Summary The purpose of this study was to develop prototype farm plans according to the multi-objective production goals of small-scale arable crop producers in Kogi State, Nigeria. A multi-stage sampling technique was used to select a total of 137 farm households in different local government areas (LGAs). A structured questionnaire complemented with interview schedule was used to collect primary data from the respondents. Descriptive statistics and linear goal programming were used for data analysis. The results obtained indicate that the optimal plan of generating an income of ₦242,076.20 requires 0.368 ha of melons, 0.044 ha of yam/maize mixture and 0.259 ha of sorghum/groundnuts. The optimal net profit was 44.05% higher than that achieved by implementing the existing plan. To meet family food requirements, the solution plan prescribed devoting 0.048 ha to cassava, 0.211 ha to sorghum, 0.368 ha to melons, 0.074ha to Bambara nuts, and 1.065 ha to sorghum/groundnuts to generate an income of ₦158,475.00. To minimize paid labour and generate an income of ₦168,325.50, the plan prescribed devoting 0.195 ha to rice, 0.502 ha to melons and 0.246 ha to Bambara nuts. Out of the three basic farm household objectives considered, meeting family food requirements and limiting labour expenditure were overachieved, whereas the objective of maximizing farm income was underachieved. A great deal of the existing staple food plan was found consistent with the prescribed optimal plan, except in the case of existing cassava and Bambara nut production which was falling short of the optimal production prescribed. The maize/groundnut production had the lowest shadow prices. However, land, labour, capital, agrochemicals, fertilizers and seeds constituted the limiting resources in the plan. It was found that these resources were not optimally allocated in the existing plan for arable crop activities. Therefore, the respondents were advised to utilize their resources as prescribed in the optimum plan, supported by farm advisory services in selecting good crop mixtures.
Read full abstract