Optimizing the performance of onion (Allium cepa l.) farmers in Northwestern Nigeria

Abstract

This research focused on optimizing the output of onion farmers in North West, Nigeria. A simple random sampling design was utilized to select 220 onion growers. Primary data were collected using a well-structured questionnaire. The data were analyzed using descriptive statistics, stochastic production efficiency frontier models, and Kendall’s coefficient of concordance. The analysis of technical efficiency shows that farmers operated at a mean efficiency score of 0.53, indicating 47% potential for productivity improvement. Stochastic production function estimates revealed that farm size and labor (p < 0.01) significantly influenced onion output. The estimated returns to scale (RTS = 1.4025) suggested increasing returns, implying that farmers could achieve higher output by scaling up input use. The inefficiency model reveals that education (–0.2759, p < 0.01), farming experience (–0.2709, p < 0.01), and access to credit (–0.3609, p < 0.01) are significant factors reducing inefficiency. The gamma (γ) parameter, which measures the proportion of variance attributable to inefficiency, was estimated at 0.7125. This implies that about 71% of the variation in onion output among farmers was due to inefficiency rather than random noise. The most critical challenges were high costs, limited access to fertilizers, pesticides, and labor shortages. The study concludes that efficiency is constrained by input costs, weak institutional support, and market barriers. It recommends policies promoting affordable input access, credit facilities, and strengthened extension services to optimize onion farmers’ productivity and enhance their livelihoods. Keywords: optimization, onion, Stochastic Production Frontier, Kendall’s Coefficient of Concordance, Nigeria