Optimizing Rice Thresher Performance in Nigeria: A Systematic Review and Meta-Analytic Synthesis of Response Surface

Postharvest rice losses in Nigeria persist at 15–25%, partly attributable to the absence of standardised optimization frameworks for mechanised smallholder threshers. No study has directly compared Response Surface Methodology (RSM) and Taguchi optimization in this context. This PRISMA 2020 systematic review and metaanalysis synthesises 35 studies (2010–2025) sourced from Scopus, Google Scholar, and AJOL, comprising RSM (n=12), Taguchi (n=8), hybrid (n=3), and factorial ANOVA (n=12) designs. Meta-analytic procedures included Cohen’s d effect size computation, variance ratio analysis, Egger’s regression, and trim-and-fill correction. Cylinder speed (optimal: 750–825 RPM; reported precision peak approximately 770 RPM) contributed 62.4% of threshing efficiency variance. Moisture content optima were 13–14% for grain quality and 16–18% for maximum throughput. Feed rate optimum was 3 kg·min−1, blower air velocity peaked cleaning efficiency at 99.32% (6.0 m·s⁻¹), and a 4.5 Hz vibrating sieve reduced scatter loss from 5.2% to 1.8%. Meta-analysis revealed no significant difference in threshing efficiency between RSM (94.2%) and Taguchi (93.1%) frameworks (p=0.21; Cohen’s d=+0.35), though RSM yielded 26–40% lower output variance (differences not statistically significant; p > 0.27). Publication bias inflated mean throughput by 8.3%; the bias-adjusted estimate is 187 kg·h⁻¹. A hybrid sequential strategy — Taguchi L screening followed by RSM-CCD refinement — is recommended for future optimization studies.