Determinants of Smallholder Maize Productivity in Western Kenya: Evidence From a Post Harvest Plot Level Survey
Authors
Wilbrodah Adhiambo Orina (PhD)
Educational/Research Consultant, Core Health and Wealth International, Eldoret, Kenya (Kenya)
Data Analyst, Searchlight Research, Nairobi, Kenya (Kenya)
Article Information
DOI: 10.47772/IJRISS.2026.100600885
Subject Category: Agriculture
Volume/Issue: 10/6 | Page No: 12579-12594
Publication Timeline
Submitted: 2026-06-15
Accepted: 2026-06-20
Published: 2026-07-08
Abstract
In developing agrarian economies, smallholder maize production serves as a critical pillar for rural livelihoods and national food security, yet conventional agricultural interventions consistently struggle to close persistent yield gaps. While structural policy frameworks heavily prioritize upstream input distribution, the systemic interplay between field-level management, post-harvest preservation, and empirical data accuracy remains poorly understood. Smallholder maize productivity in sub-Saharan Africa remains substantially below biological potential; Bungoma County in Western Kenya exemplifies this yield gap. This cross-sectional study examined agronomic and socio-economic factors associated with maize yield among 400 systematically sampled households using a post-harvest, plot-level survey. A thirteen-item Good Agricultural Practice (GAP) score was constructed (mean = 5.15/13; SD = 1.68) and decomposed into production and post-harvest sub-indices. Yield was measured on a six-category ordinal scale (<6 to ≥30 bags per acre). Ordinal logistic regression models were estimated alongside alternative specifications, including ordered probit models and wealth controls, to evaluate the robustness of identified yield determinants. Improved storage was the only predictor consistently associated with higher reported yield across all specifications. The post-harvest GAP sub-index correlated positively with yield (OR = 1.282, p = 0.033), whereas the production sub-index lacked statistical significance. Wealth was also positively associated with yield after adjusting for agronomic practices (OR = 1.206, p = 0.035). These findings suggest that post-harvest management significantly influences reported productivity in recall-based surveys. They further highlight the necessity of distinguishing between harvested production and grain retained after storage. Consequently, agricultural policy should pivot from a narrow focus on seed and fertiliser subsidies toward improving post-harvest infrastructure and localized storage technologies.
Keywords
Maize Productivity; Good Agricultural Practice; Post-Harvest Management; Yield Gap; Smallholder Agriculture
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References
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