Assessing the economic and data management impacts of precision agriculture among smallholder farms in Nigeria

Abstract

 This study provides an econometric analysis of the impact of precision agriculture (PA) technologies on the economic sustainability and data management practices of smallholder farms in Nigeria. While PA technologies promise to enhance productivity and optimise resources, their adoption among smallholder farmers, who form the backbone of agriculture in developing economies, remains constrained. This study fills a critical research gap by employing a mixed-methods approach that combines survey data from 250 smallholder farmers in Oyo State, Nigeria, with 20 in-depth interviews. An Ordinary Least Squares (OLS) regression model was used to analyse the relationship between a PA technology adoption index and economic sustainability, measured as net farm income per hectare. Pre-estimation diagnostics confirmed the model's suitability, and post-estimation robustness checks affirmed the core findings. The model showed a strong fit (Adjusted R² = 0.68), indicating that a one-unit increase in the PA adoption index is associated with a statistically significant increase in net farm income (β = 0.38, p < 0.01). Qualitative findings reveal that while PA improves data management for better decision-making, significant adoption barriers, notably high initial costs, lack of technical knowledge, and poor infrastructure, persist. The novelty of this study lies in its development of a PA adoption index tailored to the Nigerian context and its mixed-methods validation of the economic benefits and systemic barriers. The findings suggest that targeted policy interventions, including financial support, bespoke training programs, and improved data infrastructure, are essential to unlock the transformative potential of precision agriculture for sustainable development.