Regionalising Loan Repayment Capacity of Small Holder Cooperative Farmers in Nigeria: Exploring South-South Nigeria

This paper examined the repayment capacity of small holder cooperative farmers in South-south region of Nigeria. A composed sample of ninety-six respondents randomly selected from sixteen cooperatives from eight local governments in Bayelsa and Delta states made up the sample. Descriptive statistics and Multiple regression analysis were used to achieve the study objectives. The result shows that age, education level, loan size, repayment period, net farm income, loan supervision, engagement in other jobs as well as farm size has positive influence on loan repayment capacity. Also, gender, marital status, household size and the amount expended on hiring equipment have negative influence on loan repayment capacity. The author recommends that there is the need to improve access to farm implement and fertilizer as this will help to increase farm yield and consequently the net farm income of the farmers which the study has shown will improve the repayment capacity of the farmers. Also, pertinent that effective loan supervision mechanisms be put in place to ensure loan repayment compliance. More loans should be advanced to females. Government should subsidize farm equipment or at best grant waiver to farmers who want to import such equipment. In addition, government should do well to offer preferential interest rate to small holder farmers. Key words: Loan Repayment Capacity, Small Holder  Cooperative Farmer

Analysis of Beef Marketing in Oshimili South Local Government Area, Delta State, Nigeria

This study examined the marketing of beef in Oshimili South Local Government Area of Delta State. The specific objectives of this study were to: describe the socio economic characteristics of beef marketers, determine the profitability of beef marketing in the study area, examine the factors affecting marketing margin of beef. Twenty (20) sellers were randomly selected from each of the five markets randomly composed in Oshimili South local government area of Delta State. The markets selected were Ogbeogonogo, Cable point, Okwe. Abraka, and Oko. Well-structured and validated questionnaires were administrated to get information from beef sellers. Descriptive statistics was used to analyze the social economic characteristics of beef marketers in the various markets; the profit function (estimated by gross margin since fixed cost was negligible)  was used to determine the profitability of beef market and regression analysis was used to determine the factors affecting marketing margin of beef. The results showed that the marking of beef in the area was profitable. The result further showed that cost of purchase, cost of transportation, packaging and middlemen profit had significant effects on marketing margin of beef in the study area. From the findings, it is recommended among others, that government should site more abattoirs close to major beef markets to reduce transportation cost and consumer price. Keywords: Beef marketing, Profitability, Profit function, marketing margin, Oshimili South, 

Binary probit estimation of factors affecting pesticide adoption for the control of yam tuber beetles in delta state, Nigeria

Yam is a major staple food crop with significant impact on the food security, income generation and employment creation for the various participants in the yam value-chain in Nigeria. However, pest infestation by yam beetles poses serious production constraint to farmers resulting in over 50% of yield losses. Many farmers have adopted the use of pesticides such as chlorpyriphos. pirimiphos-methyl and deltamethrin to control yam beetles and boost output. Therefore, this study was conducted to examine factors that affect pesticide adoption for control of yam beetles in Oshimili Area of Delta State, Nigeria. Data were obtained from a cross-section of 159 yam farmers including 79 adopters and 80 non-adopters of pesticides, drawn from 6 communities with the aid of questionnaire. t-test and binary probit were employed to analyse the data. The choice of the probit model is due to the qualitative nature of the dependent variable (pesticide adoption). Results of t-test revealed that significant (p < 0.01) differences existed in age, years of formal education, number of adults per household, farm income and farm size between adopters and non-adopters. The probit model had a good fit with significant LR ratio, 106.67 (p < 0.001); a McFadden R2 of 0.48 with 84.9% of cases correctly predicted. The results also showed that age, years of education, adults per household, farming experience, farm income, access to credit, extension contact as well as training on pesticide application all had significant influence on adoption decision. While the impact of age on the probability of technology adoption was negative, all other variables exerted positive effects. The authors recommended that improved access to farm credit, efficient and effective extension service delivery system and on-farm training on pesticide handling and application be intensified to reduce beetles attack, boost yam yield and improve food security of farming households