurrences of the benthic macro-invertebrates with seasons, only gastropoda showed a significant seasonal variation (p<0.05). Bivalvia, insecta and maxillopoda were more frequent in the wet season while clitellata and gastropoda were more frequent in the dry season.

Figure 4 presents the relationship between total number of individuals per station and total number of species per station. Station 3 had the highest number of individuals and species. Station 1 had the lowest number of individuals while stations 1 and 2 had the same number of species.

Figure 4: Relationship between number of individuals and number of species of benthic macro-invertebrates in Stubbs creek Figure 5 presents the Shannon-wiener diversity values, Margalef species diversity values and species evenness values for each station. Station 3 had the lowest values for all the diversity indices. Shannon-wiener diversity and species evenness were highest at station 2 while Margalef species diversity was highest at station 1.

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Figure 3: Class seasonal variation of benthic macro-invertebrates in Stubbs creek


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Figure 5: Relationships between the diversity indices of benthic macro-invertebrates in Stubbs creek

DISCUSSION Low taxa number characterized the benthic macro-invertebrate composition of Stubbs creek during the study. This is not unusual of tropical waters (Edward and Ugwumba, 2011). Nkwoji et al. (2010) reported 9 species from 8 genera, 4 classes and 2 phyla from Lagos lagoon, Andem et al. (2012) recorded 10 species from Ona River, Ogidiaka et al. (2012) reported 6 species in 4 phyla from Ogunpa River and Saliu and Ekpo (2006) reported 4 species from Ogbe creek.

However, high taxa number has been reported, Zabbey (2002) reported 30 taxa belonging to 20 families and 5 classes of macro invertebrates in Woji creek, Olomukoro and Azubuike (2009) reported 19 taxa belonging to 4 groups from Ekpan creek, Umeozor (1995) recorded 23 species in the New Calabar River and George et al. (2010) reported 19 species from 6 classes and 4 phyla from Okpoka creek. Low species diversity has been attributed to some physico-chemical conditions of water such as fast flow, high pH, low dissolved oxygen and low conductivity. These factors probably cause disruption of life cycle, reproductive cycle, food chain and migrations of imposed physiological stress on even the tolerant macroinvertebrates (Adakole and Annune, 2003). Also, Umeozor (1995) in his study on the New Calabar River reported that the important factors governing the occurrence and distribution of macro-invertebrates are the physico-chemical qualities of the water and the nature of immediate substrate. Any severe alterations of these factors will substantially affect the macroinvertebrtae community. Results from this study show that the class Bivalvia was the most abundant (86.7 %) with Pisidium casertanum accounting for 97.34 % of the class Bivalvia and 84.40 % of the total macro-invertebrates. The abundance of bivalvia may be due to their ability to tolerate physical and chemical variations in the environment and are usually found in broad range of habitants (Ajao and Fagade, 2002). Pisidium casertanum was only found in station 3. Gammarus lacustris, Hexacylloepus sp and Tubifex tubifex were found in all the stations. The presence of Tubifex tubifex in all the stations suggests organic pollution from anthropogenic source (Andem et al., 2012). The presence of a particular species does indicate the suitability of the environment for its growth and development and the absence of any species does not necessarily indicate the unsuitability of the environment, instead the absence of an entire group of species with same ecological needs indicate adverse environmental conditions (Rashid and Pandit, 2014). Stations (1 & 2) lacked some group of organisms found in station 3 indicating that they were perturbed from anthropogenic activities. The overall differences observed in the abundance and species richness may be due to the slight variations in the physico-chemical and sediment quality of the aquatic habitat (George et al., 2010). Wood (1987) explained that species have to contend with environmental

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changes and biological interactions, which may produce significant alterations in overall community structure. Again, variability in the occurrence and distribution of organisms in a habitat has been linked with recruitment and reproduction pattern which vary among different organisms (Okorafor et al., 2013).

The occurrence of relatively higher taxa and individuals in station 3 is an indication of lower degree of anthropogenic activities at this station compared to other stations. Species composition was highest at station 3 but the same at stations 2 and 1. The differences in species composition recorded could be attributed to the ecological diffences of the different geographical locations and depth of investigation (George et al., 2010). Highest Margalef species diversity (d) of 1.2 recorded in this study is an indication of low diversity of macro-benthos in the creek. This is a further indication of impact of perturbation stress on the macro-invertebrate benthic communities (Saliu and Ekpo, 2006). According to Shannon-wiener diversity water quality index, the values obtained during the present study were more than 1.0 in stations 1 and 2 thus confirming the pollution levels of these stations (Adjarho et al., 2013). Station 3 is a relatively unimpacted site and is reflected in the number of individuals and species recorded in that station. Station 3 recorded the highest number of individuals and species for the period of study. This in turn is a good index for assessing the health of that station (Nkwoji et al., 2010b). There was no significant seasonal variation (p<0.05) in the abundance of classes of benthic macro-invertebrates except for gastropoda. Clitellata and gastropoda were more frequent in the dry season. This was in consonance with the report by Ajao and Fagade (2002). They reported that, of the 42 benthic fauna observed in Lagos Lagoon, the highest number of species (41) was recorded during the dry season.


Five classes of benthic macro-invertebrates were encountered in the creek during the study. Bivalvia (86.70%), Clitellata (4.61%), Maxillopoda (3.90%), Gastropoda (2.48%), and Insecta (2.31%). Low Margalef species diversity (1.125-1.2) across the stations is an indication of impact of perturbation stress on the benthic macro-invertebrate communities. Also the presence of T. tubifex in all the stations indicated organic pollution from anthropogenic sources. Hence, the aquatic ecosystem of Stubbs creek can be said to be an environment under stress with organic pollution from anthropogenic sources. This study recommends that government and concerned organized private sectors operating in this environment, adopt ecological surveillance and mitigation measures in order to prevent further pollution and guarantee restoration.

REFERENCES Adakole, J. A. and Annune, P. A. (2003). Benthic macroinvertebrates as indicators of

environmental quality of an urban stream, Zaria, Northern Nigeria. Journal of Aquatic Science, 18(2): 85-92.

Adjarho, U. B., Esenowo, I. K. and Ugwumba. A. A. A. (2013). Physico-chemical Parameters and Macro-invertebrates Fauna of Ona River at Oluyole Estate, Ibadan, Nigeria. Research Journal of Environmental and Earth Sciences, 5(11): 671-676.

Ajao, E. A. and Fagede, S. O. (2002). The benthic macroinfauna of Lagos Lagoon. The Zoologist, 1(2): 1-5.

Andem, A. B., Okorafor, K. A., Udofia, U., Okete, J. A. and Ugwumba, A. A. (2012). Composition, Distribution and Diversity of Benthic Macroinvertebrates of Ona River, South-west, Nigeria. European Journal of Zoological Research, 1(2):47-53.

Austen, M. C. and Widdicombe, S. (2006). Comparison of the response of micro and macro benthons to disturbance and organic enrichment. Journal of Experimental Marine Biology and Ecology, 330: 96-104.


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Brown, D. S. (1994). Fresh Water Snails of Africa and their Medical Importance. London: Taylor and Francis Ltd. 607pp.

Day, J.A., (1967). A Monograph on the Polychaeta of Southern Africa Part 1 Errantia. London: British Museum of Natural History. 458pp.

Edokpayi, C. A., Olowoporoku, A. O. and Uwadiae, R. E. (2010). The hydrochemistry and macrobenthic fauna characteristics of an urban draining creek. International Journal of Biodiversity and Conservation, 2(8): 196-203.

Edward, J. B. and Ugwumba, A. A. A. (2011). Macroinvertebrate fauna of a tropical southern reservoir, Ekiti state, Nigeria. Continental Journal Biological Sciences, 4(1): 30-40.

Emmanuel, B. E. and Ogunwenmo, C. A. (2010). The macrobenthos and the fishes of a tropical estuarine creek in Lagos, south-western Nigeria. Report and Opinion, 2(1): 6-13.

George, A. D. I., Abowei, J. F. and Alfred-Ockiya, J. F. (2010). The distribution, abundance and seasonality of benthic macro invertebrate in Okpoka creek sediments, Niger Delta, Nigeria. Research Journal of Applied Science Engineering and Technology, 2(1): 11-18.

Holme, N. A. and Melntyre, A.D. (1984). Methods for the study of marine benthos. London: Blackwell Scientific Pub. 387pp.

Ikomi, R. B., Arimoro, F. O. and O.K. Odihirin (2005). Composition, distribution and abundance of macroinvertebrates of the upper reaches of River Ethiope Delta State, Nigeria. The Zoologist, 3: 68-81.

Nkwoji, J. A., Onyema, I. C. and Igbo, J. K. (2010). Wet season spatial occurrence of phytoplankton and zooplankton in Lagos Lagoon, Nigeria. Science World Journal, 5(5): 7-14.

Nkwoji, J. A., Igbo, J. K., Adeleye, A. O., Obienu, J. A. and Tony-Obiagwu, M. J. (2010b). Implications of bioindicators in ecological health: Study of a coastal lagoon, Lagos, Nigeria. Agriculture and Biological Journal of North America, 1(4): 683-689.

Ogidiaka, E., Esenowo, I. K. and Ugwumba, A. A. A. (2012). Physico-chemical parameters and benthic macroinvertebrate of Ogunpa River at Bodija, Ibadan, Oyo State. European Journal of Scientific Research, 85(1): 89-97.

Okorafor, K. A., Effanga, E. O., Andem, A. B., George, U. U. and Amos, D. I. (2013). Spatial variatio in physical and chemical parameters and macro-invertebrates in the intertidal regions of Calabar River, Nigeria. Greener Journal of Geology and Earth Sciences, 1(2): 63-72.

Olomukoro, J. O and Egborge, A. B. M. (2003). Hydrobiological studies on Warri River, Nigeria: The composition, distribution and diversity of macro benthic fauna. Journal of Aquatic Pollution, 15(4): 15-22.

Olomukoro, J. O. and Azubuike, C. N. (2009). Heavy metals and macroinvertebrate communities in bottom sediment of Ekpan Creek, Warri, Nigeria. Jordan Journal of Biological Sciences, 2(1):1-8.

Pennak, R. W. (1978). Freshwater invertebrates of the United States, 2nd edn. New York: John Wiley and Sons. 810pp.

Rashid, R. and Pandit, A. K. (2014). Macroinvertebrates (oligochaetes) as indicators of pollution: A review. Journal of Ecology and the Natural Environment, 6(4): 140-144.

Ravera, O. (2000). Ecological monitoring for water body management. Proceedings of monitoring Tailor-made 111, International Workshop on Information for Sustainable Water Management, pp: 157-167.

Saliu, J. K. and Ekpo, M. P. (2006). Preliminary chemical and biological assessment of Ogbe Creek, Lagos, Nigeria. West Africa Journal of Applied Ecology, 9: 14-22.

Sharma, K. K. and Chowdhary, S. (2011). Macroinvertebrate assemblages as biological indicators of pollution in a Central Himalayan River, Tawi (J&K). International Journal of Biodiversity Conservation, 3(5): 167-174.


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Umeozor, O.C. (1995). Benthic fauna of New Calabar River, Nigeria. Tropical Freshwater Biology, 4: 41-51.

Woke, G. N. and Aleleye-Wokoma, I. P. (2007). Effect of organic waste pollution on the macrobenthic organisms of Elechi creek Port Harcourt. African Journal of Applied Zoology and Environmental Biology, 9: 26-30.

Wood, E. (1987). Subtidal ecology. London: Edward Arnlod. 121pp. World Health Organization (WHO) (1984).International Standards for drinking water, 4th edn.

World Health Organization, Geneva. Zabbey, N. (2002). An Ecological survey of benthic macroinvertebrate of Woji creek, off the

Bonny River System, Rivers State. M.Sc. Thesis, University of Port Harcourt, 102pp.


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EFFECTS OF LEGUMINOUS COVER CROPS AND DENSITIES ON WHITE YAM (Dioscorea rotundata Poir) YIELD AND PEST SEVERITY AT HARVEST

Ikeh, A. O1., Etokeren, U. E.2, Nwanne, A.J3., Chinaka, I.C4., and Essang, I. P5.

1 Department of Crop Science, University of Uyo, Uyo.Akwa Ibom State Nigeria. 2 Department of Agricultural Technology, Akwa Ibom State Colleges of Arts and Science, Nung

Ukim Ikono, Akwa Ibom State Nigeria. 3Department of Horticulture and Landscape Technology, Akanu Ibiam Federal Polytechnic Unwana

Afikpo, Ebonyi State, Nigeria. 4 Department of Crop Science and Technology, Federal University of Technology Owerri, Imo State

Nigeria. 5 Department of Botany and Ecological Studies, University of Uyo, Uyo Akwa Ibom State.

Corresponding Author: [email protected]

ABSTRACT

A field study was conducted in 2009 and 2010 cropping seasons at University of Uyo Teaching and Research Farm, Uyo Southeastern Nigeria to evaluate the growth and yield productivity of white yam (Dioscorea rotundata Poir) under two cover crop cropping systems at different plant population density. The treatments were laid out in a randomized complete block design in split plot arrangement, replicated three times. The main treatment was two cover crop crops (groundnut and vegetable cowpea- Akidi) while cover crop population densities (0, 10000, 20000, 30000 and 40000 plant per hectare) constituted the sub-treatment. The result of the study showed that the vegetable cowpea as cover plot had significant reduction in weed density and biomass in both cropping seasons. No significant effect was observed on tuber yield obtained from groundnut (32.17 and 30.32 t/ha) and vegetable cowpea (30.71 and 30.56 t/ha) in 2009 and 2010 cropping seasons, respectively. The result also showed increase in yam yield with increase in plant population irrespective of the cropping system. The yield of vegetable cowpea and groundnut were significantly higher at 30,000 plant population and drastically reduced from 40,000 plant population. The study suggested that farmers should adopt both leguminous crops at 30,000 plant population in order to reduce weed infestation and improve the yield of white yam. Keywords: Yam, vegetable cowpea, groundnut, cover crop, pest severity.

INTRODUCTION Water yam (Discorea rotundata) is a very important food crop in West Africa, especially in the area from Nigeria to Cote d’ Ivoire. This region alone produces more than 90% of world production of yam (FAO, 2005). Nigeria is currently the largest producer of yam in the world, with average production record of 27 metric tonnes per annum, yam is only second to cassava among the staple root and tuber crops grown in Nigeria. (Nwosu, 2004; Ekwe, 2005). Analysis of crop area yield survey conducted in Nigeria showed that production in Nigeria stood at 25 – 30 metric tonnes/annum grown on 2.4 million hectare of land/annum and at an average yield of 10.7 tonnes/ha (Orkwor, 2001). Yam being the second most important tuber crop in Nigeria is a major food staple, which contributes substantially to nation’s food security (Ikeh, 2010 and Ikeh et al 2015). In the major producing area, yam is consumed at least once a day, during the yam season, from October to March of succeeding years (Ugwu, 1990). It is a major source of income to small scale yam farmers in West Africa (Dansi et al., 2001). Yam is recognized as a prestige food crop in many African communities and in Nigeria, especially the Igbo tribes where yam feature prominently in may traditional festivities. The ceremonies associated with

Ikeh, A. O., et al. (2017). Effects of Leguminous Cover Crops and Densities on White Yam (Dioscorea rotundata Poir) Yield and Pest Severity at Harvest. Journal of Environment and Sustainable Development, 3(1): 125 – 135.


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the yam planting ‘Nkoyiji’ and yam harvest ‘Ahajoku’, in Igbo land are often the major social-cum-religious occasion of the year (Onwueme and Sinha, 1991; Ikeh, 2010). Yam also occupies a place in many traditional marriage ceremonies and in special diets for mothers in confinement after child birth (Ihekoronye and Ngoddy, 1985). In southeastern Nigeria especially in many communities of Igbo tribes, any farmer that produced highest tuber yield or biggest tuber size per harvesting season is worthy of a title ‘Ezeji” meaning “King of Yam”. No other crop in Nigeria or Africa at large is associated with a greater amount of social and cultural activities than yam (Ikeh, 2010, Ikeh et al, 2012a). Yam production in southeastern Nigeria is declining because of low productivity associated with the cropping systems in the region (Unamma et al, 1985, Ano, 2006, Ikeh, 2010). Yam tubers are relatively cheaper than either cereals or legume grains on per kilogram basis (Ano, et al, 2003).

Moreover, yam tuber yield in the traditional farming system is low because of declining soil fertility. In the past, yam was the first crop that was planted to a land after long fallow because the nutrient requirement of yam is high (Ano, 2006). Currently, the fallow period (land use factor) has greatly reduced due population pressure in southeastern, urbanization and other non-agricultural land use and this has led to reduced soil fertility resulting to low yam system of southeastern Nigeria (Ano, 2006; Ikeh, 2010). As the productivity of yam cropping system is low in the study area, yam production is no more attractive to farmers. Most farmers attributed low production to high cost of mineral fertilizer, lack of improved seed yam, high cost of labour, problem of pest and diseases in the field and barn, staking problem, low multiplication ratio, poor respond to some cropping system, etc. One of the problems facing yam researchers is to develop production package that could improve the productivity of yam based system. Also different yam cultivar differs in respond to cropping system. According to Francis et al (1976), knowledge on how the intercrop uses resource and the extent to which the micro-environment of the system differs from the component sole crops can give a basis for choice of materials for the system, for there is evidence that high yielding materials in sole cropping do not performed the same when in intercrop Ikeh et al (2012a) in their work reported that yam genotype, TDr95/18894 was more adaptable to intercropping while TDr 75/1/2 preferred sole cropping. Thus, Zimmermann et al (1984); Rao and Willey (1980); Ikeh (2010) stressed the need to select genotypes for intercropping systems.

Intercropping with legumes as live-mulch or cover crops are not new in Nigeria but it become next alternative now organic agriculture is booming, soil water conservation as ready check for effect of climate change on soil. Mba et al (2003) have shown that the productivity of root crops system was improved through intercropping with legumes. Ano et al (2003) attributed the improvement to the higher cost of legume grain compared to root crop tubers. Okoh et al (2001); Kolawole and Tian (2004); Muhamman and Gungula (2006) have reviewed the economic benefit of leguminous cover crops such as improving soil fertility, reduction in the use of inorganic fertilizer, herbicides, weed and insect control cost, protecting of ground water, scavenging residual nitrate and high economic return to the farmers.

Vegetable Cowpea (Vigna unguiculata (L) walp) and sub specie sesquipedallis and groundnut (Arachis hypogaea L.) are legumes that thrive and form high vegetative during yam growing season. Most researchers have recommended legumes intercrop to yam but presently information on type of legume and appropriate density/population to valuable water yam intercropping system is scarce. Farmers in southeastern Nigeria will adopt this package easily since all the component crops are already in existence to their farming system. The objective of this study was to determine the yield of yam genotypes to different leguminous crop population.


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MATERIALS AND METHODS The study was carried out during the 2009 and 2010 cropping seasons at University of Uyo Teaching and Research Farm located at Uyo (Latitude 5°17' and 5°27'N Longitude 7°27' and 7°58°E and altitude 38.1m above sea level). This rainforest zone receives about 2500mm rainfall annually. The rainfall pattern is bimodal, with long (March – July) and short (September – November) rainy seasons separated by a short dry sell of uncertain length, usually during the month of August. The mean relative humidity is 78% atmospheric temperature is 300C and the mean sunshine hour is 12 (Peters et al, 1989).

The experimental site was under fallow for 2 years after being planted with maize/fluted pumpkin intercrop. Land preparation was manually done with matchetes and spade. The site, after clearing was left to dry for three and the trashes were raked and packed at the borders. The 8m ridges were constructed at 1m x 1m spacing. The experimental design used was randomized complete block design in a split-plot arrangement and replicated three times. The main treatments were two leguminous crops Cowpea “Akidi”; semi-erect that is suitable for forest zone and groundnut - SAMNUT 20 which is suitable south guinea savannah while the sub- treatments were five leguminous densities: 0, 10000, 20000, 30000 and 40000 plant per hectare. Cowpea and groundnut seeds were obtained from National Seed Service Station, Umudike, Abia State Nigeria.

The main plot measured 24 m x 8 m, while sub-plot, 12 m x 8 m with a spacing of 1m between each plot and 2m between replicates. Planting was done on second week of April in both cropping seasons. Yam setts of 180 g were planted at the crest of ridges. Cowpea and groundnut seeds were planted at 2/3 of the ridges on the same day based on treatment basis. Harvesting of immature cowpea pods started from 12 weeks after planting (MAP) while groundnut was harvested at 5MAP. Yam was harvested at 8 MAP.

The following growth and yield data were assessed: number leaves per plant, leaf area, total tuber yield, others include number of tuber attacked by termite, cricket, nematode and yam beetle. The following weed data: weed population/m2, and weed biomass (g/m2) were also determined at 2 and 3 MAP. The yield of cowpea pods and groundnut grains were also determined by weighing the pods and grains, respectively. The data obtained were subjected to Analysis of Variance. Means that showed significant difference were compared with least significant difference at 5% probability level while the land equivalent ratio (LER) was determined by the use of Harwood and co-workers (IRRI, 1974) procedure.

LER =IntercropyieldofcropA

SolecropyieldofAG+

IntercropyieldofcropB

solecropyieldofcropBG+

Intercropyieldofcrop�

solecropyieldofcrop�

= relative yield crop A + relative yield crop B + relative yield cropn.

RESULTS The result of the study showed significant difference between both cropping system at 2 to 5 months after planting (MAP) except at 2MAP in 2009 on number of leaves per plant (Table 1). In both cropping seasons, the use of vegetable cowpea as cover crop in yam field resulted to highest number of yam leaves per plant compare to intercropping with groundnut. The vegetable cowpea plots had (14% and 13%) and (8% and 9%) higher number of leaves per plant at 4 and 5 MAP in 2009 and 2010 cropping seasons, respectively.

The results of cover crop population density on number of yam leaves per plant also differed significantly in all the months under study in both cropping seasons. The results also showed increase in leguminous population per hectare with increase in yam leaves. The least


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number of leaves per plant in both cropping seasons was recorded from control (sole crop yam). There was a positive interaction effect between cropping systems and leguminous plant population on number of leaves per plant at 3, 4, and 5 MAP in both cropping seasons. The effect of cropping system on leaf area showed significant difference only at 3 MAP in 2009, however, intercropping with vegetable cowpea resulted to wider leaf size 19.98, 27.56, 30.88 and 31.96 cm2 in 2009, 20.96, 23.89, 32.09 and 34.90cm2 in 2010 at 2 to 5 MAP respectively. The influence of leguminous population per hectare on yam leaf area also differed significantly (p<0.05) in cropping seasons. The results showed no significant difference among the leguminous population of 20,000, 30,000 and 40,000 irrespective of cropping systems. The interaction effect between cropping systems and leguminous plant population on leaf area showed no significant difference on both cropping seasons.

The effect of cropping systems and leguminous plant population on weed population showed significant difference in 2009 and 2010 respectively. Among the cropping systems, the highest weed population was recorded groundnut (165.00 and 200.80 weeds per m2) and (162.40 and 166.20 weeds per m2) at 2 and 3 MAP in 2009 and 2010, respectively. The groundnut plots had (8 % and 6 %) and (13 % and 7 %) higher weed population at 2 and 3 MAP in 2009 and 2010 cropping season, respectively. The weed population per m2 as influenced by leguminous plant population also differed significantly (p<0.05). The results showed decrease in weed population per hectare with increase in leguminous plant population. The sole yam plots had the highest weed population per m2 in both cropping seasons, irrespective of cropping system. The interaction effect between cropping system and leguminous plant population on weed population per m2 showed significant difference in both cropping seasons. The result of dry weed biomass (g/m2) as influenced by cropping system also differed significantly in both cropping seasons (Table 3). Vegetable cowpea as leguminous cover crop had the least dry weed biomass (Table 3). The effect of leguminous cover crop population per hectare on weed biomass also showed significant difference (p<0.05). In both cropping seasons, control (sole yam plot) had the highest dry biomass (Table 3) irrespective of cropping system. The interaction of cropping systems and leguminous cover crop population per plant also varied significantly except at 2 MAP in 2009.

Yam beetle severity as influenced by cover crop had no significant effect in both cropping seasons (Table 4). Effect of cover crop density on yam beetle attack at harvest had significant effect in both cropping seasons. The highest beetle infestation was observed in sole yam plots (no cover crop) irrespective of cover crop type (Table 4). Result of cricket attack at harvest presented in table 4 had no significant difference when both cover crop types were compared. Effect of cover crop density on cricket attack showed significant difference (P<0.05) among the cover crop densities. The highest severity was recorded in sole yam plot, irrespective of cropping season while the least severity, irrespective of leguminous cover crop type was observed in the treatment of 40,000 cover crop density. The results of termite and nematode attack also maintain the similar trend in yam beetle and cricket attack. Yam planted in 40,000 cover crop density had the least termite and nematode attack while the highest severity was observed in the sole yam plots. In all the pest attack at harvest, the results indicated decrease in pest at attack harvest with increase in cover crop densities (Table 4). The interactions of leguminous cover crop type and densities had no significant effect.

The effect cover crop densities on groundnut grain and vegetable cowpea pod yields varied significantly (Table 5). In groundnut yield, the result indicated increase in yield with increase in cover crop density up to 30,000 groundnut stands per hectare and decreased at 40,000 groundnut stands per hectare. The 30,000 groundnut stands per hectare had the highest groundnut grain of yield of 809.30 and 814.40 kg/ha in 2009 and 2010 cropping seasons, respectively. The study further indicated decrease in groundnut yield (633.18 and 632.58 kg/ha) at 40,000 groundnut stands per hectare. In both cropping seasons, 10,000 groundnut stands per


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hectare had the least groundnut grain yield (566.81 and 625.18 kg/ha) in 2009 and 2010 cropping seasons, respectively. The 30,000 groundnut plant population had 30% and 23% groundnut grain yield more than other groundnut densities in 2009 and 2010 cropping seasons, respectively.

Vegetable cowpea yield also followed similar pattern as in groundnut grain yield. The highest fresh pod yield (10.48 and 11.10 t/ha) in 2009 and 2010 cropping seasons, respectively, was obtained from 30,000 vegetable cowpea stands per plant (Table 5). The results showed reduction in pod yield (7.10 and 7.75 t/ha in 2009 and 2010 respectively) in the plots of 40,000 stands per hectare. The 30,000 stands of vegetable cowpea per hectare had 32 – 40 % and 30 – 40 % more vegetable cowpea yield than other densities in 2009 and 2010 cropping seasons, respectively. The white yam tuber yield as influenced by leguminous cover crop types differed not significantly in both cropping seasons (Table 5). In vegetable cowpea plots, the yam tuber yield was (32.17 and 30.71 t/ha) in 2009 and 2010 cropping seasons, respectively. The use of groundnut as cover crop resulted to yam tuber yield of 30.56 and 30.32 t/ha in 2009 and 2010 respectively. The use of vegetable cowpea as cover crop had only 5% and 1% yam tuber yield than yield obtained from groundnut cover crop plots. The increase in vegetable cowpea and groundnut densities resulted to increase in yam tuber yield. The 40,000 stands of leguminous cover crops plots gave the highest yam tuber yield in both cover crop types, irrespective of cropping seasons. The least yam tuber yield (25.71 and 24.23 t/ha) in both cropping seasons, was obtained from control (sole yam plots). The results of tuber yields further revealed no significant difference between the density of 30,000 cover crop plots and 40,000 cover crop plots.

DISCUSSION The effect of leguminous densities showed significant increase in vegetative traits and yam tuber yield. Vegetable cowpea plots had low weed population than groundnut plots. This could be due to bigger leaf morphology of vegetable cowpea compared to smaller leaf area of groundnut. Vegetable cowpea also had high foliage, longer vines and coverage than groundnut. These attributes could have enabled vegetable cowpea to conserve soil moisture, reduce erosion and add more organic matter to the soil.

The study also showed decrease in weed population and biomass with increase in cover crop densities. The 40,000 stands per hectare of cover crop density had the least weed population and dry biomass in both cropping seasons, irrespective of leguminous cover crop types. This was followed by 30,000 stands per hectare. The highest weed population and dry biomass were observed in sole yam plots. This observation was agrees with the findings of Singh et al (1986) that intercropping yam (D. floribunda) with cover crops (cowpea - Vigna unguiculata and black gram - V. mungo) were equally effective in suppressing weed growth in field. The low weed population recorded in the cover crop plots could be that the cover crops covered the soils and reduced the opportunity of the weeds to be established. This observation agrees with Sullivan, 2003; Kolo et al., 2004; Ikeh, 2010 and Ikeh et al., 2012b that cover crops compete with weeds for light, space, nutrient and water and also reduced the opportunity of the weeds to be established. Ikeh et al (2012b) also reported that cover crop such as vegetable cowpea is option of weed management where cost of weeding is high. Stockwell and Fisher (1996) reported that cover crops can provide an effective alternative to chemical weed control and improve net savings in labour cost. The results also showed low pest infestation level in the plots of cover crops. Sole yam plot had the highest severity of yam beetle, cricket and nematodes while the 40,000 stands of cover crop per hectare had the least severity. This observation agrees with the findings Sullivan (2003), that some species of cover crops may be a non host for pest or may release toxic materials (allelopathic chemicals) that are harmful to


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the pest or other plants while some cover crops attract beneficial insects which are detrimental to pests of the component crops which deterred the pests from the crop. The low nematode attack at harvest recorded from cover crop plots was in consonance with findings of Lebot (2009), that some cover crops had nematode control potential e.g. velvet bean (Mucuna pruriens), kudzu (Pueraria phaseoloides).

The results showed significant increase in yam tuber yield when cover crop plots were compared with sole yam plots. Increase in cover crop densities also produced significant yam tuber yield, irrespective of leguminous cover crop type. This agrees with the report of Obiagwu (1997), yam responded positively to NPK (ratio 15:15:15) applied at 30 – 80 kg/ha and to intercropping with cowpea or yam bean (Sphenostylis stenocarpa). Obiagwu (1997) further stated that intercropping was equivalent to application of 48 and 26 kg/ha of NPK, respectively. In Obiagwu (1997) study, cowpea gave the greatest improvement in maize yield than other cover crops. The difference exist between cowpea and groundnut as cover crop could be a result of different in land coverage and ability to fix N in the soil. Obiagwu (1997) reported that among the legumes used in his study, common bean (Phaseolus vulgaris) had higher N fixation, leaf nutrient level and biomass than the other legumes but was slower to gain ground cover.

The yield of vegetable cowpea and groundnut grains increased with increase in legume population with peak at 30,000 plant population. The reduction in legumes yield at 40,000 plant population could be due to intra and inter competition for light, water and other soil nutrients with the plants. This agreed with findings of Udealor (2002), that in an intercropping system, component crops compete for growth resource, the competition becomes more pronounced as population of the crops increases while Fregman and Venkateshwarlu (1977) reported that such increase in plant population may lead to low crop yield in the intercropping systems compared to the yield of the same crop in the sole cropping system.

The yield of yam tuber increased with increase in leguminous densities while legume yield increased from 10,000 cover crop stands per hectare to 30,000 stands per hectare and decreased at 40,000 cover crop stands per hectare. The decrease in vegetable pod and groundnut grain yield observed in 40,000 stands plots could be as a result of high completion rate within the cover crops and yam.

CONCLUSION The study revealed that leguminous cover crops could be an alternative means of reducing weed interference and yam tuber pest severity. Intercropping yam with vegetable cowpea and groundnut at 30,000 plant population density resulted to increase in yield productivity of yam, cowpea and groundnut. The use of cover crops reduced pest attack and enhances yam tuber yield. Therefore, farmers in southeastern Nigeria could improve their white yam yield and obtain more yields from the component crops on the same piece of land with appropriate leguminous cover crop density.

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productivity of yam minisett based system. Niger Agric. J. 37:81 – 84. Ano, A. O., G. C. Okwor and J. E. G. Ikeorgu (2003). Evaluation of the Contribution of

Leguminous Cover Crops to the Conversation of Soil Resource Base and Productivity of Yam Based Systems. In M. O. Akoroda editor, Root Crops: The small processor and development of local food industries for market economy. Proc. Of the 8th Triennial symposium of the international society of tropical root crops African branch, held at the international institute for tropical agriculture, Ibadan, Nigeria. 12 November, 2001, pp.293 – 295.


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Dansi, A., Mignouna, J., Sangara, A., Zoundjihekpa, J., Asiedu, R., Quin, F. M. (2001). Characteristics and Conservation of Yam Biodiversity for Sustainable Use for Food and Agriculture in Benin Republic. In: Proceeding of 7th Triennial Symposium of the International Society for Tropical Root Crops-Africa Branch (ISTRC-AB) Centre International des Conferences, Cotonou, Benin Rep. 11-17 October, 1998.

Ekwe, K. C. (2005). Promotion and Dissemination of Hybrid Yam Varieties Implications for Increased Yam Production in Nigeria. Proceeding of the 39th Conference of the Agricultural Society of Nigeria (ASN), University of Benin, Benin, pp. 195 – 197.

FAO (2005). Food and Agricultural Organisation (2006). Databases.

Francis, C. A., Flor, C. A. and Temple, S. R. (1976). Adopting Varieties for Intercropped Systems in the Tropics. In: Multiple Cropping, Special Publication No. 27. American Society of Agronomy. Madison, W. I. pp. 235-253.

Fregman, S. and J. Venkateshwarlu (1977). Intercropping on rainfed red soils of Decan Plateau, India. Canadian Jour of Plant Sci. 57:677-705.

Gomez, K. A. and Gomez, A. A. (1984). Statistical Procedures for Agricultural Research. A Willey-Interscience Publication, John Willey and Sons. New York 660pp.

Ihekoronye, A. I. and Ngoddy, P. O. (1985). Integrated Food Science and Technology for the Tropics. Macmillian Education Limited. London. p. 266-282.

Ikeh, A. O. (2010). Effects of intercropping melon (Colocynthis cirullus) and fertilization on performances of yam (Dioscorea rotundata) genotypes on an ultisol, Southeastern Nigeria. M.Sc. Dissertation, University of Uyo, Uyo, Nigeria.

Ikeh, A. O., Ndaeyo, N. U., Iwo, G. A., Aderi, O. S., Ikeorgu, J. E. G., Nwachukwu, E. C. and Essien, B. A. (2012a). Effects of Cropping System on Growth and Yield of Yam (Dioscorea rotundata) Genotypes and Egusi Melon (Colocynthis cirullus) on an Ultisol. International Journal of Applied Research and Technology. 1(1):119 – 131.

Ikeh, A. O. Ndaeyo, N. U. Udounng P. I. and Akata O. R. (2012b). Growth and Yield of Cassava (Manihot esculenta Crantz) as Influenced by Different Weed Management Techniques in Uyo Southeastern Nigeria. In: Proceeding of 46th Annual Conference of Agricultural Society of Nigeria. Kano. pp. 938-942.

Kolawole, G. O. and Tian, G. (2004). Potentials of Leguminous Cover Crop Systems for Sustaining Agricultural Production in the Humid Tropics of Africa in Badejo, M. A. and A. O., Togun (Eds) Strategies and Tractics of Sustainable Agriculture in the Tropics. Vol. 2. College Press and Publishers Ltd. Ibadan, Nigeria.

Kolo, M. G. M., Oladiran, J. A., Abdullahi, M. and Raji, M. (2004). Influence of Melon (Citrus lanatus) (thumb) Mansf) Intercrop in Yam (Dioscorea rutundata poir/maize (Zea mays L.) based Cropping System on Weed Control and Crop Yield. Journal of Sustainable Tropical Agricultural Research. 10:116-127.

Lebot, V. (2009). Tropical root and tuber crops: Cassava, sweet potato, yams, aroids. CABI: Walingford, Oxfordshire.

Mba, E. U., C. O. Muoneke and D. A. Okpara (2003). Evaluation of cassava / soybean intercropping systems as influenced by cassava genotypes, Niger Agric. J. 34:11-18.

Muhamman, M. A. and Gungula, D. T. (2006). Cover Crops in Cereals Based Cropping Systems of Northern Nigeria: Implication on Sustainable Production and Weed Management. Journal of Sustainable Development in Agriculture and Environment Vol. 2 (1). pp. 85 – 91.

Nwosu, K. I. (2004). Achievements of National Root Crops Research Institute, Umudike. Paper Presented at Annual Research Review and Planning Workshop of NRCRI, Umudike held 5th – 7th April, p. 2.


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Obiagwu, C. J. (1997). Screening Process for idea food legume cover crops in the tropical ecosystem II. Application of the selection method for grain legume crops of the Benue River Basins of Nigeria. Journal of Sustainable Agriculture 10(1), 15 – 31.

Obigbesan and Agboola, A. A. (1978). Unptake and distribution of nutrients by yams (Discorea spp.) in Western Nigeria. Experimental Agriculture 14:349 – 355.

Okoh, A. K., Oladiran, J. A. and Kolo, M. G. M. (2001). Effect of Time of Planting Maize Intercropped with Melon on Weed Suppression and Crop Yield. Journal of Vocational Education 1 (1): 164-171.

Okwor, G. C. (2001). Perspectives in Yams Research in Africa: In M. O. Akoroda (Eds.). Proceedings of 8th Triennial Symposium of ISTRC A-B held in Ibadan, Nigeria 12 – 16 November, pp. 5 – 7.

Onwueme I. C. and Sinha, T. D. (1991). Field Crop Production in Tropical Africa. CTA, ed., The Netherlands. pp. 250 – 266.

Peters, S. W., Usoro, E. J. Udo, E. J. Obot, U. w. and Okpon, S. N. (eds), (1989). Akwa Ibom State: Physical Background, Soils and Land Use and Ecological Problems. A Technical Report of the Task Force on Soils and Land Use Survey, Akwa Ibom State. 603p.

Rao, M. R and Willey, R. W. (1980) Evaluation of Yield Stability in Intercropping Studies on Sorghum – Pigeonpea. Journal of Experimental Agriculture, 116: 105 – 116.

Singh, A. Singh, M. and Singh, D. V. (1986). The successful use of intercropping for weed management in medicinal yam (Discorea floribunda Mart and Gal) by single-node leaf cuttings. Tropical Agriculture (Trinidad) 68(2), 196- 197.

StockWell, C. and Fisher, L. (1996). Cover Crops for Sustainable Agriculture in West Africa: Constraints and Opportunities. A Workshop Organised by the International Developmental Research Centre (IDRC) in Collaboration with Sassakawa Global 2000, the International Institute of Tropical Agriculture (IITA), the World Bank and Ministry of Rural Development (MDR) in Contonour, Benin Republic. 1st – 3rd October, 1996.

Sullivan, P. (2003). Overview of Cover Crops and Green Manures. ATTRA – National Sustainable Agricultural Information Services. Fayetteville, U.S.A.

Udealor, A. (2002). Studies on growth, yield, organic matter turnover and soil nutrient changes in cassava (Manihot esculenta Cranz), vegetable cowpea (Vinga unguiculenta L. Walp) mixtures. Ph.D Thesis University of Nigeria, Nsukka.

Ugwu, B. O. (1990). Resource Use and Productivity in Food Crop Production in major Yam Producing Area of Southeastern Nigeria. Ph.D Dissertation, University of Nigeria, Nsukka.

Unamma, R. P. A., S. O. Odurukwe, H. E. Okereke, L. S. O. Ene and O. O. Okoli (1985). Farming systems in Nigeria. Report of benchmark survey of the farming systems of eastern agricultural zone of Nigeria. AERLS, National Root Crops Research Institute, Umudike.

Zimmermann, W. J. A., Roseille, A. A; Wanes, J. G., Foster, K. W (1984) A Heritable and Correlation Study of Grains Yield, Yield Components and Harvest Index of Common Bean in Sole and Intercrop. Journal of Field Crops Research, 9: 109– 118.


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Table 1: Number of Leaves per Plant as Affected by Leguminous Cover Crops and Densities

Cover crops Density (Plant/ha)

2009 _____Months After Planting_____

2010 ________Months After Planting____

2 3 4 5 2 3 4 5 Cowpea 0 9.30 52.61 93.60 115.61 10.66 59.12 103.16 169.51

10,000 12.33 76.33 165.11 185.60 18.30 80.66 170.33 201.30 20,000 17.61 101.31 180.18 196.18 18.63 96.40 182.36 218.80 30,000 17.67 112.60 196.20 213.09 19.11 125.36 208.38 223.60 40,000 18.30 131.80 206.13 241.05 19.61 183.81 213.16 251.18 Mean 15.08 94.93 168.24 190.31 17.26 99.97 175.48 212.88 Groundnut 0 9.05 51.33 96.18 107.33 10.33 54.01 111.31 121.60 10,000 9.17 63.60 118.13 163.14 10.48 67.40 133.08 188.62 20,000 10.33 79.40 151.16 172.18 12.66 85.90 169.09 211.60 30,000 15.61 86.70 166.18 187.33 18.25 112.30 189.06 218.40 40,000 16.35 103.40 189.15 196.12 18.48 128.18 208.30 228.41 Mean 12.10 76.89 144.16 165.22 14.04 89.56 162.17 193.73 LSD (p<0.05) Cover crops (C) ns 1.51 2.31 2.81 0.55 1.75 2.08 2.61 Density (D) 2.11 5.25 8.66 9.03 1.77 4.91 6.33 9.25 C x D Interaction ns 0.78 1.06 1.12 ns 0.82 1.35 2.01

Table 2: Leaf area (cm2) of Yam as Affected by Leguminous Cover Crops and Densities

Cover crops

Density (Plant/ha)

2009 Months after Planting

2010 Months after Planting

2 3 4 5 2 3 4 5 Vegetable Cowpea 0 13.00 18.25 20.13 21.80 14.60 20.11 21.88 22.00 10,000 20.20 22.15 24.55 25.16 20.67 23.60 25.14 26.31 20,000 21.33 24.18 28.40 29.33 22.40 24.81 28.44 31.65 30,000 22.66 24.51 39.18 40.65 22.55 25.12 38.66 46.13 40,000 22.71 24.55 42.12 42.88 34.60 25.80 46.33 48.43 Mean 19.98 27.56 30.88 31.96 20.96 23.89 32.69 34.90 Groundnut 0 12.75 15.61 20.18 20.96 13.43 18.62 20.69 21.55 10,000 19.00 20.18 22.16 23.40 20.41 21.1`1 23.44 25.18 20,000 21.51 22.40 24.30 23.31 22.40 22.58 33.93 38.66 30,000 21.66 23.50 32.62 38.12 24.30 24.16 35.12 45.13 40,000 22.0`1 23.65 38.12 40.81 24.40 25.12 39.41 45.80 Mean 19.39 21.07 27.48 29.72 20.99 22.32 30.52 35.26 LSD (p<0.05) Cover crops (C) ns 1.22 ns ns ns ns ns ns Density (D) 2.05 3.11 3.65 4.29 1.67 1.88 2.75 4.22 C x D Interaction ns ns ns ns ns ns ns ns

*ns= not significant


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Table 3: Weed Population and Dry Biomass of Yam Field as Affected by Leguminous Cover Crops and Densities


2009 2010

Weed population Weed Biomass Weed population Weed Biomass

2 3 2 3 2 3 2 3 Vegetable Cowpea

0 294.11 451.06 198.51 226.81 265.19 369.26 186 210.40

10,000 215.20 308.18 161.88 185.63 206.48 225.81 153.11 159.41 20,000 103.33 98.39 112.63 98.88 99.44 76.73 116.77 128.16 30,000 83.11 45.78 66.75 96.51 83.39 64.14 77.50 84.33 40,000 66.22 38.23 80.44 95.31 64.14 39.45 82.18 73.14 Mean 152.48 188.33 138.89 140.63 124.04 155.12 123.23 131.01 Groundnut 0 288.18 476.18 175.51 218.44 281.39 361.22 182.15 218.77 10,000 222.40 261.24 143.60 140.61 202.40 198.26 152.22 160.45 20,000 118.15 103.39 130.45 138.40 125.29 111.33 125.14 143.40 30,000 104.30 93.31 110.30 128.15 116.38 95.81 120.46 130.75 40,000 96.12 71.08 89.93 91.30 88.40 66.20 103.31 125.88 Mean 165.83 201.04 127.96 `143.38 129.96 166.56 136.66 155.85 LSD (p<0.05) Cover crops (C) 2.55 1.81 0.65 3.88 2.13 1.15 2.03 1.06 Density (D) 11.30 12.66 8.17 16.41 12.75 18.25 10.25 9.`17 C x D Interaction 1.33 1.20 ns 1.98 1.08 0.22 1.98 0.51

Table 4: Pest Attack at Harvest as Influenced by Leguminous Cover Crops and Densities


2009 2010

Yam beetle

Cricket Nematode

Termite Yam beetle

Cricket Nematode Termite

Vegetable Cowpea

0 3.80 2.53 3.33 3.45 3.33 2.81 3.41 3.60

10,000 2.33 1.33 2.00 2.30 2.30 1.30 2.40 2.41 20,000 1.33 1.00 1.30 1.33 1.30 1.30 1.33 2.00 30,000 1.30 1.00 1.00 1.30 1.30 1.10 1.33 1.33 40,000 1.00 1.00 1.00 1.00 1.00 1.10 1.30 1.33 Mean 1.95 1.37 1.73 1.88 1.85 1.52 1.95 2.13 Groundnut 0 3.75 2.80 4.10 3.63 3.33 2.41 3.50 2.33 10,000 2.13 1.63 2.33 2.13 2.33 2.31 2.00 2.00 20,000 1.33 1.30 2.00 1.33 1.30 1.30 1.30 1.30 30,000 1.60 1.30 1.55 1.30 1.30 1.30 1.33 1.30 40,000 1.00 1.30 1.30 1.30 1.00 1.30 1.30 1.30 Mean 1.84 1.67 2.26 1.94 1.85 1.73 1.89 1.65 LSD (p<0.05) Cover crops (C) ns ns ns ns ns ns ns ns Density (D) 1.30 0.75 1.05 1.71 1.43 0.82 0.91 1.63 C x D Interaction ns ns ns ns ns ns ns ns



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Table 5: Yields of Groundnut, Vegetable Cowpea and Yam Tubers as Affected by Leguminous Cover Crops and Densities


__________2009__________ __________2010___________ Groundnut yield (kg/ha)

Vegetable cowpea yield (t/ha)

Yam tuber yield (t/ha)

Groundnut yield (kg/ha)

Vegetable cowpea yield (t/ha)

Yam tuber yield (t/ha)

0 - - 26.25 - - 23.21 Vegetable Cowpea

10,000 - 6.33 30.75 - 6.75 28.42

20,000 - 8.56 33.43 - 8.55 32.17 30,000 - 10.48 35.18 - 11.10 34.88 40,000 - 7.10 35.25 - 7.75 34.89 Mean 8.12 32.17 8.54 30.71 0 - - 25.16 - - 25.25 Groundnut 10,000 566.81 - 29.55 625.18 - 28.28 20,000 793.80 - 31.45 788.40 - 31.38 30,000 809.30 - 32.25 814.40 - 33.25 40,000 633.18 - 34.38 632.58 - 33.45 Mean 700.77 30.56 715.14 30.32 LSD (p<0.05) Cover crop (C) - - ns - - ns Density (D) 31.25 2.03 2.51 25.14 1.98 3.06 - - ns - - ns



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A COMPARATIVE STUDY ON ORGANIC AND INORGANIC METHOD OF FARMING IN IMPROVING THE NUTRITIONAL QUALITY OF

Ocimum gratissimum

Ekpo, F. E1. Okey, E. N1 and Njoku, K. U.2 1 Department. of Biological Sciences, Akwa Ibom State University, Ikot Akpaden, Mkpat

Enin Local Government Area, Akwa Ibom State, Nigeria. 2 Faculty of Environmental Science, Abia State University, Uturu

Corresponding Email: [email protected]

ABSTRACT

Studies on the effect of farming methods (organic and inorganic the on nutritional quality of Ocimum gratissimum leaves was investigated. The leaf of Ocimum gratissimum is used in traditional medicine for the treatment of several ailments such as urinary tract, wound, skin and gastrointestinal infections. A 5kg of organic manure (poultry dungs) was mixed with 50kg of soil and this was regarded as organic method of farming. Also, 5kg of NPK fertilizer was mixed with 50kg of soil and this was regarded as inorganic method of farming. Each treatment was replicated three times. The study was conducted as pot experiment in the Green House at Botanical Garden. Plant samples were watered daily for 12 weeks (three months). At the end of 12 weeks, the leave of Ocimum gratissimum were harvested for laboratory analysis. The proximate compositions and mineral nutrients of the leaf samples were determined. The result showed that organic method of farming recorded the highest mean values of energy yield (1460.38±1.10), crude fat (4.05±1.00), carbohydrate (15.00±0.20) and total ash content (6.92±0.15). While protein content recorded the highest values in crop grown with conventional method of farming. There was no significant difference (p<0.05) in the moisture contents of the plant samples obtained from organic and conventional farming. The concentrations of mineral nutrients Ca, P, K, Mg, Na, Fe and Zn in the leaves of Ocimum gratissimum were also found to increase significantly in the soil treated with organic manure as compare to values recorded in soil treated with NPK fertilizer. The study showed that organically grown crops have positive influence on the proximate compositions and mineral elements of vegetables than conventional grown crops. The study recommend organic agricultural practices because it contained high nutritional quality than conventional method of agriculture. KEYWORDS: Nutritive Quality, Ocimum gratissimum leaves, Organic and Conventional Farming

INTRODUCTION Organically grown crops are crops that have been cultivated without the use of synthetic agricultural inputs such as synthetic pesticides, herbicides, fungicides, soluble mineral fertilizers, growth regulators, components derived from genetically modified organisms (GMO) and irradiation (USDA, 2002). A group of them include vegetables that uses animal manures, green manures, compost manures and a varied crop rotation practices, instead of readily synthetic fertilizers. Vegetables play a significant role in human nutrition, especially as sources of dietary fiber, minerals, and vitamins (Craig and Beck 1999). Woese et al., (2000) reported that vegetables remain an important source of nutrients in many parts of the world and offer advantages over dietary supplements because of low cost and wide availability.

It is widely assumed that method of farming affect the nutritional quality of crops. In particular organic farming produce higher quality than conventional farming method (Mozafar

Ekpo, F. E., Okey, E. N and Njoku, K. U. (2017). A Comparative Study on Organic and Inorganic Method of Farming in Improving the Nutritional Quality of Ocimum gratissimum. Journal of Environment and Sustainable Development, 3(1): 136 – 142.


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2004). Benefits derived from organic farming is due to an absence of synthetic chemical residues in the crops. Although it is scientifically challenging to adequately assess the nutritional quality of crops grown in different cultivation methods, because the final measure of nutritional quality of food lies in the organism that consumes the food. However, different farming methods have their different reaction pattern that result in the culinary value of that product. Nutritional quality is defined as the value of the food for the individual consumer’s physical health, growth, development, reproduction and psychological and emotional well-being (Roth et al, 2005). Lester, (2007) reported that organic farming system avoid the severe negative effects on human health that can be caused by conventional method of farming. Interest in organic food has increased worldwide in response to concerns about conventional agricultural practices, food safety, taste, human health, animal welfare and the environment (Baker et al., 2006). Opinion polls have suggested that a significant proportion of organic consumers believe that organic food is qualitative and contains a higher concentration of nutrients as a result of the superior soil management and activities of soil micro-organisms. A range of positive inferences are made by consumers on organic food (Wiler et al., 2009.). Public concern about nutritional quality of food grown in conventional farming system has intensified in recent years. A series of food scares and the controversy surrounding genetically modified crops have prompted heated debate about the safety and integrity of conventional food (Mayer, 2001). Against this background, demand for organically grown food has been growing rapidly. However, the study assessed the nutritional quality of scent leaf (Ocimum gratissimum) leaves grown in organic and conventional methods of farming system

Botany Ecology of the Plant: Ocimum gratissimum belong to the family Labiatae and grows mostly in south eastern Nigeria and coastal communities of Niger Delta region, Nigeria. The plant is known by various names in different parts of the world. In Efik it is called “Nton”, in Yoruba it is called “efinirinajase”, in Hausa it is known as “Aaidoya ta gida”. Ocimum gratissimum is a perennial plant which is widely distributed in the tropics of Africa and Asia. In Nigeria it is a widely used as spice and vegetable in rural communities of Akwa Ibom State. The plant is used in traditional medicine for the treatment of several ailments such as urinary tract, wound, skin and gastrointestinal infections (Baker et al., 2006). The pleasant smell of the plant gives it the common name scent leaf plant (Ocimum gratissimum) MATERIALS AND METHODS The research was conducted as pot experiment in the Green House at Botanical Garden, Akwa Ibom State University, Ikot Akpaden, Mkpat Enin Local Government Area, Akwa Ibom State. The University is located a distance of 10 miles from Atlantic Ocean is located between longitude 70 300E and 70 450 E latitudes 40 300 W and 40 450N. The soil samples used for the study were collected from bush fallow in the Botanical garden, Akwa Ibom State University. The soil sample was divided into two treatments A and B. Treatment A contains 5kg of organic manure (poultry dungs) and 50kg of soil sample and this was regarded as organic method of farming. Then treatment B (inorganic method of farming) contain 5kg of (NPK) fertilizer (Nitrogen Phosphorus and Potassium) and 50kg of soil sample. The soil treatments were allowed to stay for one week (7 days) before the seeds of Ocimum gratissimum were planted. This was to allow for free mixture of organic manure and NPK fertilizer in the different soil treatments and to maintain a uniform component mixture. Each treatment was replicated three times. The seeds of Ocimum gratissimum used for the experiment were obtained from Akwa Ibom State Agricultural Development Programme (AKADEP). The experiments were watered daily for 3 months (12 weeks). The analyses of proximate composition and mineral elements in Ocimum gratissimum leaves were done at the end of 3 months (12 weeks). Processing of Leaf Samples: At the end of three months (12 weeks), the fresh leaves of


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Ocimum gratissimum were plucked and air dried at 28oC for 24hours. The leaf samples were grounded into fine powder using an electric blender and stored in a cool dry container for both proximate and mineral analysis. The fresh leaves were used for moisture and dry matter content determination. Food energy determination: Food energy is the measures of the chemical energy inherent in the bonds of the organic components of foods. Energy value was determined according to the methods of Osborne and Voogt (1978) using the equation.

Energy (KJ/100g) = 4.186 {(% crude protein x 4) + (% crude fat x 9) + (% carbohydrate x 4)}. Proximate Analysis: The proximate analysis of the leaves of Ocimum gratissimum for crude fibre, total ash, crude protein and fat contents were determined using the methods described by Pearson (1976). Total ash content was determined by furnace incineration using the method of James (1995). Moisture and carbohydrate contents were determined using the method described by AOAC (2000). Elemental Analysis: Mineral contents of processed samples were determined following the dry ash extraction methods Kirk et al., (1998) in Central Laboratory, Akwa Ibom State Ministry of Science and Technology. Calcium and magnesium were determined by Versanate EDTA titrimetric method (Udoh and Oguwale, 1986). Phosphorus in test sample was determined by Molybdo vanadate colorimetric method James (1995). Sodium and potassium was determined by flame photometry. Micro minerals (Zinc and Iron) were determined using atomic absorption spectrophotometer AAS 969 Model AOAC, (2000).

Data Analysis: Data were generated in triplicates and expressed as mean (±) standard deviation and was determined according to the method of (Steel and Torrie 1980).


The effects of organic and conventional method of farming on moisture contents in Ocimum gratissimum leaves is shown in table 1. The moisture content values of Ocimum gratissimum leaves grown in the organic and inorganic farming system was no statistically difference. The values of moisture content and dry matter content were higher in the inorganic farming than in the organic farming methods (organic and inorganic system of farming) used in the experiment. The increase in the moisture contents and dry matter contents of the leaf samples treated with organic manures (poultry dungs) and inorganic fertilizer may be attributed to the daily watering of the sample treatments, since the study was conducted in a controlled environment (greenhouse). Also the higher values of moisture and dry matter content recorded in organic and inorganic farming system may be attributed to the increase in soil fertility that enhance water and minerals uptake by plant. The values of crude protein were 15.00±0.20 and 22.25±0.20 in organic and inorganic farming system respectively. The values of crude fat and fibre content were 4.05±1.00 and 4.10±0.00 in organically farming method respectively. The values of crude fat and crude fibre were3.25±0.50 and 2.55±0.02 in inorganic farming system respectively. The values of carbohydrate and total ash content were 57.35±0.00 and 6.92±0.15 in organic farming system respectively, while the values of carbohydrate and total ash were 42.25±0.25 and 3.22±0.00 in inorganic farming system respectively. The mean values of food energy were 1460.38±1.10 (KJ/100g) in plant sample grown with organic method of farming, while the mean value of food energy obtained in inorganic farming method was (1275.20±0.00KJ/100g). The effect of organic and inorganic farming system of agriculture on mineral elements in the leaves of Ocimum gratissimum is presented in table 2. The result showed that there was significant difference between organic and conventional farming method of agriculture in proximate compositions and their mineral elements. In the soil samples treated inorganic fertilizer, , the leaves of Ocimum gratissimum gave the highest concentration of


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nitrogen (57.12±0.02), while the plant samples grown in organic method of farming showed a significant increase in calcium, magnesium, sodium and phosphorus. Consequently, plant samples grown in organic method of agriculture was higher in all the mineral nutrients including some essential micro elements determined (Fe and Zn). The values of iron and zinc in organic method of farming were 27.20±0.00 and 23.14±0.15 respectively, while the values of iron and zinc in the inorganic method of farming were 18.25±0.02 and 19.25±0.10 respectively. The results of mineral elements in the leaves of Ocimum gratissimum revealed that organic manure in the soil improves the mineral nutrients and proximate compositions of plants than synthetic fertilizer.

Table 1. Proximate Composition and Energy yield of Ocimum gratissimum leaves grown in organic and inorganic method of farming Proximate composition Organic method of Farming Inorganic farming method of

Moisture content 12.16±0.00 12. 20±0.01

Dry matter content 8.25±1.10 4.65±0.20

Total ash content 6.92±0.15 3.22±0.00

Crude fibre 4.10±0.00 2.55±0.02

Crude fat 4.05±1.00 3.25±0.50

Crude protein 15.00±0.20 22.25±0.20

Carbohydrate 57.35±0.00 42.25±0.25

Energy (KJ/100g) 1460.38±1.10 1275.20±0.00

The data are mean values (±) standard deviation of triplicates determination.

Table 2. Effect of farming methods on the mineral content of the leaves of Ocimum gratissimum Mineral elements Organic method of farming Inorganic method of farming

Nitrogen 42.14±1.15 57.12±0.02

Phosphorus 53.41±0.00 35.15±0.20

Calcium 45.20±0.15 32.45±0.00

Potassium 51.30±0.15 40.65±1.00

Sodium 39.76±0.35 27.50±1.55

Magnesium 32.19±0.25 23.15±0.00

Iron 27.20±0.00 18.25±0.02

Zinc 23.14±0.15 19.25±0.10

The data are mean values (±) standard deviation of triplicates determination.


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Discussion: The results from the analyses revealed that different farming methods (organic and conventional farming system) influenced the nutritional quality of Ocimum gratissimum leaves. According to Mjad (2012), nutritional quality is the value of the food for individual consumer’s physical health, growth, development, reproduction and psychological or emotional well-being. Vegetables produced from organic farming method recorded higher values of dry matter content, crude fibre, crude fat, total ash, carbohydrate and food energy content in the leaves of Ocimum gratissimum than conventionally grown crops. The result was similar with the study of Worthington, (2001) who reported that organic fruits and vegetables contained more nutrients than conventionally grown crops. The higher values of dry mater content, crude fibre, crude fat and carbohydrate observed from the leaves of Ocimum gratissimum grown in organic method of farming may be attributed to higher soil microorganisms content in the soil applied with organic manure (poultry dungs). Also, Heaton (2011) observed a similar trend of higher nutrients content in organically grown fruits than those fruits obtained from conventionally farming method. The result for crude protein were higher in the leaves of Ocimum gratissimum grown from conventionally farming method, while crops grown with organic farming method recorded the lower values. The high value of crude protein observed in the crops grown from conventional farming system may be linked with the application of synthetic fertilizer (NPK) to the soil. The results for crude protein agreed with the work of Salunkhe and Desai, (2008), who reported a lower nitrate content in organically grown vegetables, and less protein but higher quality protein in organic fruits. However, the higher values of crude protein in the leaf samples obtained from conventional method of farming may lower amounts of certain essential amino acids such as lysine and consequently have a lower quality in terms of human and animal nutrition (Mozafar, 2004). Thus, continuous application of synthetic fertilizer to crops will lead to increase in protein production and the excess is accumulated as nitrates which are stored in the green leafy part of the vegetables. The result showed that organic method of farming present plants with lower amounts of nitrogen than chemically fertilized soils. Raigón et al., (2010) reported that organic crops contained more vitamin C, less nitrates and less protein and higher nutritional quality than conventional crops.

The result also revealed that different cultivation method of farming influenced the concentration of mineral nutrients in the crops. The mean values of calcium, sodium and magnesium were 45.20±0.15, 39.76±0.35 and 32.19±0.25 respectively in the leaves of Ocimum gratissimum grown with organic method of farming, while the mean values of calcium, sodium and magnesium were 32.45±0.00, 27.50±1.55 and 23.15±0.00 respectively in the crops grown with conventional method of farming. However, there was no significant difference in the concentration of potassium and phosphorus in the plant samples grown with organic and conventional farming system. The result is in line with the work of Benbrook (2008), who reported a higher concentrations of minerals and other nutrients in organically grown crops. Also the results of Raigón et al. [2010] showed that organic manure and proper management of soil have a positive effect on the accumulation of certain beneficial mineral compounds like K, Ca and Mg in vegetables and fruit crops. The higher concentrations of mineral compound recorded in plant samples grown with organic method of farming may be attributed to the application of organic manure in soil that increased soil fertility and provide sufficient mineral nutrients to the soil. Also application of organic manure to the soil enhanced soil structure and microbial activities are encouraged (Reuss 1976). The mean values of some essential micro nutrients analyzed were higher in the leaves of Ocimum gratissimum grown with organic method of farming, while the mean values of these essential micro nutrient were low in plant samples grown with inorganic method of farming. The low values of trace metals in organic farming system may be due to the fact that organic farming does not use synthetic agricultural inputs such as synthetic pesticides, herbicides, fungicides, soluble mineral fertilizers, growth


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regulators trace mineral fertilizers and virtually never use fertilizers produced from industrial waste.

CONCLUSION The results of this study revealed that organically produced crops were found to have significantly higher levels of crude fat, dry matter content, carbohydrates, total ash and food energy than the inorganic produced crops. Also the mean values of mineral nutrients and some essential micro nutrients were higher in plant samples produced from organic method of farming than those obtained from inorganic method of farming. The study recommend organic agricultural practices because it is safe, environment friendly and does not has negative effects on human health. Also, the use of organic farming method in planting indigenous crops will enhance for security to Akwa Ibom state in particular and Nigeria as a whole.

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Baker, B.P., Benbrook, C. M, Groth, E, and Benbrook, K. I. (2006). Pesticide residues in conventional, integrated pest management (IPM) - grown and organic foods: Insights from three US data sets. Food Addit. Contam. 19:427– 446.

Benbrook, C., Xin, Z., Yanez, J. and Andrews, P. (2008). New evidence confirms the nutritional superiority of plant-based organic foods. An Organic Center State of Science.

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Heaton, S., (2011). Organic farming food quality and human health. A review of an evidence. Journal of Food and Nutrition. 4 (2): 17-31.

James C.S (1995). Analytical Chemistry of Foods, Chapman and Hall: New York; 52–55. Kirk, R.S, R. Sawyer R., and K. Walton (1998). Pearson’s composition and analysis of foods,

9th Ed. Addison Wesley Longman Ltd., England. Lester, G.E. (2007). Organic vs conventionally grown Rio Red whole grapefruit and juice:

comparison of production inputs, market quality, consumer, acceptance, and human health bioactive compounds. J. Agric. Food Chem. 55(11): 4474–4480.

Mayer, A.M. (2001). Historical changes in the mineral content of fruits and vegetables. Brit. Food J. 99:207–211.

Mozafar, A. (2004). Nitrogen fertilizers and the amount of vitamins in plants: A review. J Plant Nutr; 16: 2479–2506.

Miad, V. (2012). Effect of agricultural methods on nutritional quality: a comparison of organic conventional crops, Altern. Therapies Health Med., 2012; 4: 58-69.

Osborn, D.R. and Voogt, P. (1978). Calculations of calorific value in the analysis of nutrients Roots. Academic press, New York pp 239-240.

Pearson, D., (1976). The Chemical Analysis of Foods, Chivah Livingstone Edinburgh; 3-7. Reuss, J. H., Dooley, I and Griffis, W. ( 1976). Plant uptake of cadmium from phosphate

fertilizer. 600/3-76- 053. Corvallis, OR: Ecological Research Service:1–37. Roth, E., Berna, A. Z., Beullens, K., Schenk, B. J. and Nicolai, B. (2005). Comparison, of taste

and aroma of integrated and organic apple fruit. Commun. Agr. Appl. Biol. Sci. 70:225–229.

Salunkhe, D. K. and Desai, B. B. (2008). Effects of agricultural practices, handling, processing, and storage on vegetables. In: Karmas E, Harris RS, eds. Nutritional Evaluation of Food, Processing. New York: AVI Publishing Co: 23–71.


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Steel, R.G, and Torrie, J. H. (1980). Principles and procedures of statistics- a biometrical approach, 3rdedition, McGraw-Hill Book Coy. NY, USA.

Raigón, M .D. Rodríguez-Burruezo, A. and Prohens, P. (2010). Effects of organic and conventional cultivation methods on composition of eggplant fruits. J Agric Food Chem. 58 (11), 6833–40.

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Wiler, C., Woodward, L., Forde, G. and Vogtmann, H. (2009). The nitrate content of vegetable and salad crops offered to the consumer as from “organic” or “conventional” production systems, Biol. Agric. Hort.; 5: 215-21.

Worthington, V. (2001). Nutritional quality of organic versus conventional fruits, vegetables, and grains. J. Alter. Compl. Med. 7, 161–173.

Woese, K., Lange, D., Boess, C. and Bogl, K.W. (2000). A comparison of organically and conventionally grown foods—Results of a review of the relevant literature. J. Sci. Food Agr. 74:281–293.


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IMPACT OF FLOOD DISASTER ON SOIL QUALITY DYNAMICS IN AGRO-ECOLOGICAL ZONE OF EBONYI STATE, NIGERIA.

Ubuoh, E. A1. Uka, A2. and Egbe, C3. 1&3Department of Environmental Management and Toxicology (EMT), College of Natural Sciences

and Environmental Management (CNREM), Michael Okpara University of Agriculture, Umudike (MOUAU), Abia State, Nigeria.

2 Department of Fisheries and Aquatic Resource Management (FISHARM), College of Natural Sciences and Environmental Management (CNREM), Michael Okpara University of Agriculture, Umudike,

Abia State, Nigeria. Correspondence: [email protected] (+2348037639777)

ABSTRACT

The study focused on impact of Flood disaster on Soil Quality dynamics in Abakaliki Agro-ecological Zone of South-Eastern State, Nigeria, for proper soil and flood management to avert soil degradation. Soil samples were collected from three different floodplains and from arable land at the middle of the stream as control at the depth of 0-30cm, and were used for the determination of the selected soil quality. The treatments were replicated five times and data collected were analyzed using analysis of variance for complete randomized design. All the soil properties assessed were significantly different (p<0.05) among the study locations. The results further showed that apart from sand, BD, soil moisture that were higher in control, silt, clay and porosity were recorded highest mean values than control. Mean pH in floodplains recorded mean value of 5.9 being less acidic than control with the mean of pH5.38. Also apart from Available P.(38.50ppm),OC (1.89cmol/kg), Nitrogen (0.15cmol/kg), ECEC(18.16%) and BS(89.65%) being higher in control than floodplains, the mean of OM (2.5cmol/kg), Ca (10.5cmol/kg), Mg(4.7cmol/kg), K(0.14cmol/kg), Na(1.06cmol/kg) and EA(2.07) were higher in floodplains than control, which could support farming during flood cessation for increased food productions. Based on the results, it is recommended that flood best management practice should be encouraged in order to retain soil nutrients, reduce soil and water pollutions for ecosystem sustainability.

Keywords: Flood, Soil Quality, Agro Ecological Zone, Ecosystem sustainability

INTRODUCTION Flooding is the most common of all environmental hazards and it regularly claims over

20,000 lives per year and adversely affects around 75 million people world-wide (Smith, 1996). Across the globe, floods have posed tremendous danger to people's lives and properties. Floods cause about one third of all deaths, one third of all injuries and one third of all damage from natural disasters (Askew, 1999). In Nigeria, the pattern is similar with the rest of world. Flooding in various parts of Nigeria have forced millions of people from their homes, destroyed businesses, polluted water resources and increased the risk of diseases (Akinyemi, 1990; Nwaubani, 1991; Edward-Adebiyi, 1997; Askew, 1999). Soil nutrient dynamics in seasonal floodplain ecosystems are highly complex as a result of flood pulses and changing redoximorphic state (Dezzeo et al., 2000). Flood pulse refers to the alternating dry and wet conditions in floodplain ecosystems. It facilitates soil nutrient exchange between rivers and their associated seasonal floodplains Valett et al, 2005) .During floods, soil nutrients dissolve in floodwaters and are transported from seasonal floodplain surfaces into adjacent rivers, and soil nutrients may also be transported from the river into seasonal floodplains through lateral flow (Gallardo, 2003).

Ubuoh, E. A. Uka, A. and Egbe, C. (2017). Impact of Flood Disaster on Soil Quality Dynamics in Agro-Ecological Zone of Ebonyi State, Nigeria. Journal of Environment and Sustainable Development, 3(1): 143 – 153.


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Flooding can lead to both increases and decreases in soil nutrient content. In tropical regions, floods of high magnitude have resulted in serious consequences caused by heavy rainstorms, hurricanes, snow melt and dam failures Jeb and, Aggarwal, 2008). Flooding results in shortage of food crops due to loss of entire harvest and the destruction of soil quality. When a soil is flooded (anaerobic conditions), microorganisms use the available soil O2 to survive. Free O2 in the soil is usually depleted within a couple of days after flooding. The longer the soil is flooded, the lower the soil O2 levels become more reduced (Walls et al., 2005). Oxygen deficiency is likely the most important environmental factor that triggers growth inhibition and injury in flooded plants (Visser et al, 2003). Despite the significant consequences of flooding on the environment, flood plays an important role in maintaining key eco-system function and biodiversity in many natural systems. Flood deposits organic materials, minerals, and essential nutrients from rivers and oceans into land which makes the soil richer, fertile and productive. However, these environmental benefits come at a high price when excessive flooding occurs, since natural systems can no longer be resilient to the effects of large and excessive floods

(Visser et al., 2003). Increasing demand for land as a result of population increase and food scarcity has

made farmers to farm in marginal lands such as lands susceptible to erosion and flooding (Sanchez et al., 1997; Quansah, 1997). Flood contributes positively to soil properties through the provision of nutrients that maybe lacking in the soil Stephen, 1993; O’Connor and John, 2004). Wetting of the floodplains and meadows by floods releases immediate nutrients that were left over from the last flood and those that result from the rapid decomposition of organic matter that has accumulated during the flood. According to Njoku, and Okoro (2015), Njoku et al (2011), soil properties such as total porosity, moisture content, pH, and organic carbon were higher in a soil after flooding than before flooding.

Therefore, this study focused on the evaluation of the effect of flooding on soil properties dynamics in tropical agro-eco-zone in Abakaliki based on selected floodplains prone to flooding.


The study was carried out at the flood meadows along Ebonyi River in Abakaliki South-Eastern Nigeria. These flood meadows are among the major sources of dry season vegetable crops for Ebonyi people especially those residing at Abakaliki urban. Abakaliki lies at latitude 6o 15'N and longitude 8° 5'E in the derived savannah of South-Eastern Nigeria. The two distinct seasons within the zone are rainy season which lasts from April to October and dry season which lasts from November to March. The minimum and maximum temperatures of the area are 27°C and 31°C, respectively (Ofomata, 1075).The relative humidity of the area is between 60 to 80 percent. The annual rainfall of the area ranged between 1500 – 2000mm and the soil of the area belongs to the order ultisol classified as typic Haplustult (FDALR, 1975).

Soil Sampling Techniques: Soil samples were representatively collected with a soil auger at surface and subsurface depth (0-30cm) from the three flood plains that were randomly selected and from upland 200m away from the flooded farmlands, the flooded plains used for the study include: Iyiudele Floodplain, Iyiokwu Floodplain and Ebonyi River Basin. Collection of the soil samples were carried out after the nationwide flooding that rocked the entire country. Soil samples were representatively collected from three different floodplains at every 100 meters distance apart within the flood affected and control as flood unaffected sampling areas respectively. Soil samples collected from the individual locations were bulked, thoroughly mixed and stored in clean polythene bags prior to laboratory analysis. Laboratory analysis: Bulk density (Bd) and saturated hydraulic conductivity (Ksat) were determined using method according to Grossman and Riensah (2002). The auger soil samples


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were air-dried in the laboratory ground and passed through a 2 mm sieve. Sieved samples < 2 mm soil fraction was bagged for routine analysis. The fraction of sand, silt and clay was determined using hydrometer method (Gee and Or, 2002), with NaOH as dispersant. Soil pH was determined by McLean (1982) method. Total nitrogen was determined using micro- Kjeldahl method Bremner and G Mulvaney, 1982). Soil organic carbon was measured by combustion at 840°C (wet-oxidation method) (Wang, 2004). Exchangeable bases, Ca2+ and Mg2+ were obtained by ammonium acetate (NH4 OAC) method, and Na+ and K+ by flame photometer. Cation exchange capacity (CEC) was obtained using method by Blakemore (1987). Exchangeable acidity was determined titrimetrically using 0.05 N NaOH. Available phosphorus was obtained using Bray 11 bicarbonate extraction method as described by Olsen and Sommers (1983).

Statistical Analysis: Analysis of variance was used to test differences in physical and chemical properties across the three selected floodplains and the inland area as control, significant variations in the means were determined using least significance difference (LSD0.05) test (Steel and Torie, 1980). Correlation analysis was carried out to detect functional relationship among key soil variables. All the analyses were done using a statistically software package (SAS Institute Inc, 2001).


Table 1: Mean and F-FSD of the Effect of Flooding on Particle Size distribution of Flooded Soil

Soil Samples % Sand % Silt % Clay Textural Class Iyiudele Floodplain 36.40 36.80 26.80 Clay Loam Iyiokwu Floodplain 42.40 36.80 20.80 Loam

Ebonyi River Basin 32.40 34.80 32.80 Clay Loam Total 111.2 108.4 80.4 - Mean 37.1 36.1 27 - Control /Upland 44.40 34.80 20.80 Loam F-LSD 0.05 0.45 0.22 0.18

Particle Size Distribution (PSD): Table 1 shows the distribution of particle size distribution of flooded soils. From the results, sand compositions in the study locations ranged between 32.30 -44.40% with Ebonyi River Basin having the lowest values and Iyiokwu Floodplain having the highest value with the mean value of 37.1% lower than the control/upland with 44.40 % with F-LSD 0.45.It shows that there is high percolation rates and low capillary action at control. From silt, the result ranged between 34.80 – 36.80% with Ebonyi River Basin having the lowest value and Iyiudele, Iyiokwu Floodplains having the highest values respectively with the mean value of 36.1% above 34.80% of control with F-LSD 0.22. The results also indicated that Iyiudele floodplain and Iyiokwu floodplain had the highest values of 36.80% respectively. Clay composition ranged between 20.80-32% with Iyiokwu having the lowest value and Ebonyi Floodplain recording the highest value than all with the mean value of 27% above the control with 20.80% all having F-LSD 0.18. The results show that the study areas are more fertile than control which is good for agricultural. The textural class of Iyiudele floodplain was clay loam and Ebonyi River. The result also showed that the textural class for Iyiokwu floodplain and control was loam. It shows that Iyiudele floodplain and Ebonyi River basin is good for cultivating rice, carrot, cucumber, etc., while control and Iyiokwu floodplain is good for cultivating maize, groundnut, yam melon, etc. The result is in line with the observation by Obi (2000), who stated that texture was a permanent component of the soil and do not change as much with time.


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Table 2: Mean and F-LSD of the Effects of Flooding on Soil Physical Properties in the study locations Soil Samples Bulk Density

(gcm-3) Percentage Moisture content (%)

Gravimetric Moisture

Porosity

Iyuidele Floodpain 1.20 22.48 0.29 54.50 Iyiokwo floodplain 1.30 19.34 0.24 51.10 Ebonyi River Basin 1.24 24.78 0.33 53.30 Total 3.73 66.6 0.86 158.9 Mean 1.24 22.2 0.3 53 Control/Upland 1.61 9.88 0.11 39.20 FLSD (0.05) 0.13 2.98 0.01 3.92

Bulk Density (BD): The result of bulk density indicated significant differences among the samples at (P<0.05). The result shows that bulk density ranged between 1.20-1.30 gcm3 with the mean value of 1.24 gcm-3 below 1.61 gcm-3 of the control having LSD 0.13.The result also showed that control had the highest value of 1.61 gcm-3 while Iyiudele floodplain had the lowest value of 1.20gcm-3. According to Obi (2000), soil properties such as bulk density have a large influence on denitrification activities of flooded soils. Under saturated soil conditions, losses of soil nitrogen can be substantial, nitrate nitrogen can be lost by leaching down and out of the reach of crops. While leaching occurs rapidly on coarse textured sandy soils, it is a slower process on loam and clay soils due to slower water movement. The gaseous loss of nitrogen by denitrification occurs when soil microorganisms reduce nitrate under saturated conditions, leading to loss of nitrogen gas. In addition, soil microorganisms are not very effective at decomposing crop residues and organic matter when the soil is saturated, slowing the release of nitrogen from this source (Adriano, 2001).

Moisture content (MC): The result of percentages moisture content showed that there were significant differences among the treatment at (P<0.05).The result ranged between 19.34-24.78% with the mean value of 22.2% above 9.88% of the control location with LSD being 2.98. The result also showed that Ebonyi River Basin recorded the highest value of 24.78% followed by Iyiudele while control recorded the latest value of 9.88%. This showed that percentage moisture content contributed to the denitrification activities of Iyiudele flooded soil. According to Nelson and Terry (1996), percentage moisture is a contributing factor to denitrification activities of flooded soils.

Gravimetric Moisture Content (GMC): The result indicated that there significant differences among the soil samples at (P<0.05) in gravimetric moisture content. The result ranged between 0.24-0.33 with the mean value of 0.3 lower than LSD 0.11. The result further indicated that Ebonyi River Basin had the highest value of 0.33 while control had the lowest value of 0.11. It shows that the rate of denitrification activities are higher at Ebonyi River Basin and Iyiudele but lowest at upland or control.

Porosity: The result of porosity indicates significant difference among the treatment at (P<0.05) in porosity. The result then ranged between 51.10-53.30% with the mean value of 53% above 39.20% of the control with LSD being 3.92. The result further states that Iyiudele floodplain had the highest value of 54.50 while the control had the lowest value of 39.2%. It shows that the rate of infiltration and the water-holding capacity is higher at Iyiudele floodplain and lowest at control. Nelson and Terry (1996) observed that soil physical properties such as porosity are poor during flooding and increase denitrification activities of the soil.


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Table 3: Mean and F-LSD of the Effect of Flooding on Chemical Properties of the samples.

Soil Samples Avail. Phosphorous pH (H20) % Organic Carbon

% Organic Matter

% Nitrogen

Iyiudele Floodplain 34.80 6.15 1.12 1.63 0.13

Iyiokwu Floodplain 29.20 5.89 1.80 3.11 0.15 Ebonyi River Basin 28.20 5.95 1.53 2.65 0.14 Total 92.2 18 4.45 7.39 0.42 Mean 30.7 5.9 1.5 2.5 0.14 Control /Upland 38.50 5.38 1.89 0.13 0.15 F-LSD 0.05 0.44 0.001 0.04 0.01 0.007

Available Phosphorus (AP): The result of available phosphorus showed that were significant differences among treatments in available phosphorous at (P<0.05). The result of available phosphorus ranged between 28.20-34.80 with the mean value of 30.7 below the control with 30.50 having F-LSD 0.05 -0.44. The result further indicates that control had the highest value of 38.50ppm, while Ebonyi River Basin had the lowest value of 28.20ppm (Table3). The result showed that there is large amount of phosphorus in Ebonyi River Basin and Iyiudele Floodplain had 34.80ppm. Nathan (2002) observed that flooding generally increases the availability of phosphorous to crops especially rice which is at variance with the present study. Possible leaching of available phosphorusas phosphate in the soil by the flood could account for this observation, since in water columns, anaerobic conditions renders it soluble. Phosphorus reduction in the flood affected farmlands is in strong contrast with the findings of Kalshetty et al. (2012), where increased phosphorus levels were seen in flood affected cultivated soils in India.

pH: The result of the soil pH (H2O) indicated significant differences among treatment in pH at (P<0.05). The soil pH ranged between 5.15-615, with the mean value of 5.9 greater than 5.38 as control with F.LSD being 0.001.These values are in the same range with the values reported by Oviasogie and Omoruyi, 2007; Oviasogie and Ofomaja, 2007; Osakwe, 2012), but lower than the values reported by Jung (2008), Obasi et al. (2012), Osakwe (2014) . The result also showed that Iyiudele floodplain had the highest value of 6.15 and the control treatment had the lowest value of 5.38. It shows that the Iyiudele floodplain and Ebonyi River Basin are good for agriculture with pH range of 6.15, 5.85 and 5.95 respectively. Snyder (2002) observed that after a soil is flooded regardless of its original pH before flooding, the pH would approach neutrality (6.5 to 7.5). Micronutrients may also be influenced by soil wetness. Soluble manganese (Mn) concentrations may "explode" in flooded soils, interfering with iron (Fe) nutrition and causing iron chlorosis, especially in flax. Flooding of alkaline (high pH or high lime) soils causes a buildup of bicarbonate, which interferes with iron uptake and causes iron deficiency and chlorosis (Amarawansha et al., 2014).

Organic carbon (OC): There were significant differences between the treatment at (P<0.05) in percent organic carbon. The results of OC ranged between 1.12-1.80%, with the mean value of 1.5% less than 1.98% of control having LSD of 0.04. The result further showed that control treatment had the highest value of 1.89 % while Iyiudele floodplain had the lowest value of 1.12%. The above shows that there is a bacterial decomposition or ration that has taken place in the Iyiudele floodplain, thereby reducing the content to 1.12 % that is the organic carbon is low. A slight reduction in total organic carbon was observed in the flood affected farmlands, which could bead due to the effect of flooding; as most soil organic content such as organic acids and humus which are the sole source of organic carbon could have been leached out by the impact of the flood. Decreased organic carbon content of soil adversely affects soil quality


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and fertility since organic carbon is required to stimulate microbial respiration and activities. The reduced organic carbon content in the flood affected farmlands is at variance with the findings of Kalshetty et al (2012) where increased organic carbon content was observed in flood affected cultivated areas in India.

Organic Matter (OM): There were significant differences among treatments at (P<0.05) in percent organic matter. The result ranged between 1.63-3.11% with the mean value of 2.5% greater than 0.13 as control wit LSD being 0.13%. It also showed that control or upland treatment had the highest value of 3.26 % while Iyiudele floodplain had the lowest value of 1.93 %. It shows that the control has large amount of organic matter decomposed into humus. The results conformed with the finding of Chen et al. (2005), who observed that, soil flooding can cause hypoxia leading to a reduction in the soil nutrient content available to plants .As a result of hypoxia, the organic matter decomposition rate is reduced (Visser et al, 2003), leading to low soil nutrient content release (Teyler, and Olsson, 2001) .Another factor that could lead to reduced soil nutrients during high flood is the rate of decomposition of organic matter. Organic matter is a reservoir of nutrients which are released when it decomposes (Gosz, et al., 1976).During flooding, water displaces oxygen from the soil (Lobo and Jolly, 1998; Hefting et al., 2004), leading to anaerobic conditions (Moorhead and McAuthur, 1996). Under anaerobic conditions, the rate of decomposition of organic matter declines, resulting in low soil nutrient content.

Total Nitrogen (TN): There were significant differences among treatment at (P<0.05) in percent nitrogen. Results ranged between 0.13-0.15% with the mean value of 0.14% less than control being 0.15%, with 0.007 LSD. It also showed that the control treatment and Iyiokwu floodplain had the highest values of values of 0.15 % while Iyiudele floodplain had the lowest value of 0.13 %. It indicates that there will be rapid fruiting and ripening of fruiting and there will be increased resistance in grains in Iyiudele floodplain.

Table 4: Mean and F-LSD of the Effects of Flooding on soil Exchangeable basis

Soil Sample Ca (Cmol/kg) Mg (Cmol/Kg) K(Cmol/kg) Na (Cmol/kg)

Iyiudele Floodplain 11.20 5.20 0.154 0.096 Iyiokwu Floodplain 8.40 3.60 0.133 0.087 Ebonyi Basin 12.00 5.20 0.133 0.135 Total 31.6 14 0.42 0.318 Mean 10.5 4.7 0.14 0.106 Control/Upland 12.40 3.60 0.133 0.087

FLS(0.05) 0.17 0.11 0.007 0.002

Calcium (Ca): Table 4 showed that there were significant differences among treatments at (P<0.05) in Calcium. The also indicated that control treatment had the highest value of 12.40 Cmol/kg followed by Iyiudele with 11.20Cmolkg-1 while Iyiokwu floodplain had the lowest value of 8.40Cmol/kg. Willet (1989) observed that flooding affected soil properties including exchangeable cations like calcium. These results are consistent with findings from previous studies. Alfaia and Falcao (1993), Antheunise and Verhoeven (2006), Humphrie (2008) observed that Ca content decreased with an increase in moisture content during flooding.

Magnesium (Mn): Table 4 showed that there were significant differences among treatments at (P<0.05) in magnesium. It also showed that Iyiudele floodplain and Ebonyi River basin had the highest values of 5.20Cmol/kg while Iyiokwo floodplain and control or upland had the highest values of 3.60Cmol/kg. But a reduction in Mn concentration in the affected soils on account of the flooding effect is not a healthy development because these are essential


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micronutrients required in the soil for improved soil productivity .Reduced levels of manganese and potassium in the flood affected farmlands are in strong contrast with the findings of Kalshetty et al. (2012), where increased levels were seen in flood affected cultivated soils in India.

Potassium (k): The result showed that there were significant differences among treatments at (P<0.05) in potassium. The results also showed that control has the highest value of 0.174Cmol/kg, followed by Iyiudele floodplain with 0.154cmol/kg-1 while Iyiokwu floodplain and Ebonyi River basin had the lowest value of 0.133Cmol/kg (Table 4). The result was further explained that, It was found that P binding to clay decreased with an increase in pH from 7 to 9, which was attributed to formation of hydroxyl species of the lanthanum ions decreasing the number of P binding sites on the clay sites (Ross et al., 2008). A high flood is expected to lead to anoxic conditions because of increased water depth and prolonged waterlogging, which leads to mobilization of P and results in its increase (Akinyemi, 1990; Askew, 1999). Under aerobic conditions, P binds to iron oxides. Because of prolonged anaerobic conditions imposed by flooding, Fe bound to P is reduced from Fe (III) to Fe (II), releasing P from iron-phosphate complexes (Dezzeo et al., 2000; Gallardo, 2008; Brady and Weil, 2008).It is expected that during low flooding conditions, P reacts with Ca, Al and Fe oxy-hydroxides as a result of aerobic conditions, consequently reducing its available content in the soil. Potassium is a macronutrient that is not only required for healthy plant growth in the soil, but also for proper microbial functioning; therefore a reduction in potassium levels in the flood affected soils is a negative impact on soil quality. Sodium (Na): Table 4 showed that there were significant differences among treatments at (P<0.05) in sodium. It also indicated that Ebonyi River Basin had the highest value of 0.139Cmol/kg and control had 0.104Cmolkg-1 and Iyiudele recorded 0.096Cmolkg-1 while Iyiokwu floodplain had the lowest value of 0.087Cmol/kg. All these showed that there is loss in exchangeable cations during flooding. Low Ca, Mg, K and Na during high flood in the study locations could be a result of leaching and dilution (Conklin,2005), because flooding increases the solubility of mineral nutrients (Mitsch and Gosselink, 2000) .It could be expected that during a high flood more soil nutrients dissolve in water and are lost through leaching as water infiltrates the soil. It could also be expected that because clay is negatively charged (Barber, 1995), cations would bond to the soil particles, thus reducing leaching. However, leaching of cations has been found to be accelerated by dissociation of NO3- from HNO3 (from nitrification) (Barber, 1995) , and study locations experienced high flooding depth and long flooding duration, which would suggest that more of their soil nutrients dissolved in the water and were lost through leaching.

Table 5: Mean and F-LSD of the Effect of Flooding on Exchangeable Acidity, Effective Cation Exchange Capacity and % Base saturation.

Treatment Exchangeable Acidity ( Cmol/kg-1)

ECEC (Cmol/kg-1) % Base Saturation

Iyiudele Floodplain 2.08 18.73 88.89 Iyiokwu Floodplain 1.96 14.18 86.18 Ebonyi River Basin 2.16 19.63 88.99 Total 6.2 52.54 264.1 Mean 2.07 17.5 88.02 Control/Upland 1.88 18.16 89.65 FLS (0.05) 0.03 0.53 1.40

Exchangeable Acidity (EA): There were significant differences among the treatments at (P<0.05) in exchangeable acidity. The result also showed that Ebonyi River Basin had the highest value of 2.16 Cmol/kg-1 while the control or upland had the lowest value of 1.88Cmol/kg (Table 5). The showed that there is high rate of acidity in Iyiudele floodplain compared to that in the control meaning that there is high rate of negative changes on soil clays


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and organic matter in Iyiudele floodplain. Oorts et al. ( 2003) observed that flooding affects the exchangeable acidity of soil due to its intensity.

Effective Cation Exchange Capacity (ECEC): The result indicated that there were significant differences among the treatments at (P<0.05) in effective cation exchange capacity. It also showed that Ebonyi River Basin had the highest value of 19.63 Cmol/kg-1 while Iyiokwu floodplain had the lowest value of 14.18Cmol/kg-1 and Iyiudele recorded 18.73cmolkg-1. It indicates that there is high presence of negative charges on soil clays and organic matter in Iyiudele, Ebonyi River Basin compared to control. Reduced organic matter in the flood affected soils could have also accounted for the reduction in cation exchange capacity, since organic matter contributes to the cation exchange capacity of the soil by increasing adsorption sites for cations (Oorts et al., 2003). Reduced cation exchange capacity is not favorable for agricultural soil because it limits the availability of essential positively charged macro and micro nutrients to be adsorbed on soil particles, since few negatively charged sites will be available to attract them. The reduction in cation exchange capacity levels on the flood affected farmlands is similar to the findings of Kalshetty, et al. (2012), where reduced levels were also observed on flooding of cultivated areas from river Krishna in Southern India.

Percentage Base Saturation: There were significant differences among the treatment at (P<0.05) in percentage base saturation. The result also showed that the control treatment had the highest value of 89.65% while Iyiokwu floodplain had the lowest value of 86.18%. Ebonyi River Basin recorded 88.99 % and Iyiudele floodplain had 88.99 % according to Ohiri et al. (1989) who observed that there is a loss in percentage base saturation during flooding.

CONCLUSIONS AND RECOMMENDATIONS The results obtained from the study showed that most of the available nutrients added to the soil during the flooding are washed down slope to the lower course of the river. For instance, flooding increases the availability of phosphorus to soils (Nathan, 2002), but in the result obtained upland (control) had the highest value of phosphorus while the other three soil samples collected from flooded land had low values of available phosphorus. This could be attributed to the washing of nutrients through runoff along the river channel where the samples were collected down to the lower course of the river. These results have direct implications for flood recession farming. It is then recommended that:

Recommendations: � Farmers operation on the floodplains should plough immediately after the onset of flood

recession when the soil is still moist and rich in nutrients. Those crops that could be planted and harvested before the rain sets in should be cultivated within the floodplain.

� Measures should be put in place by government and concerned State Ministries of Water Resources and Environment and agency like, National Emergency Management Agency (NEMA) to help reduce the possibility of future flooding of farmlands in order not to further expose the natural quality of these agro-ecological zone to the degradative and devastating effects of flooding. This will also reduce pollution and siltation/sedimentation of the rivers that serve as habitat for aquatic lives, hence extinction.

� The use of field boundaries, such as hedges and stone walls and buffer strips can act as potential traps for runoff, increasing the time for infiltration into the soil and reducing the flow connectivity and retain soil fertility for increased food production.


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EFFECTS OF CROP RESIDUE ASH APPLICATION ON SOIL, COWPEA YIELD AND ECONOMIC RETURN TO MANAGEMENT IN UYO, NIGER DEL TA

REGION OF NIGERIA

Ikeh, A. O1., Etokeren, U. E2., Essien, I. E2., Udo, E. A2., Ukut, A.N2. and Nwanne, A. J3. 1- Department of Crop Science, University of Uyo, Uyo. Akwa Ibom State, Nigeria.

2-Department of Agricultural Technology, Akwa Ibom State College of Arts and Science. Nung Ukim, Ikono Akwa Ibom State, Nigeria.

3- Department of Horticulture and Landscape Technology, Akanu Ibiam Federal Polytechnic Unwana Afikpo, Ebonyi State, Nigeria.

Corresponding author’s contact: [email protected], Phone +234(0)8033934217

ABSTRACT Soil acidity is a major hindrance of legume production in high humid region of Niger-delta of Nigeria. In this investigation, effect of crop residue ash level and source were evaluated in 2012 and 2013 cropping seasons as potential source of lime with aim of reducing soil acidity and increase cowpea yield. The experiment was laid out in a randomized complete block design with split plot arrangement replicated three times. The main treatment were three ash levels; 0, 2.5 and 5 t/ha while sub-treatment were three sources; cocoa pod, plantain bunch/peel and oil palm bunch. Result showed that application of 5t/ha of crop residue ash resulted to 9-28% and 9-27% increase in soil pH in 2012 and 2013 cropping seasons respectively with significant increase in organic matter; 39% and 37% respectively above control treatment. Application of crop residue ash led to significant increase in number of leaves per plant and number branches per plant. Application 5t/ha of ash led to significant increase in grain yield of 543.26 and 644.03 kg/ha in 2012 and 2013 cropping respectively, followed by 537.09 and 628.29 kg/ha respectively harvested from the treatment that received 2.5t/ha of ash, compared to the least yield of 290.01 and 291.69 kg/ha respectively obtained from control treatment. The result further indicated that the application of 5t/ha of ash had grain yield of 47% and 55% more than the control treatment in 2012 and 2013 cropping seasons respectively with only 1 and 2% respectively more than the treatment of 2.5t/ha of ash. Results of economic returns to management revealed that the use of 2.5t/ha of had the highest benefit ratio of 2.04 and 2.44 in 2012 and 2013 respectively while 5t/ha application had 2.0 and 2.44 benefit ratio respectively. Zero application had least benefit ratio of 0.71 and 0.66 respectively. The study therefore concluded that application of crop residue ash irrespective of source could be alternative to highest cost and scare conventional liming materials in reducing soil acidic in Niger-delta region.

Keywords: Crop residue, ash, cowpea, yield, economic return

INTRODUCTION The soils of southeastern Nigeria are predominately ultisols, with pH value of less than 5.5 (Ahn, 1993) and these soils are acidic in nature and also, they are highly weathered (Brady and Weil, 1999). The acidity of this region is as a result of heavy rainfall and excessive leaching of basic cations leaving the exchange complex dominated by A3+ and H+ ions (Ogunwale et al., 2002). Also, the development of acid soils may be as a result of continuous use of nitrogenous fertilizers (Ano and Agwu, 2005) and other fertilizer salts like potassium chloride and magnesium sulphate which increases the concentration of Aluminum in soil solution and hence depress the pH level of the soil (Akinmutimi and Agwu, 2014). Soil acidity has been tagged a

Ikeh, A. O., et al. (2017). Effects of Crop Residue Ash Application on Soil, Cowpea Yield and Economic Return to Management in Uyo, Niger Delta Region of Nigeria. Journal of Environment and Sustainable Development, 3(1): 154 – 165.


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problem to global food production (Chude et al., 2004) and most notable effects of soil acidity is drastic reduction in crop yield which is as a result of decrease in nutrient uptake especially phosphorus nitrogen and potassium (Mullins et al., 2005). The presence of high amount of Aluminum (Al) and manganese (Mn) in the soil solution of acid mineral soil is detrimental to plant growth (Onyekwere et al., 2005).

Acidity of soil due to high Aluminum toxicity aluminum toxicity is a major limitation to leguminous crop production in ultisol of southeastern Nigeria. Aluminum (Al) is the abundant metal in the earth’s crust and occurs in a number of different forms in the soil (Adegoke et al., 2013). It is generally accepted that Al toxicity is a primary factor limiting plant growth on acid soils (Koachian, 1995). Toxic effects of the elements on plant growth have been attributed to several physiological pathways, but the precise mechanism include Al interaction with the root cell wall, aluminum disruption of plasma membrane and membrane transport processes, and Al inhibition of mineral uptake and metabolism, especially that of Ca and P. (Rout et al., 2001).

Besides salinity, Al toxicity is among the widespread problems of ion toxicity stress in plants. Poor growth in acid soils could be related directly to Al saturation (Akinrinde et al., 2004). In acid soils, Al toxicity limits plants’ growth due to series of chemical interaction including toxicities of H, Al and Mn (Adegoke et al., 2013). Estimate of soil limitation to plant growth in developing countries showed that an average of 23% of soil used is constrained to Al toxicity (Oluwatoyinbo et al., 2005). The restriction of plant growth by excess soluble Al in acid soils may arise from either the direct inhibition of nutrient uptake or disturbance of root cell functions (Kochian, 1995).

Aluminum exists in soils in many mineral forms including hydrous oxide, aluminum silicates, sulphates and phosphates (Adegoke et al., 2013). Accumulation and distribution of many minerals elements are often strongly affected by aluminum. A common symptom of soil acidity due to aluminum toxicity is P deficiency symptoms (Haynes, and Mokolobate, 2001). Acid soil results from leaching of basic cations (in area of high rainfall), leaving behind the more resistant Al3+ which predominates (Adegoke et al., 2013).

Soil acidity is normally corrected by application of lime. Liming has a beneficial effect on plant growth under aluminum toxicity (Bessho and Bell, 1992). In many developing countries in sub-Sahara Africa where subsistence farming is pronounced and dominated, unavailability, inaccessible and high cost of conventional liming materials like dolomite and calcitic prevent the effective use of conventional liming materials. It has been also discovered that liming may also have some negative effects on plant growth and soil properties (Ahmad and Tan, 1986). Deficiencies for example of some nutrients such as P, Sn, B, and Mn can be induced by liming.

A number of workers have shown that addition of green manure, animal waste and ashe to acid soils can reduce aluminum toxicity and increase crop yields (Adegoke et al., 2013; Ikeh et al, 2013a; Akata, 2015). Application of organic fertilizer have also shown to increase nutrient uptake and crop growth (Ikeh et al., 2015; Akata, 2015). The application of organic residue to avoid acid soils in order to minimize the need for lime and P fertilizer application would be beneficial to poor resources farmers especially in Niger-delta region of Nigeria.

Cowpea (Vigna unguiculata Walp) is dicotyledonous spermatophyte belonging to the family fabaceaceae. The plant is an annual crop grown virtually all over the world. It is a major staple food crop in sub-Saharan Africa, especially in the dry savanna regions of West Africa (Abdullahi et al., 2012). The seeds are major source of plant proteins and vitamins for man, feed for animals and also a source of cash income (Abdullahi et al., 2012; Ikeh et al., 2013b). Cowpea prefers light sandy loam soils and soil reaction of pH 5.5-6.5 and does not tolerate saliniity and acidity (Maiyaki 2012). Cowpea’s ability to fix up to 70-350kg Nha-1 from atmosphere in association with nodule bacteria (Bradyrhzobium spp) and replenished soil with


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40-80kg Nha-1yr-1 (Quin, 1997) made it good for soil amendment green manure and cover crop (Maiyaki, 2012). The leaf litter from shed leaves and flowers and root residues decay in-situ, contributing some organic matter and associated nutrients to the soil. The spreading habit of cowpea provides good ground cover thus suppressing weeds and act as protection against soil erosion (Maiyak, 2012; Ikeh et al., 2013b).

In southeastern and Niger-delta region of Nigeria, cowpea could be consumed in many ways such as; preparing ‘akara’, moi-moi, porridge, or in a combination with starch or energy food such as rice/beans, yam/beans, maize/beans etc. production of cowpea in Niger-Delta region of Nigeria is faced with many problems such as high salinity and acidity of soils of the region, high pest/disease infestation, poor agronomic practices such as time of planting and high rainfall duration and intensity. Planting of cowpea between early September to first week of October have been reported as optimum planting date of cowpea within the region in order to encourage high yield and low pest/disease infestation (Ikeh et al., 2013b) indicating that those constraints could be reduced by planting between September but issue of acidity has not received much attention.

Many authors had reported on ways, to reduce aluminum toxicity through conventional methods but information on non-conventional methods like use of locally available soil amendments have not been fully reported. Therefore, the present study was conducted aimed to determine the effect of application of crop residue ash on soil chemical properties, cowpea and economic return to management.


This work was conducted in 2012 and 2013 late planting seasons at National Cereals Research Institute (NCRI) Uyo outstation. Uyo lies between latitude of 4°30' and 5°27' and longitudes 7°50'E and 80°20'E sea level and receives about 2500mm rainfall annually. The rainfall pattern is bomodal, with long (March-July) and Short (September - November) rainy seasons usually during the month of August that is traditionally referred to as “August break” (Peters et al., 1989). The mean relative humidity separated by a short dry spell of uncertain length is 78%, atmospheric temperature 30°C and day length of 12 hours.

The experiment was laid out in a randomized complete block design with split plot arrangement and replicated three times. The entire experimental site measured 40 m x 18 m. The main plot dimension was 14 m x 4 m while sub-plot dimension was measured 4 m x 4 m. Each replicate was separated from the other by a 2m path while each main and sub plots were separated from other by 1m path. The main treatments were three crop residue ash levels viz; 0, 2.5 and 5 t/ha while three different sources; cocoa pod, plantain bunch/peel and oil palm bunch constituted the sub-treatments. The experimental site was manually cleared with machete, ranked, marked out and seedbeds of 4 m x 4 m were constructed. Composite soil sample was collected at random before planting and at harvest at soil depth of 20 cm. The three cowpea (Ife Brown cultivar) seeds were sown at spacing of 75 cm x 60 cm and later thinned to one per stand. Crop residue ashes were incorporated in the soil during land preparation based on treatment basis. Manual weeding was done at 3 weeks after sowing, by hand hoeing.

The following growth and yield parameters were assessed; emergence percentage, number of leaves per vine, number of branches per plant, number of pods per plants, weight of 100 seed, (g) and grain yield in kilogram per hectare. Cost of production and economic returns to management cowpea as influenced by ash level and source was determined with partial budget method (Ndaeyo and Aiyeleri, 2010). Soil chemical properties, growth and yield data obtained were subjected to analysis of variance (Anova), while least significant difference was used to compare significant different at probability of 5 percent.


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The results of some chemical content of cocoa pod, plantain bunch/peel and oil palm bunch ashes presented in Table 1, shows that the ashes had higher pH in water; 8.80, 8.90 and 9.10 for cocoa pod, plantain bunch/peel and oil palm bunch ashes respectively with higher organic carbon, available P and exchangeable bases. The result of higher pH values of the ashes was indicative that these crop residue ashes had liming potential to ameliorate soil acidity. The physico-chemical properties of experimental site before planting is shown in Table 2. In both cropping seasons (2012 and 2013), the results indicated that the soil of the experimental site was acidic with pH values of 4.60 and 4.50 in 2012 and 2013 respectively. The organic matter and total nitrogen were low. The exchangeable bases such as K were low (0.21 and 0.23 cmolkg-1) in 2012 and 2013 respectively with high exchangeable acidity of 1.60, respectively. Results of particle size distribution revealed that the experimental soil was predominately sandy soil of 87% and 85% sand in 2012 and 2013 cropping seasons, respectively. The results of some chemical properties of the soil at harvest which includes organic matter content, total nitrogen and soil pH is shown in table 3. The result indicated significant increase in organic matter, total nitrogen and soil pH with increase in crop residue ash level in both cropping seasons. Application of 5 and 2.5t/ha led to 2.97 and 2.55 % organic matter content in 2012 and 2013 cropping seasons respectively compared to 1.71 and 1.60 % respectively recorded in control treatment. Application of 5t/ha resulted to 20-39 % and 14-37 % increase in soil organic matter content in 2012 and 2013 cropping seasons respectively. The result further indicated that application of 5t/ha resulted to increase in total nitrogen, 0.16 respectively (Table 3), with 13-63% and 13-75% increase more than control(no soil amendment) and 2.5t/ha level in 2012 and 2013 cropping seasons, respectively. Control plot had only 0.06% and 0.04% total nitrogen respectively. The result also showed significant increase in soil pH with increase in ash level. Treatment that received 5t/ha of ash led to soil pH level of 7.47 and 7.22 at harvest in 2012 and 2013 cropping seasons respectively (Table 3), whereas application of 2.5t/ha, has soil pH value of 6.77 and 6.60 on average respectively compared to acidic pH value of 5.40 and 5.27 recorded in 2012 and 2013 cropping seasons respectively. Comparing the percentage increase in soil pH, application of 5t/ha of ash had 9-28% and 9-27% high soil pH value above other treatments in 2012 and 2013 cropping seasons respectively. Comparing the effect of crop residue ash source on soil organic matter content, total nitrogen and soil pH, the results showed no significant differences among the treatments (Table 3). The results of interaction between organic ash level and source in all the tested soil chemical properties at harvest in both cropping seasons showed no significant difference. Influence of crop residue ash level on emergence percentage of cowpea in both year of trials was not significantly difference (p<0.05) (Table 4). In both cropping seasons high emergence percentage range of 97.67-99.33 and 98.50 – 99.9% was recorded in 2012 and 2013 cropping seasons respectively. Number of cowpea leaves per vine as influenced by crop residue ash level varied significantly (p<0.05) only at 2 and 3 months after sowing (MAS). The highest number of cowpea leaves per plant was recorded in treatment that received 5t/ha of ash, followed by application of 2.5t/ha while zero application that the least number of leaves per vine. Application of 5t/ha of ash resulted to 36.31 and 37.68 number of leaves per cowpea vine at 3MAP in 2012 and 2013 cropping seasons respectively, while 34.98 and 34.89 leaves per vine at 3MAP was recorded in 2.5t/ha ash treatment in 2012 and 2013 cropping season respectively. Effect of crop residue ash source on cowpea emergence percentage and number of leaves per vine showed no significant difference (p<0.05) in all the months under observation. The interaction effect between crop residue ash level and source on number of


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cowpea leaves per vine also showed no significant difference (p<0.05) in all the weeks under observation. Number of cowpea branches per plant as influenced by crop residue ash level indicated significant difference (p<0.05) in all months under investigation with application of 5t/ha resulting to highest production of branches per plant; 11.85 and 12.84 at 2 and 3 MAS respectively in 2012 with corresponding mean values of 12.04 and 12.99 in 2013 cropping season (Table 5). Treatment that received 2.5t/ha of ash resulted to 12.43 and 12.31 branches per plant in 2012 and 2013 cropping seasons respectively whereas 8.44 and 8.61 branches respectively was recorded in control treatment. The interaction of crop residue ash source and rate had no significant difference (p<0.05) in all the months under investigation, irrespective of cropping seasons. Yield and yield components of cowpea as influenced by ash level varied significantly in number of pods per plant and grain yield in kilogram per hectare (Table 6). Application of 5t/ha of ash resulted to the highest number of pods per plant, 25.39 and 27.28 in 2012 and 2013 cropping seasons respectively followed by 24.78 and 28.65 recorded from treatment of 2.5t/ha ash. Zero application of ash had the least number of pods per plant; 9.19 and 10.93, respectively. The application of 5t/ha of ash had 2-64 % more pod yield than other treatments in 2012 cropping season whereas application of 2.5t/ha produced 5-62% pod yield more than other treatment in 2013 cropping season. The weight of 100 seeds as influenced by ash level showed no significant difference (p<0.05) in both cropping season. The weights range between 15.34 -16.11 g and 15.13-15.80 g in 2012 and 2013 cropping seasons respectively. Cowpea grain yield as influenced by crop residue ash level was significantly different (p<0.05). The application of 5 and 2.5 t/ha of ash produced the highest grain yield (543.26kg/ha and 644.03 kg/ha) in 2012 and 2013 cropping season from treatment that received 5t/ha of ash whereas 537.09 and 628.29 kg/ha, respectively was harvested from the treatment that received 2.5t/ha of ash. Zero application had the least grain yield of 290.01 and 291.69 kg/ha in 2012 and 2013 cropping season, respectively. The application of 5t/ha of ash resulted to 1-47% and 2-55% more grain yield. Comparing 5 and 2.5 t/ha, the result showed that application of 5t/ha of ash produced only 1% and 2% more gain in 2012 and 2013 than grain yield obtained from 2.5t/ha ash plots. Table 7 shows cost of production of cowpea and economic return to management as influences by crop residue ash level and source. The result indicated that treatment of 5t/ha of ash resulted to highest cost of production of N281,000 in each cropping compared to N263800 and 273600 recorded in control and 2.5t/ha treatment respectively. The extra cost recorded in 5t/ha was due to extract cost of procurement of ash, transporting and application. Application of 5t/ha of ash resulted to highest gross revenue, followed by application 2.5t/ha of ash while the least was recorded in control. Comparing the net return to management, the result indicated increase in ash level with increase in net revenue. The cost-benefit ratio presented in table 7 showed highest cost-benefit ratio in 2.5 and 5t/ha ash levels with application of 2.5t/ha having the highest benefit ratio of 2.04 and 2.44 on average in 2012 and 2013 cropping season respectively compared to 2.00 and 2.44 respectively recorded in 5t/ha of ash. The least cost benefit ratio, 0.71 and 0.66 in 2012 and 2013 was recorded in control treatment. The result revealed that for every N1 spent in 2.5t/ha treatment the farmer is expected to have a gain of 2.04 in 2012 or 2.44 in 2013 cropping season while without application, every N1 spent will led to a gain of 0.71 in 2012 cropping season or 0.66 in 2013 cropping.

DISCUSSION The results of some chemical properties of crop residue ash in Table 1 showed that crop residue ash had high organic matter content ranged between 56.14g 1kg in oil palm branch ash to 68.02 g/kg in cocoa pod ash with very strong alkaline pH value of 8.80 (cocoa, pod ash), 8.90


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(plantain bunch/peel ash) and 9.10 (oil palm bunch ash). The high alkaline value recorded in all the ashes of crop residue indicated that crop residue ash could have potential attribute of increase the soil pH. The pH value recorded at harvest indicated increase in soil pH, 7.47 and 7.22 in 2012 and 2013 cropping season when 5t/ha of ash was applied compared to 5.40 and 5.27 recorded in control (no soil amendment). This observation revealed that application of ash has great potential of increasing soil pH level of acid soil. This observation is in support of the submission of some researchers that addition of green manure, animal waste and ash to acid soils can reduce aluminum toxicity and increase crop yield (Hue 1992; Adegoke et al 2013; Akata, 2015 and Ikeh et al., 2015). Application of crop residue ash irrespective of source improved soil properties by increasing soil organic matter, total nitrogen, soil pH as well as high growth rate and yield of cowpea. The observation was in line with report of Uwah and Ogbonna (2013), that positive response exhibited by okra to application of organic fertilizer was as a result of the high content of macro and micro nutrients in organic fertilizer which have the capacity to improve the morphological characters and yield of crops. Ojeniyi (2002) reported that the use of non-conventional lime like egg-shell ash palm bunch ash, cocoa husk could serve as liming materials in reducing the acidity of soil and also serve as of nutrient. The result indicated that treatments that received 2.5 and 5t/ha of ashes had the highest number of leaves and branches per plant as well as grain yield compared to control. The high performance of growth and yield recorded could be due to nitrogen content in the ash which serve as starter nitrogen for the growth of the cowpea. Ganda et al (2013) reported that starter nitrogen is of importance to legume before they start fixing nitrogen. Amujoyegbe et al., (2007) reported that organic fertilizer contained and released considerable amount of nutrient especially nitrogen for plant use and it is essential for chlorophyll and protoplasm formation. The plots with crop residue ash produced higher number of pods per plant and grain yield compared to control (no ash). This could be accounted for by the amount of nutrients contained and released by the particular ash applied to the plant. This observation corroborated the reports of Vanlauwe (2000) and Asaduzzaman et al. (2010) who concluded that organic waste such as, ash farmyard manure, etc improved fertility and water holding capacity of the soil, stored plant nutrients, acted as buffering agent against undesirable nutrient fluctuations, served as a major contributor of cation exchange capacity in soils as well as stimulated microbial activities by increasing temperature, which invariable improve agro-physical properties of the soils. Results showed no significant difference between the yield obtained from 2.5t/ha and 5t/ha rates. This indicated that 2.5t/ha was optimum for cowpea yield in acidic soil of the southeastern Nigeria. Results of economic return to management revealed that application of 2.5t/ha of crop residue ash resulted to higher economic return in cowpea production than application of 5t/ha. No significant difference recorded among the ash sources could be due to close in chemical concentration among the three crop residue ashes tested.

CONCLUSION The results obtained showed that irrespective of crop residue ash, acidic level of Niger-delta soils could be reduced by application of 2.5t/ha of ash. For high yield and economic returns to management, farmers should apply 2.5t/ha of crop residue ashes. This rate of 2.5 t/ha of ash could serve as an alternative to 0.5 t/ha rate of conventional limes recommended for the region.

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Table 1: Chemical Content of Crop Residue Ashes Parameters

Cocoa pod Ash Plantain Bunch/peel Ash

Oil Palm Bunch Ash

pH (H20) 8.80 8.90 9.10 Organic carbon (g/kg) 39.50 38.50 32.60 Organic matter (g/kg) 68.02 66.30 56.14 Total N (g/kg) 7.14 8.33 8.10 Available P (mg/kg) 61.12 68.40 62.45 Exchangeable bases (cmol/kg) K 3.95 4.82 4.75 Ca 2.14 2.20 2.55 Mg 1.89 1.75 1.80 Na 1.10 1.30 1.25 Exchange Acidity 0.04 0.07 0.03 ECEC 3.55 3.60 3.45 Base Saturation 78.00 79.50 78.90

Table 2: Soil Physico-Chemical Properties of the Experimental Site before Planting Values Parameters 2012 2013

Soil pH (H20 4.60 4.50 Organic matter (%) 1.85 1.68 Total nitrogen (%) 0.07 0.07 Available p (mg/kg) 68.75 74.18 Exchangeable bases (cmol/kg-1) K 0.21 0.23 Ca 0.52 0.50 Mg 1.33 1.48 Na 0.16 1012 Exchange Acidity 1.60 1.60 Particle size distribution (g/kg) Sand 87.00 85.00 Silt 5.70 6.20 Clay 7.30 8.00 Textural class Sandy loam Sandy loam

Table 3: Some Soil Chemical Properties at harvest as Influence by Crop Residue Ash and Rate 2012 2013 Ash Rate (t/ha) Ash Source Org.

matter Total N Soil pH Org.

matter Total N Soil pH

Cocoa pod 1.72 0.05 5.40 1.55 0.04 5.20 0 Plantain

bunch/peel 1.70 0.07 5.50 1.65 0.04 5.30

Oil palm bunch 1.71 0.07 5.30 1.61 0.05 5.30 Mean 1.71 0.06 5.40 1.60 0.04 5.27 Cocoa pod 2.20 0.15 6.70 2.11 0.13 6.50 2.5 Plantain bunch 2.30 0.13 6.80 2.20 0.15 6.70 Oil palm bunch 2.25 0.14 6.80 2.30 0.15 6.60 Mean 2.25 0.14 6.77 2.20 0.14 6.60 Cocoa pod 2.80 0.16 7.50 2.50 0.17 7.10 5.0 Plantain bunch 2.75 0.16 7.40 2.55 0.16 7.30 Oil palm bunch 2.82 0.15 7.50 2.60 0.16 7.25 Mean 2.79 0.16 7.47 2.55 0.16 7.22 LSD (p<0.05) Rate (R) 1.06 0.77 0.50 0.95 0.45 0.28 Source (S) ns ns Ns ns Ns ns RxS ns ns Ns ns Ns ns

*ns = not significant


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Table 4: Cowpea Emergence Percentage and Number of Leaves per vine (cm) as Influence by Application of Crop Residue Ash Rates

2012 Months After Planting


Ash Rate (t/ha)

Ash Source Emergence (%)

1 2 3 Emergence (%)

1 2 3

Cocoa pod 100 6.68 16.70 22.42 100.12 5.74 13.38 20.66 0 Plantain

bunch/peel 95 6.70 15.22 21.99 99.80 6.15 15.14 21.36

Oil palm bunch

98 6.48 15.91 20.40 100.00 5.88 16.20 23.40

Mean 9767 6.62 15.94 21.60 99.97 5.92 14.91 21.81 Cocoa pod 98 10.18 21.30 34.28 97.50 8.75 21.12 35.40 2.5 Plantain

bunch 99 10.25 21.68 36.41 98.00 9.84 20.60 35.16

Oil palm bunch

100 9.96 22.40 34.30 100.00 9.81 20.74 34.12

Mean 99.00 10.13 21.79 34.98 98.50 9.47 20.82 34.89 Cocoa pod 100 10.24 21.68 34.60 99.50 9.70 22.40 35.70 5.0 Plantain

bunch 98 10.31 22.13 38.14 100.00 9.80 21.40 39.95

Oil palm bunch

100 10.25 22.62 36.20 99.50 9.72 22.42 37.40

Mean 99.33 10.27 22.14 36.31 99.67 9.73 22.07 37.68 LSD (p<0.05) Rate (R) Source (S) R x S

ns ns 1.68 2.15 ns ns 2.95 3.02 ns ns ns Ns ns ns Ns ns ns ns ns Ns ns ns Ns ns

ns = not significant

Table 5: Number of Cowpea Branches Per Plant as influenced by Application Crop Residue Ash Rates

Ash Rate (t/ha)

Ash Source 2012 Months After Planting


1 2 3 1 2 3 Cocoa pod 2.45 6.58 8.30 2.71 7.05 9.20 0 Plantain bunch/peel 2.75 6.75 8.46 2.80 7.12 7.99 Oil palm bunch 2.34 6.73 8.55 2.69 7.30 8.65 Mean 1.99 6.69 8.44 2.73 7.16 8.61 Cocoa pod 3.95 10.24 12.50 4.12 11.25 11.95 2.5 Plantain bunch 4.30 10.33 12.10 5.16 11.41 12.64 Oil palm bunch 4.11 11.48 12.70 4.97 11.75 12.33 Mean 4.12 10.68 12.43 4.75 11.47 12.31 Cocoa pod 4.05 11.98 12.77 4.25 11.38 12.90 5.0 Plantain bunch 4.36 12.01 12.86 6.55 12.40 12.89 Oil palm bunch 4.19 11.54 12.88 4.39 12.35 12.90 Mean 4.20 11.85 12.84 5.06 12.64 12.99 LSD (p<0.05) Rate (R) Source (S) R x S

1.12 2.17 1.33 0.98 2.07 1.85 ns ns Ns Ns ns Ns ns ns Ns Ns ns Ns



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Table 6: Yield and Yield Components of Cowpea as influences by Crop Residue Ash

Ash Rate (t/ha)

Ash Source 2012 2013 Number of pods/plant

Weight of 100

seeds (g)

Grain Yield

(kg/ha)

Number of pods/plant

Weight of 100 seeds

(g)

Grain Yield

(kg/ha) Cocoa pod 9.02 15.35 285.30 11.25 15.11 276.55 0 Plantain bunch/peel 9.31 15.38 291.99 10.20 15.13 297.09 Oil palm bunch 9.25 15.30 292.75 11.35 15.14 301.44 Mean 9.19 15.34 290.01 10.93 15.13 291.69 Cocoa pod 24.30 16.10 528.36 28.11 15.79 613.11 2.5 Plantain bunch 25.14 16.12 549.40 28.08 15.75 622.50 Oil palm bunch 24.90 16.11 533.51 29.77 15.80 649.25 Mean 24.78 16.11 537.09 28.65 15.78 628.29 Cocoa pod 23.75 16.11 537.43 26.30 15.80 633.40 5.0 Plantain bunch 27.40 16.10 551.01 28.15 15.80 640.17 Oil palm bunch 25.01 16.11 541.34 27.39 15.81 658.51 Mean 25.39 16.10 543.26 27.28 15.80 644.03 LSD (p<0.05) Rate (R) Source (S) R x S

2.55 ns 18.75 3.06 ns 13.68 ns ns Ns ns ns ns ns ns Ns ns ns ns



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Table 7: Cost of Cowpea Production and Economic Returns to Management as influenced by Application of Residue Ash level and source

2012 2013 0 2.5 5 0 2.5 5 Cos t of production C P O C P O C P O C P O C P O C p O Preparation 145,00 145,00 145,00 145,00 145,00 145,00 145,00 145,00 145,00 145,00 145,00 145,00 145,00 145,00 145,00 145,00 145,00 145,00 Weeding 73,000 73,000 73,000 73,000 73,000 73,000 73,000 73,000 73,000 73,000 73,000 73,000 73,000 73,000 73,000 73,000 73,000 73,000 Soil Analysis 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 15,000 Fertilizer (Ash) - - - 1500 1500 1500 3000 3000 3000 - - - 1500 1500 1500 3000 3000 3000 Ash Application - - - 5000 5000 5000 8000 8000 8000 - - - 5000 5000 5000 8000 8000 8000 Harvesting 12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,000 Transportation 1800 1800 1800 5100 5100 5100 8000 8000 8000 1800 1800 1800 51000 51000 51000 8000 8000 8000 Pesticides/Application 6000 6000 6000 6000 6000 6000 6000 6000 6000 6000 6000 6000 6000 6000 6000 6000 6000 6000 Misillenous 11,000 11,000 11,000 11,000 11,000 11,000 11,000 11,000 11,000 11,000 11,000 11,000 11,000 11,000 11,000 11,000 11,000 11,000 Total cost of production 263,80

0 263,800 263,800 273,600 273,60

0 273,600 281000 281000 281000 263800 263800 263800 273600 273600 273600 281000 281000 281000

Cowpea yield (kg/ha) 285.30 291.99 292.75 528.36 549.40 533.51 537.43 551.01 541.34 276.55 297.09 301.44 613.11 622.50 649.25 633.40 640.17 658.51 Gross Revenue 442.21

5 452584.5

453762.5

818958 851570 826940.5 8330165 8540655 839077 414990 445635 452160 919665 933750 973875 950100 960255 987765

Net Return (N) 178415 188784.5

189962.5

545358 577970 553340.5 552016.5

573065.5 558077 151190 181835 188360 646065 660150 700275 669100 679255 706765

Cost Benefit Ratio 0.68 0.72 0.72 1.99 2.11 2.02 1.97 2.04 1.99 0.57 0.69 0.72 2.36 2.41 2.56 2.38 2.42 2.52 Average cost Benefit Ratio in level

0.71 2.04 2.00 0.66 2.44 2.44

Miscellaneous = cost of planting material (seeds), planting and rodent control Yield X unit price of N1550 per kg of grain in 2012 and 1500 per kg of grain in 2013 based on prevailing market price than C = Coco pod Ash; P = Plantain bunch/peel Ash; 0 = Oil palm Ash


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AN ASSESSMENT OF THE PROFITABILITY OF CASSAVA PROCE SSING IN EDO STATE, NIGERIA

1Izekor. O.B. and 2Ilavbarhe, K.O. Department of Agricultural Economics and Extension Services, Faculty of Agriculture,

University of Benin, Benin City, Nigeria. [email protected] [email protected]

ABSTRACT The study was conducted to assess the profitability of cassava processing in Edo State, Nigeria. It specifically estimated the costs and returns of cassava processing, determined its viability and identified constraints facing cassava processors in the study area. Data for the study were collected using a well-structured questionnaire administered to 100 cassava processors randomly selected from the study area. Data analysis was done using descriptive statistics, gross margin profitability analysis and benefit-cost ratio. The result of the study showed that cassava processing in the study area was dominated by females (67%) with a mean age of 47 years, who were married (64%) and had mean family size of 6 persons per household. The respondents had one form of education or the other with majority (44%) having primary school education and had a mean cassava processing experience of 13 years. The identified products from cassava processing in the study area were garri, cassava flour (lafun), edible starch and fufu with majority (39%) of the respondents involved in the processing of garri. The results further showed that the processing of cassava into the identified products in the study area was profitable with net profits of N25,749.81, N23,632.56, N24,593.20 and N26,66.37 for garri, fufu, edible starch and cassava flour (lafun) respectively and viable with benefit cost ratios of 1.56, 1.47, 1.45 and 1.47 respectively. The major constraints facing the processors were inadequate capital, high cost of transportation, high cost of inputs and high cost of processing equipment. Investors are advised to invest in the processing of cassava since the business is profitable and viable. Cassava farmers should therefore be educated on the potentials that exist in cassava processing and how they can seize the opportunities to increase their income. Keywords: Cassava, processing, profitability, Edo State, Nigeria

INTRODUCTION Agriculture is a major contributor to Nigeria's Gross Domestic Product, with cassava playing a dominant role. Cassava is one of the most affordable staples and is predominantly one of the key income generating crop in Nigeria. Cassava is a crop that has the potential of increasing farm incomes, reduce rural and urban poverty and help close the food gap (Nweke et al., 2002). Nigeria is the world largest producer of cassava with about 44 million metric tonnes per annum ahead of other producers like Brazil and Thailand (Eke-Okoro and Njoku, 2012).

As a crop whose value added products have a wide array of uses, cassava is the most important food crop in Nigeria by production quantity next to yam, which is the most important food crop by value (FAO, 2013). However, consumption of cassava products is not possible without processing. More so, cassava being an agricultural product is bulky and perishable. Fresh cassava roots cannot be stored for long because they rot within 3 – 4 days of harvest. It therefore, exerts various pressures on handling, packaging, transportation and sales with adverse antecedent effect on market prices (Ugwumba and Okoh, 2010). Cassava also contains two (2) cyanogenic glycoside namely linamarin and lotaustralin, which are highly toxic to human and animals. Therefore, the roots need to have the cyanogenic glycosides reduced to a level which is tolerable and safe for human and animal consumption

Izekor. O. B. and Ilavbarhe, K. O. (2017). An Assessment of the Profitability of Cassava Processing in Edo State, Nigeria. Journal of Environment and Sustainable Development, 3(1): 166 – 173.


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(Yakasai, 2010). Processing procedures are aimed at reducing cyanide, improving storability, providing convenience and palatability. As a traditional crop, expanding cassava processing enterprises can bring direct economic benefits to the farmer, and increase investment in the downstream sector of the cassava commodity system. To serve its function as a provider of household food, income and employment, cassava is processed into various wet and dry product forms, which are eaten by both the rural and urban populace (Ezedinma et al., 2007).

At present, a wide range of traditional cassava products such as garri, fufu, edible starch, lafun, abacha, etc. are produced for human consumption (Kormawa and Akoroda, 2003). Garri is the most consumed and traded of all food products made from cassava roots. It is a creamy-white, partially gelatinized, free flowing granular flour with a slightly fermented flavour and sour taste. It accounts for 70% of the entire cassava production in Nigeria (IITA, 1990). It is consumed as processed or reconstituted with hot water to give a dough-like paste called "Eba", which is consumed with sauce. Garri is consumed with animal or plant protein accompaniments (Tubman 1989) or protein enriched with soybeans to boost its protein content (Sanni and Sobamiwa 1993). Fufu is the second major product consumed by households and institutions, ranked next to garri in importance. Prepared cassava fufu is a fermented product of cassava. Until recently, it was not sold in ready-to-eat form, this change as a result of demand for convenient foods (Ezedinma et al., 2007). Fermented paste is also a product of cassava tuber. This product is an intermediate step in the processing of garri and fufu. Fermented cassava flour (locally called lafun or elubo) is another unique product. With respect to food, it is used to prepare amala, a very popular food recipe in the south-west part of Nigeria. Cassava chips are processed in several ways and come in several forms. They may be fermented or unfermented peeled roots that are either sun dried or dried over the fire place. They are intermediate products that are converted into flour by milling (Ezedinma et al., 2007).

A common problem identified in cassava processing and marketing is that of price fluctuation (Muhammad–Lawal et al., 2013). Processors are constantly faced with problems of seasonal variation in product prices (Olagunju et al., 2012). It has become imperative to focus on the processing and utilization of cassava in order to sustain and improve the present production level and also guarantee higher prices for farmers. Against this background, this study sought to provide answers to the following research questions: What are the various products derived from cassava processing? Does cassava processing have potential for economic viability? Are there problems in the processing of cassava? It is in view of this that this study was designed. It seeks to achieve the following specific objectives: to examine the socio-economic characteristics of cassava processors, identify the various products from cassava processing in the study area, estimate the profitability and viability of cassava processing, and identify the constraints in cassava processing in the study area.

MATERIALS AND METHODS Study area: The study was conducted in Edo State, Nigeria. The State lies within the geographical co-ordinates of Longitude 05º 04' and 06o 43'E and Latitude 05º 44' and 07º34'Nh. It has 18 Local Government Areas (LGAs) with the capital in Benin City. It has an estimated population of 3,218,332 (Census, 2006). The State has a tropical climate characterized by two distinct seasons: the wet and dry seasons with average temperatures of about 25oC (77oF) in the wet season and about 28oC (82oF) in the dry season which is quite conducive for cassava production. The State is mainly agrarian, producing crops such as yam, cassava, cocoyam, rice, maize, plantain, oil palm, cocoa, coffee and rubber. A large proportion of the population is engaged in farming, fishing, carving, carpentry and agricultural marketing.


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Data collection methods: The State is divided into three agro-ecological zones according to Edo Agricultural Development Programme (EADP) delineation, namely; Edo North (comprising Akoko Edo, Etsako Central, Etsako East, Etsako West, Owan East and Owan West LGAs), Edo Central (comprising Esan Central, Esan North East, Esan South East, Esan West and Igueben LGAs) and Edo South (Egor, Ikpoba-Okha, Oredo, Orhionmwon, Ovia North East, Ovia South East and Uhunmwonde LGAs). A multi-stage sampling procedure was used in selecting the respondents for the study. The first stage involved the random selection of two out of the three agro-ecological zone of the state. The second stage involved the random selection of two Local Government Areas from each selected zone. In the third stage, simple random sampling was used to select 25 cassava processors from the sampled LGAs making a total sample size of 100 respondents. Copies of well structured questionnaire were administered to the selected respondents.

Data analysis: Data collected were analysed using descriptive statistics, gross margin, profitability, return on investment and benefit cost ratio. The socio-economic characteristics of the processors and the various cassava products processed in the study area were examined using descriptive statistics such as frequency counts, mean values and percentages. The profitability of cassava processing was evaluated using gross margin analysis, net returns and benefit cost ratio.

Gross Margin = Total Revenue – Total Variable Cost………….………………. (1) Total Variable Cost = Total Cost – Total Fixed Cost Net Profit = Gross Margin –Total Fixed Cost (depreciation)…….…………...….. (2)

BenefitCostRatio7BCR9 = Presentvalueoftotalbenefits

Presentvalueoftotalcost……… .………… . . 739

BenefitCostRatio7BCR9 =

∑Bt

71 + r9��K<

∑Ct

71 + r9��K<

(Reddy et al., 2009)

Where Bt is the total benefit in naira in the time period t; Ct is the total cost in naira in the time period t; r = interest rate; n = number of years (Reddy et al 2009). The values for this analysis were however not discounted as cross sectional data were used for the study. Therefore, the benefit cost ratio was calculated using:

BCR = Totalbenefits

Totalcost

Decision Rule: BCR > 1 - The business is viable; BCR = 1 - Break-Even point; BCR < 1 - The business is not viable The constraints in cassava processing were examined using the information obtained from a five point Likert scale. The responses to various constraints were scored in a way that the response indicating the most serious constraint was given the highest score. As a point scale the responses were grouped into five as shown below: Very Serious= 5; Serious= 4; Moderately Serious = 3; Least Serious = 2; Not Serious = 1. A score above the mean is considered very serious while that below the mean is considered less serious.


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RESULTS AND DISCUSSION Socio-Economic Characteristics of Cassava Processors in the Study Area The socio economic characteristics of cassava processors in the study area are presented in Table 1. The result indicates that majority of the respondents (67%) were females. This suggests that cassava processing is female dominated, this is in line with the findings of Muhammad-Lawal et al. (2013), that cassava processing is a female dominant activity. About half of the respondents (58%) were within the age bracket of 41-50 years with a mean age of 47years. This shows that the processing of cassava is carried out by people in their active years and are physically fit to withstand the drudgery and risks involved in cassava processing and are more mentally alert to accept innovation. This result is in line with that of Ojo (2000) and Amao et al. (2007) that cassava processing is carried out by young and active people. Furthermore, the study showed that about 44% of respondents had primary education, 18% had secondary education and only 9% were educated up to tertiary level. This shows that majority of the respondents had one form of education or the other though about 29% of the respondents had no formal education. This finding agrees with the finding of Ahmadu and Erhabor (2012). Education attainment is very important because it broadens knowledge, improves intelligent quotient and enhances the capacity of processors to seek and make use of new improved technologies. Education also enhances the entrepreneurial skills of processors to harness resources.

Most of the respondents (64%) were married while about 9% and 16% were single and widowed respectively. This indicates that married people are more interested in cassava processing a finding similar to those of Ibekwe et al., (2012) that majority(80%) of garri processor in Imo State were married. Majority of the respondents (65%) had household size of 5 – 8 persons per household with a mean household size of 6 persons. Family size has implication for agricultural productivity. The more members a family has the labour hands that would be available for farm work. This suggests that the respondents are likely to enjoy family labour readily. This is in line with the findings of Ironkwe et al., (2009), who reported that most farm enterprise families in Nigeria had large household size and the size of the family had some amount of influence on hired labour employed in processing activity. For processing experience, about 40% of the respondent had 11-15 year experience closely followed by those (33%) with 5 – 10 experience with a mean processing experience of 13 years. This suggests that the respondents were well experience in their line of business.

Table 1: Socio-Economic Characteristics of Cassava Processors in study area Characteristics Frequency Percentage Sex Female 67 67.0 Male 33 33.0 Total 100 100.0 Age(years) <30 2 2.0 31-40 15 15.0 41-50 58 58.0 51-60 21 21.0 61+ 4 4.0 Total 100 100.0 Mean 47 Educational level No formal education 29 29.0 Primary education 44 44.0 Secondary education 18 18.0


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Tertiary education 9 9.0 Total 100 100.0 Marital status Single 9 9.0 Married 64 64.0 Divorced 11 11.0 Widow(er) 16 16.0 Total 100 100.0 Household size 1-4 25 25.0 5-8 65 65.0 9-12 10 10.0 Total 100 100.0 Mean

6

Processing experience(years) <5 7 7.0 5-10 33 33.0 11-15 40 40.0 16-20 16 16.0 >20 4 4.0 Total 100 100.0

Identified Products from Cassava Processing in the Study Area The identified products from cassava processing in the study area are presented in Table 2 based on the distribution of respondents involved in the processing of the products. The result showed that main products from cassava processing were garri, cassava flour (lafun), edible starch and fufu. About 39% of the respondents were involved in the processing of only garri, 23% were involved in processing of only fufu while 13% and 9% produced only edible starch and cassava flour respectively. About 11% produced both Garri and fufu while 5% produced garri, fufu and starch. This shows that the major product cassava is processed into in the study area was garri. This may be as a result of high demand for garri in the study area being a major staple food. This finding is in line with those of Muhammad-Lawal et al. (2013) that identified four products (garri, cassava flour, starch and fufu) from cassava processing in Kwara State, with garri being the most predominant product.

Table2: Identified Products from Cassava Processing in the Study Area Products Frequency Percentages Garri 39 39.0 Fufu 23 23.0 Starch 9 9.0 Flour 13 13.0 Garri, Fufu 11 11.0 Garri, Fufu, Starch 5 5.0 Total 100 100.0

Costs and Returns in Cassava Processing The results of the costs and return analysis are presented in Table 3. The result showed that cost of raw cassava tuber accounted for the highest percentage of the total cost of processing, representing about 48.81%, 46.67%, 57.62% and 53.59% of the total cost of processing


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garri, fufu, edible starch and cassava flour (lafun) respectively. For garri processing an average of N45,650.19 was incurred as total cost and N71,400.00 was earned as total revenue giving a gross margin and net income of N42,658.90 and N25,749.81 respectively while for Fufu processing, a gross margin of N42,872.56 and net income of N23,632.56 was obtained from a total cost and revenue of N50,616.40 and N74,248.86 respectively. A total cost of N58,563.95 and N60,434.63 was incurred for processing of edible starch and cassava flour while the total returns were N84,914.29 and N89,100.00 respectively yielding gross margins of N40,414.29 and N43,588.45 and net profits of N24,593.20 and N26,66.37 respectively for edible starch and cassava flour processing. This shows that the processing of cassava into the identified products are profitable ventures in the study area. Furthermore, the result showed that they were not only profitable but also viable as their benefit cost ratios of 1.56, 1.47, 1.45 and 1.47 for garri, fufu, edible starch and cassava flour respectively were greater than one. This result is in line with the findings of Ani et al., (2013) that concluded that cassava processing was profitable in South Eastern Nigeria and Muhammed et al., (2013) that also ascertained that cassava processing was profitable in Kwara State, Nigeria.

Table 3: Profitability Analysis of Cassava Processing per 1 Tonne of Raw Cassava Tuber Processed Products

Garri Fufu Edible Starch Flour Variable Cost Items Mean %T

C Mean %T

C Mean %T

C Mean %TC

Tubers 22283.64 49 23616.00 47 33742.86 58 32384.62 54 Labour 1695.55 4 692.00 1 4628.57 8 7576.9213 Palm Oil 623.64 1 - - - - - - Transport 1120.36 3 1592.00 3 1657.14 3 1753.85 3 Water 306.55 0.7 454.40 0.9 650.00 1 288.46 0.5 Firewood 2060 5 4408.00 9 - - - - Packaging Materials 652.36 1 614.00 1 2064.29 4 1984.62 3 TVC 28741.10 63 31376.40 62 42742.86 73 43988.49 73 TFC 16909.09 - 19240.00 - 15821.09 - 16923.08 -

TC 45650.19 - 50616.40 - 58563.95 - 60434.63 - Revenue Items Revenue 71400.00 74248.96 84914.29 89100.00 Gross Margin 42658.90 42872.56 40414.29 43588.45 Net Profit 25749.81 23632.56 24593.20 26665.37 Benefit/Cost Ratio 1.56 1.47 1.45 1.47

Constraints faced by Cassava Processors in the Study Area The various constraints faced by the respondents are presented in Table 4. The result indicated that inadequate capital (mean = 4.49), high cost of transportation (mean = 4.35), high cost of inputs (mean = 4.30), High cost of processing equipment (mean = 3.36) were the major constraints faced by the processors in the study area while high cost of cassava tuber (mean = 2.33) and high taxes (mean = 2.12) were constraints in cassava processing that are not serious in the study area.


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Table 4: Constraints faced by Cassava processors

Constraints Mean score Standard deviation Inadequate capital 4.49* 0.070 High cost of transportation 4.35* 0.059 High cost of inputs 4.30* 2.61 High cost of processing equipment 3.36* 0.158 High cost of cassava tuber 2.33 0.168 High taxes 2.12 0.134

*mean ≥ 3.00 indicate serious constraints


The study found that cassava processing was a profitable and viable venture with favorable returns on investment. It is therefore recommended that cassava processors are advised to form themselves into cooperative societies to pool resources to solve the problem of inadequate capital, high cost of processing equipment among other problems. Farmers and other stakeholders are advised to invest in the processing of cassava since the business is profitable and viable. Cassava farmers should therefore be educated on the potentials that exist in cassava processing and how they can seize the opportunities to increase their income. Furthermore, there should be provision of good roads in order to reduce the cost of transportation of cassava tubers as high cost of transportation was identified to be a serious constraint of the processors.

REFERENCES

Amao, J.O., Adesiyan, O.I. and Salako, B.A. (2007). Economic Analysis of Cassava Processing into Gari in Ogo OLuwa Local Government Area of Oyo State, Nigeria. Pakistan Journal of Social Sciences, 4(2): 266-270.

Ani, S.O., Agbugba I.K. and Baiyegunhi, J.S. (2013). Processing and Marketing of selected Cassava Products in South East, Nigeria. Journal of Economics, 4(2): 105–111.

Eke-Okoro, O.N. and Njoku, D. N. 2012. A review of cassava development in Nigeria from 1940-2010. ARPNJournal of Agricultural and Biological Sciences 7(1): 59-65.

Ezedinma, C., Ojiako, I.A. Okechukwu, R.U., Lemchi, J.R., Umar, A.M., Sanni, L.O., Akoroda, M.O., Ogbe, F., Okoro, E., Tarawali, G. and Dixon. A. (2007). “The Cassava Food Commodity Market and Trade Network in Nigeria”. IITA, Ibadan, 296p.

Food and Agriculture Organisation (FAO) (2013). Analysis of Incentive and Disincentive for Cassava in Nigeria, Technical Note Series, Monitoring African Food and Agricultural Policy (MAFAP), FAO, Rome.

Ibekwe, U.C, Chikezie, C., Obasi, P.C., Eze C.C. and Henri-Ukoha, A. (2012). Profitability of Garri Processing in Owerri North Local Government Area of Imo State. ARPN Journal of Science and Technology, 2(4): 340 -343.

Ironkwe, A.G., Ekwe, K.C., Okoye, B.C. and Chukwu, I.I. (2009). Socio-Economic Determinants of Cassava Producers among Women in Ebonyi State, Nigeria. Journal of Rural Sociology, 9(1): 65-68.

Kormawa, P. and Akoroda, M.O. (2003). Cassava Supply Chain Arrangement for Industrial Utilization in Nigeria. Ibadan, Nigeria.


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Muhammad–Lawal, O.A., Omotesho, O.A. and Oyedemi F.A. (2013). An assessment of the

Economics of Cassava Processing in Kwara State, Nigeria. Paper Presented at the African Association of Agricultural Economics, September 22-25, Hammanet, Tunisia.

Nweke, F. I., Spencer D.Sc. and lynam J. k., (2002). The cassava transformation: Africa’s best kept secret. Michigan State University Press, East Lansing. Michigan, USA, 231p.

Olagunju, F.I., Babatunde, R.O. and Salimonu, K.K. (2012). Market Structure, Conduct and Performence of Garri Processing Industry in South Western, Nigeria, European Journal of Business and Management, 4(2): 99 -112.

Oyewole, O.B and Philip, B. (2006). Agro-food chain and sustainable livelihood: a case study of cassava marketing in Nigeria. Agro–food Chains and Networks for development. Reuben, B. and Slingerland (Eds).Springer, Netherlands. 107-115

Phillip, T.P., Taylor, D. S., Sanni, L. and Akoroda, M.O. 2004. A cassava industrial revolution in Nigeria: the potential for a new industrial crop. International Fund for Agriculture Developments and Food and Agriculture Organization, Rome. 1-49

Sanni, M.O. and Sobamiwa, A. O. (1993). Processing and characteristics of soybean fortified garri. World Journal of Microbiology and Biotechnology, 10: 268-270.

Tubman, A.F (1989), “Development of Cassava Processing and Preservation Facilities in Liberia”. In Akoroda, M.O. and Arene, O.B., (eds.): Proceedings of the 4th Triennial Symposium of the International Society for Tropical Root Crops (African Branch). Kinshasa, Zaire, 5-8 Dec. pp. 229- 234.

Ugwumba, C.O.A. and Okoh, R.N. (2010). Price Spread and the Determinants of catfish marketing income in Anambra State, Nigeria. Journal Agriculture and. Social Science, 6:73–78.


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THE EFFECT OF ATMOSPHERIC NITROGEN DIOXIDE POLLUTAN T DISTRIBUTION ON HUMAN AND PLANTS IN AKWA IBOM STATE

Eka, B. J. and Dike, M. C.

Department of Forestry and Environmental Management Michael Okpara University of Agriculture Umudike, Abai State, Nigeria

Department of Toxicology and Environmental Management Michael Okpara University of Agriculture Umudike, Abai State, Nigeria

Corresponding e-mail: [email protected]

ABSTRACT The measurement of distribution of Nitrogen dioxide (NO2) and it effects on human and plants made use of imaginary coordinates of longitudes and latitudes and grid Akwa Ibom State into 27 quadrates. About 7 quadrates were selected for study using random sampling later were reduced to 3 quadrates using stratified random sampling, based on the presence of physically visible point source of NO2

emission. An insitu analytical equipment was used to measure the presence of NO2 at the sample point in the sampling station. The measurements were taken in triplicate at recorded time at the upward and downward wind directions, in the sample station. Measurement was taken at interval of 100m up to 300m in each of the wind directions. On a transcent the density and diversity of plant species were studied from a quadrate laid at intervals of 100m along the 500m transcent. The different plant species within the quadrate were identified counted and recorded, and the total number of plant stands were counted and recorded. The environmental impact assessment of the host community the sampling station was carried out using reconnaissance tour, discussion, laboratory analysis and administration of questionnaire. Medical diagnostic and laboratory analysis reports were collected and collated, the NO2 emission and distribution were found to be insignificant both in months and locations. There is also NO2 is mostly emitted at the end of dry season and at the onset of rainy season when temperature is favourable for it synthesis. Children of the age 3-12 years and asthmatic patience are most susceptible to the effect of NO2. The NO2 effect on human when there is production of acid deposit. Its deposition on the soil reduces the soil PH, ornamentals and roof cover. Measures should be taken to reduce the emission of NO2 at source.

Key Words: Atmospheric Nitrogen Dioxide, Plant density, Plant diversity, NO2 distribution, Plant species

INTRODUCTION The non flammable nitrogen oxide is toxic with strong chocking odour with low daily emission (Goddish, 2003) especially in area with gas flaring and heavy industrial activities, when there is prolonged human exposure. The primary direct source of NO2 beside the photoxidation processes are fossil combustion, from stationary and mobile plants such as helicopters, generating sets, also from decomposed mangrove swamps, technological development activities, exploitation of nature given resources (deforestation and bush burning) by product of electrolysis, welding, smelting oven works, transportation and industrial activities, also atmospheric chemical oxidation and turbulent diffusion in the air into troposphere. The suspended particulate matters (spm) provide the surface in the atmosphere which reactions occur. The NO2 is catalysed by spm and distributed by meteorological elements especially windspeed. This is how the air pollutes and become

Eka, B. J. and Dike, M. C. (2017). The Effect of Atmospheric Nitrogen Dioxide Pollutant Distribution on Human and Plants in Akwa Ibom State. Journal of Environment and Sustainable Development, 3(1): 174 – 185.


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hazardous. The micro-effect of air pollutants is acid deposition. In Nigeria, the Federal Ministry of Environment (FMENV) regulates all environmental standards including gas emission which is governed by National Ambient Air Limit (NAAL) law. This law and standards are reviewed from time to time. Effect value is used in the measurement of toxicity of pollutant in which a higher value of an effect factor corresponds to an effect based on NAAL (Bradshaw, (1995). The figure 1a and 1b show the political map of the study nation and the state.C

SOKOTO

KEBBI

ZAMFARA

KATSINA

KANO

JIGAWA

YOBE

NIGER

KADUNA

BAUCHI GOMBE

BORNO

ADAMAWA

PLATEAU

NASSARAWA

TARABA

BENUE

FCTKWARA

KOGI

OYO

OGUN

LAGOS

ONDO

OSUN

EDO

EKITI

DELTA

BAYELSA RIVERS

AKWA

IBOM

CROSS

RIVER

ABIAIMO

ANAMBRA

ENUGU

EBONYI

Figure 1a: Map of Nigeria Showing Akwa Ibom State


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Visible NO2

Control

Sampling Station

Figure 1b: Grid map of Akwa Ibom State showing 27 quadrates and 7 sampling stations.

MATERIAL AND METHODS Diversed materials and methods were used to achieve the aim of the research as listed alongside each of the experiments.

EXPERIMENT 1: Establishing of Sampling Station and Sample Points. The establishing of sampling stations and sample point were done in line with Alloway and Ayres (1997) guidelines Materials: Imaginary coordinates of longitude and latitudes, anemometer, barometer, Gasman (To) Sensory Electrochemical Equispment, prismatic compass, windvane and thermometer.


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Method: Imaginary coordinates of longitudes and latitudes were used to grid Akwa Ibom State into 27 quadrates at a pre-determined interval of 10° and 14° respectively. By the use of random sampling 7 quadrates were selected for study from the initial 27. In the selected 7 quadrates sample stations and sample points were opened inline with Alloway and Ayres (1997) guidelines on the opening of sampling stations and sample points. The measurement of NO2 concentration distribution were done in triplicates at a recorded time, along the upwind (45°) and downward (235°) directions using Gasman (To) Sensory Electrochemical Equipment with a device for insitu analysis. This measurement and readings were taken at 100m interval up to 300m in upwind and up to 300m in downwind directions. Three quadrates were finally selected for the study of the effects of NO2 concentration on human and plant. Stratified random sampling based on the physical presence of visible point source of NO2 emission was used for selecting the three sampling stations. Pressure, humidity, windspeed, temperature were measured insitu, however rainfall data was a secondary data. Up3 100m Up2 100m Up1 100m 100m DN1 100m DN2 100m DN3

UP = Upwind NO2 Point Source

DN = Downwind

Figure 2: Sampling Procedure In sampling Station

EXPERIMENT 2: Assessment of Plant Density, Diversity and Plant Species Abundance. Material: A 500m transcent line, 25x25cm quadrate, recording material and tape. Method: Establish a transcent of 500m from the point source of NO2 pollutant. Lay the quadrate along the transcent at an interval of 100m staring from the point source of NO2 pollutant. The laying of the quadrate is repeated at the three sampling stations. All plant species within the quadrate are identified, counted and recorded. Then, the total plant stand within the quadrate are counted and recorded. From these data the plant species abundance is deduced.

100m Q1 100m Q2 100m Q3 100m Q4 100M Q5

= Point Source of No2

Figure 3: Schematic Diagram of laying of quadrate.

EXPERIMENT 3 : Plant Tissue and Soil Analysis

The principle of plant tissue analysis is that nutrient concentration in plants is related to the amount of nutrient available in the soil (Jones, 1987). This analysis have some limiting factors due to nutrient caliberation and growing conditions, however the analysis still serve to diagnose the uptake of some nutrients particularly the micro-nutrient.

Material: Sample of plant tissue, sample of soil, chemicals.


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Method: An identified plant sample chromolena odortata, the upper third leaf of the plant at the early bloom and it roots served as the assay plant. Soil sample at the root base of assay plant served as the soil sample. The samples collected were at Ibeno, Ikot Abasi, Uyo and at the control at Abak. These samples were analysed in the laboratory for Nitrogen, Potassium, Sodium, Sulphur and PH.

Environmental Impact Assessment (EIA) In order to assess the biophysical impact, Socio-economic impact and health impact the EIA was done. A constructed questionnaire was administered at the three (3) sampling communities with visible point of NO2 emission. Collation of affected environmental indicators was made such as soil analysis, Air purity analysis, vegetation density and diversity and plant species abundance and the collation of the opinion deduced from administered questionnaire. Also, medical diagnosis and medical laboratory analysis of patient’s blood analysis were collected and analysed.


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RESULT PRESENTATION

Table 1: Nitrogen dioxide Distribution In month and Location

TREATMENT JAN FEB MAR APRIL MAY JUNE JULY AUG SEPT OCT NOV DEC TOTAL

BLOCK UYO 0.00 0.01 0.05 0.05 0.02 0.00 0.00 0.00 0.01 0.02 0.01 0.00 IBENO 0.00 0.03 0.07 0.06 0.03 0.00 0.00 0.00 0.04 0.04 0.02 6.01 IKOT ABASI 0.00 0.02 0.06 0.06 0.03 0.00 0.00 0.00 0.04 0.04 0.02 0.01 ETIM EKPO 0.00 0.01 0.02 0.02 0.01 0.00 0.00 0.00 0.02 0.01 0.11 0.00 IBIONO 0.00 0.01 0.02 0.01 0.00 0.00 0.00 0.00 0.01 0.01 0.01 0.00 INI 0.00 0.01 0.02 0.01 0.01 0.00 0.00 0.00 0.01 0.01 0.01 0.00 ABAK 0.00 0.01 0.02 0.01 0.01 0.00 0.00 0.00 0.00 0.01 0.01 0.00 BLOCK TOTAL 0.00 0.10 0.26 0.22 0.11 0.00 0.00 0.00 0.13 0.14 0.09 0.01

The NO2 distribution in months and locations were not significant.

Table 2: Plant Tissue, and Soil Analyses

LOCATION Leaf tissue Root Tissue Soil

ELEMENTS N% P% K% S% N% P% K% S% N% P% K% AL% S% PH% Okay

IBENO 2.50 1.10 2.20 0.81 2.30 1.00 2.71 0.79 1.75 3.80 3.50 30.00 0.18 4.80 High

IKOT ABASI 2.40 1.95 1.78 0.51 2.10 1.90 2.12 0.50 1.87 1.70 3.00 13.0 0.15 4.80 High

UYO 4.00 0.26 1.70 0.26 4.05 0.26 1.72 0.27 2.44 0.30 2.50 2.75 0.25 5.50 Moderator

ABAK (Control) 4.80 0.25 2.01 0.23 4.85 0.25 2.01 0.24 2.71 0.30 2.61 2.75 0.21 6.31 Low

Source: Field


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Plant Density, Diversity and Species abundance

The quadrate was laid along 500m transcent at 100m interval, the result is presented in table 3. The total plant stands progressively. P. T. O.

Table 3: Plant Species Distribution

Location 500m Transcent

Identified Plant Spp No

Total stand Per quadrate

Overall Total Stand Identified Spp of Plant

Ibeno 100 200 400 500

6 10 10 12 12

10 14 18 22 27

91

1 Chromolaera oderatum 2 Sida acuta 3 Andropogon gayanus 4 Euphorbia hyssolifolia 5 Aneileina umbrosum 6 Axonopus Compressus 7 Elusine india 8 Cyperus haspan 9 Tridax procumbense 10 Asphilia africana 11 Commelina nodiflora 12 Starchytarpheta angustifolia 13 Sellaginela myosurus 14 Scleria peerota 15 Physalis angulata 16 Pteriduim acquitium 17 Asystasia gangelica

Ikot Abasi 100 200 300 400 500

13 13 12 14 15

14 33 48 68 100

263 Abak 100

200 300 400 500

12 12 13 14 15

104 98 124 142 150

618 Uyo 100

200 300 400 500

13 14 16 16 17

92 110 120 140 148

510


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ease away from the point source of No2 emission (gas flare stack) at Ibeno and Ikot Abasi. The density of the vegetation at the first 100m from the gas flare stack is very scanty (Figure 6) and the vegetation thickened as the distance increased away from the gas flare stack. From the schematic vegetation diagram at 400m away from the N02 source the vegetation was very thick compared to 300m, 200m and 100m, respectively. The density thickening had corresponding increase in the number of species. At the control a total of 15 plant species were identified and total plant stand of 618 were counted. However it was at Uyo that 17 species of plants were identified and the total stands was 510. These are two areas with no direct No2 emission point. However, it was at Ibeno and Ikot Abasi with visible point source of N02 emission that 12 and 15 species of plant were identified respectively, and their total stand count were 91 and 263 stands respectively.

100m 200m 300m 400m

Gas Flare Stack

Very Sparsely Dense Sparse Less Dense Thick Density Figure 6: Vegetation Destiny Distribution Result of Environmental Impact Assessment The view of the people (respondents) was that the effect of N02 was insignificant on the people and on plants and the entire environment. On the health and micro economy it was equally insignificant. The medical diagnosis and laboratory analysis from the government hospital as shown on tables 4 and 5 were not significant. A total of 2378 were sighted in the diagnostic report only 8 were reported to have environmentally caused sickness. They patience were ……….. Table 4: Patients Blood Sample Analysis

Specimen Gender Age Laboratory Analysis

Doctor’s Diagnosis

Causative Factor

Blood Sample Govt Hospital laboratory -2015

Males 3-12yrs Blood count WBC and RBC-Normal

Irritation Environmental

females 3-12yrs Blood count WBC and RBC-Normal

Conjunctivity Environmental


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Table 5: Number of Diagnosed Patients Year Gender

Male Female

Age Number of cases

Medical Diagnosis

Comment

2007 198 81 3-12 279 NC Environmental Exposure


2009 170 110 3-12 280 ENI Environmental Exposure

2010 220 130 (Asmathic) 350 NC Environmental Exposure

2011 213 126 (Asmathic) 339 NC Environmental Exposure

2012 180 122 3-12 302 ENI Environmental Exposure


2014 140 101 (Asmathic) 3-12

241 ENI Environmental Exposure

NC = Nasal Congestion Govt Hospital Record – 2011 to 2014 ENI = Eye, Nose irritation diagnosed and treated for an environmentally associated sickness (Nasal congestion and irritation of eyes and nose) for a period of eight years. From the laboratory analysis there were no mobilization of White and Red blood corpuscles to the site of sickness as would be the case if it were to be pathologically associated sickness. From the table 6, N02 effects (in synergy with other gases) was quite minor and not significant. There was little or no need for mitigation measures. However, measures to create green space was quite neglected being sure source of sustaining air purity. The youth, adults accepted that the effect of N02 emission was minor. Table 6: Collation of Group Discussion

Source: Study Area field discussion Key: Major – 61 -100% Moderates -40 – 60% Minor – 0 – 39%

Items Impact of Gas flaring Impact on Human and plant Health Mitigation Creation of green space

Youth Adults Experts Remark 26

18 2 0

23

18 1 0

28

18 1 0

Minor Minor Minor Minor


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Table 7: ANOVA Source of Variation DF SS MS Feal Tab Total 70-1=69 0.0340 0.005 - - Treatment 13-1=12 0.0107 0.0008 0.0002 NS 1.96 Block 12-1=91 0.0056 0.0006 0.0002 NS 2.08 Error 48 0.0177 0.6875

Discussion Nitrogen dioxide in the atmosphere increased with increase in human activities. This increase is catalyzed by temperature, rainfall, humidity and wind speed. When the temperature is extremely low or high they are unfavourable for the synthesis of NO2. Following from Table 7 ANOVA, the treatment mean and the block effect were not significant at 0.05, for. The location and monthly distribution were not significant. Much NO2 synthesis concentrates in the late dry season months and on set of wet season months. Peaks of dry season months and wet season months records minimal to marginal NO2

distribution. High temperature reduces NO2 to other forms of nitrogen oxides, couple wit the NO2 highly solubility in water, in atmosphere and in the soil. Also, the extremes of meteorological elements strongly affect NO2 synthesis and distribution in the Figure 5, there is no significant or clear differences in NO2 distribution all the year round.

Locational distribution shows Ibeno as the highest emission of NO2, this is due to high industrial efficient released into the atmospheric NO2 increase with the increase in human activities. Such human activities 48as gas flaring, fuel combustion, emission from Bristow Helicopters, mobile and Stationary machines and NO2 atmospheric oxidation under some photolytic reactivities. The fast cooling action of No stopped further dissociation and caused the production of NO2. This fast cooling is due to Ibeno location being a community on the coastline of Atlantic Ocean. The period between March, April and May are favourable because low temperature, low heat radiation, humidity and low wind speed, favours NO2 synthesis, as recorded in March (Figures 3 and 4). Consequently, the production of NH3 is inversely low. At the control (Abak) an agrarian urban area surrounded by heavy vegetation and traversed by large body of water the NO2 was all times low. Abak is devoid of any industrial activities. The identification of plant species per quadrate, the total plant count (stand by stand) and the relative percentage of all available plant species in the vegetation summed up the species abundance. The plant species counted (Table 3) in each station was Uyo (510), Ibeno (19), Ikot Abasi (263) and Abak (618) which summed up to 1482. The plant species increase led to the total plant stand count increase because of decreasing load of NO2. The density and diversity of the vegetation increased progressively away from the point source of NO2 pollutant. A maximum of 17 plant species were identified after laying the quadrate along a transcent of 500m. Table 3 shows the 17 identified plant species. At the control a maximum of 15 species of plant were identified and the density of plant stand counted was 618 the highest. In Ibeno the abundance was 0.07 Ikot Abasi 0.73, Abak (control) 0.99 and 0.93 in Uyo. Areas with visible NO2 emission. vegetation density increased progressively away from source of pollutant. Location with no visible pollutant source, the density of vegetation is mix with no definite pattern. Comparing the diversity density within location like Ibeno, Euphorbia hyssopifoha and Aneilema umbrosum were the most predominant, but scanty. In Ikot Abasi Sida acuta and Tridax procumbense were predominant but indax had a little edge. In all the locations the general character exhibited by plants was the emergence, disappearance and re-emergence of different plant within the 500m transcent, often die and re-emerge about 100m away from initial point of growth. This is attributed to the weight and mass of spm pollutant that cover the plant stomatal opening which result in death of plants only to re-emergy at places with


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favourable environmental conditions. (Udoessien 1997). Plant with highest density and diversity are found in areas with less air pollutant effects e.g. Abak and in Uyo. The structure of the vegetation in Uyo and Abak are similar due to no threshold pollutant (NO2) status, but in Ibeno and Ikot Abasi the structure is similar because of NO2 emission threshold status effect. The leaf and root tissues shown that nitrogen is higher in leaf tissue than in root tissue. This is attributed to foliar interception of Nitrogen in the air. In Ibeno and Ikot Abasi Nitrogen in the soil is very low. Clay lattice is high causing strong acidity, also phosphorus is high in soil and buffer the uptake of Nitrogen, hence the low nitrogen in soil and plant roots. This is well pronounced with expressible symptoms of purplish colouration and the early maturing chlorosis. The NO2 in energy with SO2 (through the process) result in photoxidation in the cause the production and deposition of the acid in the soil and results in strong pH. This causes bud harding of most shrubs and herbs, dwarfism is confirmed in line with the work of (J plant 2004) in which prolonged exposure to strong acidity exceeding 100 days causes serious deleterious physiological defects on plants. The acidity also impaired free nutrient mobilization causing nitrogen deficiency. Plant species growth, distribution and species abundance are affected. Selective pressure of differential synthesis and concentration of NO2 on vegetation is also observed. This relates to differential susceptibility earlier observed by Smith (1974) in which plant species receive from NO2 emission. Depending on the intensity of pressure it alters the composition and structure of the plant species. This assertion is further confirmed by Materia (1984).The medical diagnostic report and medical laboratory analysis report confirmed a case of not significant impact of NO2 emission (Tables 4 and 5). The patients diagnosed had nasal congestion and eye and nose imitations. The eight years reports show insignificant fraction of the population (2378) suffered. Against (296,328) combined total population of Eket, Esit Eket and Ibono only children of 3-12 years and asmathics were quite valuerable. The sickness were term environmentally caused because unlike pathologically caused irritation the White blood corpuscles (WBC) and Red blood corpuscles (RBC) are often mobilized to the site of sickness. From the biophysical analysis and the entire EIA indicated report, the No2 emission (in location and month), the impact on the health of human and plant at the study communities is not significant as such attracts no mitigation (Table 6). The effects were minor in all indices, however there was the need for creation of green spaces, to ensure continuous air purity. Conclusion Atmosphere is an all embracing sink which NO2 pollutant is equally stored. The presence of NO2 in an ecosystem affects human and plants though selectively, also depending on it concentration and the length of time which plant or human are exposed to it. The least tolerant plant species die, vegetation density and diversity increase from point source of NO2 because of it subtle deleterious effects on human, plants and the environment. The number of plant stand in plant community increased with decreasing NO2 load in the atmosphere, coupled with increase distance away from the NO2 emission point source. Successful survival of some plants are attributed to biomass formation, adaptable biomass formation, adaptable morphological structure, inherent genetic hereditary endowment and less stress impacted by NO2 pollutant.


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Godish, T. (2003). Air Quality 4th Edition. Pub-Lewis New York. pp 86-96. Hage, Smith, A. (1990). Air Pollution and Forest Interaction between Air Contaminant and

Forest Ecosystem 2nd Edition. Springer-Verlag, New York. pp 80-90. Leave Contamination by Atmospheric Pollutants as assessed by elemental analysis of leaf

tissue, leaf surface deposit and soil. A journal of plant physiology (Jplant). ISSN 0176, 2004. pp 101-116.

Liu, D. H. F. and Liptak, B. G. (1999). Air Pollution. Pub-Lewis, New York pp 16, 36-70. Materia, S. (1984). Sampling Plant Tissue Analysis Theory, Experiments and Application.

New Mexico. pp 7-12. Mcload, A. R. F. (1985). Open Air Fumigation of Field Crop: Criteria and Design for a

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Smith, W. H. S. (1974). Air Pollution Effects on the Structure and Function on the Temperate Forest System. Lewis Pub. Washington DC. pp 7-10.

Udo, E. J. (2004). Soil Potential of the Coastal Zone of Akwa Ibom State. United States Environmental Protection Agency (EPA) Citizens Bulletin, September (1990)

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FORESTRY, ENVIRONMENT AND SUSTAINABLE DEVELOPMENT · Ibom State, Nigeria. Nneke, N. E. 97-101...

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