article · Tekirdağ Ziraat Fakültesi Dergisi
An empirical study of 150 sesame producers in North West Nigeria assessed production efficiency using a stochastic production efficiency frontier model and principal component analysis. The findings reveal that farm size, chemical inputs, seeds, fertilisers, and labour significantly influence technical efficiency. In addition, farmer education, age, years of experience, household size, and access to extension services reduce technical inefficiency. The sesame farming surveyed demonstrated increasing returns to scale, but farmers operated at an average technical efficiency score of 0.5430, leaving an inefficiency gap of 0.4570. Inefficiency accounted for 80.38 per cent of output variation, with the remainder driven by uncontrollable environmental factors. Farmers cited lack of credit, lack of improved quality seeds, and the high cost of farm inputs as their primary operational barriers.
Sesame is a vital agricultural commodity, yet smallholders often fall short of potential harvest levels. Identifying that more than 45 per cent of output variation stems from manageable inefficiencies rather than natural disasters demonstrates clear scope for intervention. Targeted improvements in extension delivery, credit availability, and input supply could substantially elevate farm yields and producer livelihoods.
This applied socio-economic study does not present a commercial product, but it provides market evidence for agricultural service providers, input distributors, and microfinance institutions. The data points to immediate, near-market opportunities for agribusinesses to supply certified seed varieties, affordable agrochemicals, and tailored credit products to underserved sesame farmers in the region.
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This research study analyzed production efficiency among sesame (Sesamum indicum) farmers in North West, Nigeria. Approximately, 150 sesame producers were selected among the villages utilizing a multi-stage sampling approach. Data used were of primary sources based on a well-structured questionnaire. The method employed econometric tools for analysis of data which include stochastic production efficiency frontier model (SPEFM) and principal component model (PCM). The result shows that the significant predictors influencing TE (Technical Efficiency) of sesame production include farm size, chemical, seed, fertilizer, and labour. The significant socio-economic factors increasing TE or decreasing technical inefficiency (TIE) of sesame production include education, age, years of farm experience, size of household, and extension contact. The calculated return to scale (RTS) was 1.4025, this signifies an increasing RTS. The gamma or variance ratio of 0.8038 implies that 80.38% of random variations in output of sesame is due to farmers’ inefficiency, the remaining 19.62% of sesame output deviation from the potential level was because of random noises like unexpected rainfall, frost, and other natural disaster beyond the control of sesame producers. The minimum estimated technical efficiency is 0.06, the maximum is 0.98. The average TE score of sesame producer is 0.5430 leaving out an inefficiency gap of 0.4570 for improvement. The coefficient of total variance (σ^2) is 2.9221, this was significant at 1 percent probability level, which hypothesized that perfect goodness of fit of data with the Cobb-Douglas stochastic frontier model and also the assumption of the composite error term was properly specified. The 3 major constraints faced by sesame producers include lack of credit (1st), lack of improved quality seeds (2nd), and high cost of farm inputs(3rd). The study recommends based on the outcome of this research that farm inputs such as fertilizers, chemical. and improved quality seeds should be given to sesame producers at affordable prices and at appropriate time to increase productivity and efficiency.
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DOI: 10.33462/jotaf.1478666
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