Effects of Intelligence-Based Extension Services on Arable Farmers’ Income in Niger State, Nigeria

Abstract

This study examined the effects of intelligence-based extension services on arable farmers’ income in Niger state, Nigeria. A multistage sampling procedure was used to select 240 arable farmers for the study. Primary data were collected through the use of structured questionnaires administered to the respondents using Kobo Collect. Data were analyzed using Principal Component Analysis (PCA) and Bayesian regression techniques. Results revealed that intelligence-based extension services were grouped into six major components, including digital extension tools, communication platforms, market information systems, institutional access tools, precision agriculture, and smart farming support. The PCA adoption index had a positive and significant effect on income (posterior mean coefficient = 4.077), indicating that increased adoption improves farmers’ earnings. Other significant posterior mean coefficient factors influencing income included age (1.782), cooperative membership (2.737), farm size (29.597), labour input (6.067) and access to mobile phones (18.770). Key adoption-enhancing strategies, such as improved internet access, affordable smartphones, digital training, integration with traditional extension services, and stronger institutional support, were identified. The study concludes that intelligence-based extension services significantly enhance farmers’ income. Therefore, increased government and private sector investment in rural digital infrastructure and integration of intelligence-based platforms with conventional extension delivery systems were recommended.