Climate Experience and Climate-smart Agriculture Adoption among Smallholder Farmers in Southwestern Nigeria
Folasade J. Odekunle, Jechoniah Agabi, Idris O. Jinadu, Gabriel O. Adebayo, Adedayo S. Adediran, Akeem A. Adewole, Segun S. Adelabu, Adedotun A. Adetunji
Journal of Agriculture and Ecology Research International · pp. 506–515 · Published 29 Sep 2026
10.9734/jaeri/2026/v27i5817Abstract
Climate-smart agriculture (CSA) is promoted to strengthen smallholder farming systems under climatic variability, yet adoption determinants remain context-specific, particularly where awareness is widespread. This study examined the association between farmers’ experience of changing weather conditions and reported CSA adoption among smallholder farmers in southwestern Nigeria, while accounting for selected socioeconomic and agricultural-information characteristics. Primary data were collected through a structured questionnaire administered to 190 farmers. Descriptive statistics characterised respondents, weather-change experience and CSA adoption. Because the adoption outcome was highly imbalanced, Firth-penalised logistic regression was used. CSA awareness was reported by 187 respondents (98.4%). Frequent experience of changing weather conditions was reported by 157 respondents (82.6%), and 174 of 188 respondents with valid responses (92.6%) reported at least occasional experience. Among 176 respondents with valid adoption responses, 168 (95.5%) reported using at least one CSA practice and eight (4.5%) reported non-adoption. The regression model, based on 173 complete observations, identified experience of changing weather conditions as the only statistically significant predictor of reported adoption (OR = 10.401, 95% CI: 3.118–34.694, p < 0.001). Gender, education, farm size and extension information were not statistically significant. The findings indicate a positive association between direct climate experience and reported CSA adoption, but the cross-sectional design does not support causal inference. Climate-adaptation interventions may therefore benefit from linking farmers’ observed weather experiences with locally relevant CSA options and decision support.
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