2022•International Journal of Agriculture and Environmental ResearchOpen access

ANALYSIS OF FARMERS’ BUSINESS SCHOOL PARTICIPATION ON COCOA PRODUCTIVITY IN ONDO STATE, NIGERIA

R. S. Owoeye, A. B. Sekumade, Didunyemi Adekunle John, M. J. Falade

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Abstract

Various models and approaches are being implemented to provide technical assistance and support to improve cocoa productivity in Ondo State of Nigeria. This study compared Farmers’ Business School (FBS) participation and non- participation on cocoa farmer’s productivity. The study specifically described the socio-economic characteristics of the farmers, examined factors determining participation in (FBS) among cocoa farmers, estimated cost and returns of the two categories and determined the technical efficiency of cocoa production for both participants and non-participants. Multi-stage sampling technique was used to obtain data from 90 cocoa farmers that were selected from three Local Government Areas in Ondo State based on their participation and non-participation in (FBS). Descriptive Analysis, Gross Margin, Logit model and stochastic frontier production function were used to analyse the data. Result from descriptive analysis revealed that the mean age of the respondent was 54.2 years. Majority of the respondent (48.9%) attained secondary education and above. It also showed that 38.9% had above 6 members to make up the household in the study area. Findings also revealed that 33.3% had an average annual income above ₦1.000,000. The result further showed that majority of the respondent produced on a medium scale with average cocoa farm size of 3.5 hectares and the farmers were well experienced. The result on gross margin analysis shows that the total revenue, gross margin and profit for participants in (FBS) were ₦678,601.3, ₦402447.2 and ₦324458.3 respectively. On the other hand, the total revenue, gross margin and profit for the non- participants of (FBS) were ₦345,217.8, ₦231,084.5 and ₦193,795.6 respectively. This figure implies that participants in (FBS) were far better than non- participants in terms of gross margin, total revenue and profit. Result of the logit regression showed that gender, age, educational level, and membership of co operative society were found to be statistically significant. This implies that these variables greatly influenced the decision of the cocoa farmers in the study area to either participate in (FBS) or not. Result from the stochastic frontier production function revealed that family labour, hired labour, pesticides, area of land and amount of fertilizer were statistically significant meaning those variables determined the technical efficiency of the cocoa farmers in the study area while age, frequency of extension contact, household size and member of cooperative greatly influenced the technical inefficiency in the study area.

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Various models and approaches are being implemented to provide technical assistance and support to improve cocoa productivity in Ondo State of Nigeria. This study compared Farmers’ Business School (FBS) participation and non- participation on cocoa farmer’s productivity. The study specifically described the socio-economic characteristics of the farmers, examined factors determining participation in (FBS) among cocoa farmers, estimated cost and returns of the two categories and determined the technical efficiency of cocoa production for both participants and non-participants. Multi-stage sampling technique was used to obtain data from 90 cocoa farmers that were selected from three Local Government Areas in Ondo State based on their participation and non-participation in (FBS). Descriptive Analysis, Gross Margin, Logit model and stochastic frontier production function were used to analyse the data. Result from descriptive analysis revealed that the mean age of the respondent was 54.2 years. Majority of the respondent (48.9%) attained secondary education and above. It also showed that 38.9% had above 6 members to make up the household in the study area. Findings also revealed that 33.3% had an average annual income above ₦1.000,000. The result further showed that majority of the respondent produced on a medium scale with average cocoa farm size of 3.5 hectares and the farmers were well experienced. The result on gross margin analysis shows that the total revenue, gross margin and profit for participants in (FBS) were ₦678,601.3, ₦402447.2 and ₦324458.3 respectively. On the other hand, the total revenue, gross margin and profit for the non- participants of (FBS) were ₦345,217.8, ₦231,084.5 and ₦193,795.6 respectively. This figure implies that participants in (FBS) were far better than non- participants in terms of gross margin, total revenue and profit. Result of the logit regression showed that gender, age, educational level, and membership of co operative society were found to be statistically significant. This implies that these variables greatly influenced the decision of the cocoa farmers in the study area to either participate in (FBS) or not. Result from the stochastic frontier production function revealed that family labour, hired labour, pesticides, area of land and amount of fertilizer were statistically significant meaning those variables determined the technical efficiency of the cocoa farmers in the study area while age, frequency of extension contact, household size and member of cooperative greatly influenced the technical inefficiency in the study area.

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Available abstract

Various models and approaches are being implemented to provide technical assistance and support to improve cocoa productivity in Ondo State of Nigeria. This study compared Farmers’ Business School (FBS) participation and non- participation on cocoa farmer’s productivity. The study specifically described the socio-economic characteristics of the farmers, examined factors determining participation in (FBS) among cocoa farmers, estimated cost and returns of the two categories and determined the technical efficiency of cocoa production for both participants and non-participants. Multi-stage sampling technique was used to obtain data from 90 cocoa farmers that were selected from three Local Government Areas in Ondo State based on their participation and non-participation in (FBS). Descriptive Analysis, Gross Margin, Logit model and stochastic frontier production function were used to analyse the data. Result from descriptive analysis revealed that the mean age of the respondent was 54.2 years. Majority of the respondent (48.9%) attained secondary education and above. It also showed that 38.9% had above 6 members to make up the household in the study area. Findings also revealed that 33.3% had an average annual income above ₦1.000,000. The result further showed that majority of the respondent produced on a medium scale with average cocoa farm size of 3.5 hectares and the farmers were well experienced. The result on gross margin analysis shows that the total revenue, gross margin and profit for participants in (FBS) were ₦678,601.3, ₦402447.2 and ₦324458.3 respectively. On the other hand, the total revenue, gross margin and profit for the non- participants of (FBS) were ₦345,217.8, ₦231,084.5 and ₦193,795.6 respectively. This figure implies that participants in (FBS) were far better than non- participants in terms of gross margin, total revenue and profit. Result of the logit regression showed that gender, age, educational level, and membership of co operative society were found to be statistically significant. This implies that these variables greatly influenced the decision of the cocoa farmers in the study area to either participate in (FBS) or not. Result from the stochastic frontier production function revealed that family labour, hired labour, pesticides, area of land and amount of fertilizer were statistically significant meaning those variables determined the technical efficiency of the cocoa farmers in the study area while age, frequency of extension contact, household size and member of cooperative greatly influenced the technical inefficiency in the study area.

Key concepts: Gross margin, Respondent, Agricultural science, Descriptive statistics, Productivity, Revenue, Hectare, Multistage sampling

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