Assessing seeding rate management strategies for maize production in South Africa: Insights from the Data Intensive Farm Management Project

Abstract

Maize (Zea mays L.) is South Africa’s most widely cultivated row crop, yet traditional flat-rate seeding practices often fail to account for spatial variability, potentially limiting yield and profitability. This study evaluated the agronomic and economic outcomes of three seeding rate strategies—producers’ status quo, optimal flat rate, and optimal variable rate, where “optimal” refers to profit-maximizing rates—across nineteen site-years in four major maize-producing regions of South Africa. Trials were conducted in the 2020/2021 to 2023/2024 seasons under diverse climatic and soil conditions, capturing a range of yield potentials and environmental variability. Data from planters with precision agriculture technology and yield monitors were processed into subplots to account for intra-field heterogeneity, and linear mixed-effects models were used to quantify yield responses. Both profit-maximizing flat and variable rate approaches increased yield relative to producers’ status quo, with mean yield gains of 1.05 and 1.57 t ha⁻¹, respectively. Yield responses were strongly influenced by site- and season-specific factors, particularly rainfall and baseline productivity. Variable rate seeding provided yield advantages in fields with pronounced spatial heterogeneity, though gains were often marginal in uniform fields or under constrained yield potential. Across all site-years, 79% of site-years performed better under optimal flat rates, and 89% of site-years under optimal variable rates, compared to the producers’ status quo seeding rates. These findings demonstrate that both flat- and variable-rate optimization can enhance productivity, however the relative benefits of variable-rate seeding depend on site-specific conditions, such as baseline yield potential and spatial variability. Environments exhibiting substantial within-field variability in yield response to inputs offer the greatest potential for optimization, whereas fields that are spatially uniform or consistently yield-limited show limited additional benefit from variable rate strategies. Future research should focus on integrating multi-source datasets, hybrid-specific responses, and long-term, multi-season trials to refine site-specific recommendations and improve decision-making for sustainable maize production under precision agriculture.