Statistical Estimation of Onion Seedling Density: A Planning Framework for Smallholder Traditional Farms in Pwalugu, Ghana

Traditional smallholder farming systems often operate without systematic quantitative records, creating a data gap that hinders accurate resource forecasting. This study examines a two-acre onion farm in Pwalugu in the Upper East Region of Ghana, characterized by manually constructed sunken beds and gravity-fed basin irrigation. We applied a random sampling approach ( n=50 ) and the Central Limit Theorem to estimate seedling density and land efficiency. The estimated mean density was 48.43 plants/m 2 ( SD=21.82 ; 95% CI: 42.23–54.63), with a high Coefficient of Variation (45.05%) reflecting the manual nature of transplanting. Exploratory analysis revealed a mean land efficiency ( Ri ) of 0.91, though regression analysis showed that Ri was not a significant predictor of density ( R2=0.07 , p=0.06 ). These results demonstrate that while irrigation architecture is driven by topographic necessity and gravity-fed slopes, planting intensity remains governed by a consistent, independent cultural heuristic. The study provides a planning framework—estimating approximately 4,843 seedlings per 100 m 2 —offering a scalable decision-support tool for resource optimization in traditionally data-scarce agricultural environments.