This study was carried out to evaluate the technical efficiency of maize-based cropping systems in Ondo State, Nigeria. Primary data were used with the aid of a well-designed questionnaire. A multistage sampling procedure was used to randomly select 160 respondents. The data collected were analyzed using descriptive statistics, budgeting technique, and stochastic frontier production function model. The results of the budgetary technique revealed that the average gross margin per hectare was ₦17,715.03, ₦53,230.76, and ₦14,651 for sole maize cropping system, maize-cassava cropping system, and maize-yam cropping system, respectively. It was shown that household size and access to credit were the main determinants of the technical efficiency in sole maize cropping pattern, while access to credit and farming experience were the main determinants of technical efficiency in maize-cassava. In maize-yam, educational level and household size significantly affected technical efficiency. Farmers in the study area were producing at about 76% efficiency in sole maize cropping system, 89% efficiency in maize-cassava cropping system, 82% efficiency in maize-yam cropping system. The elasticity of variables inputs was 0.18 in sole maize cropping system, 0.61 in maize-cassava cropping system, and 0.33 in maize-yam cropping system. This indicates that all the maize-based cropping system had decreasing return to scale; therefore, the cropping systems fell within the rational stage of production surface. The implication is that maize-based farmers have not attained maximum efficiency in term of their production. Therefore, policy attention should be directed towards appropriate production technique that would improve productivity in the study area. Manuscript profile

This study investigated the socio-cultural determinants of climate change adaptation and vulnerability among crop farmers in Ondo State, South-western Nigeria. Using a multi-stage sampling approach and the Delphi method, 150 respondents were selected from the three Senatorial Zones. Primary data were sourced with the aid of a survey and oral interviews. The collected data were analyzed using the vulnerability index, Ordinal logistic regression, and Heckman probit regression. The findings revealed that the socio-cultural characteristics of respondents contributed to their vulnerability to climate change, as indicated by an average livelihood vulnerability index (LVI) of 0.33. Notably, factors such as water availability and adaptation practices exhibited higher vulnerability indices of 0.49 and 0.42, respectively. The overall LVI and LVI-IPCC averages were 0.35 and 0.02, respectively, highlighting the existence of vulnerability among farming households. The results of ordinal logistic regression revealed that age, marital status, education level, and income from agriculture were statistically significant factors determining the level of vulnerability to climate change in the study area. Consequently, the results of the Heckman two-step regression model revealed that age, marital status, household size, education, religion, belief, family structure, and community teamwork were the significant factors affecting the adaptation and vulnerability to climate change in the area. Policy should be geared towards improving the socio-cultural factors for sustainable livelihoods with an income diversification strategy by the government for crop farmers in order to cushion the effects of low income realized from farming activities in the area. Manuscript profile