Maize [Zea Mays (L.)] crop-nutrient response functions extrapolation for Sub-Saharan Africa

There is a need for methods to scale up site specific field trial results for maize to larger areas. The objectives of this research for SSA were to establish relationships between maize crop-nutrient response functions and biophysical variables; determine prediction equations for maize crop-nutrient response functions; and extrapolate (predict) maize nutrient response functions using the predictor equations to areas of interest and evaluate the goodness-of-fit of the data. Geo-referenced maize-nutrient response functions of 736, 488, and 152 for N, P and K, respectively, determined from past and recent research results by the project OFRA were used. New geo-referenced 4646 points were identified across SSA to predict crop-nutrient response functions using the prediction equations. The independent variables considered were elevation, location, climate and soil properties and their square and two-way interactions. Data were subjected to GLM at P ae<currency> 0.05. The coefficients of maize nutrient-response functions model's goodness-of-fits were evaluated using coefficient of determination (R-2), cross-validated R-2 (q(2)), R (o) (2) and R (o) ('2) and RMSE with mean values of 0.67, 0.65, 0.67, 0.68 and 0.16 Mg ha(-1), respectively. These values indicate the robustness and predictive ability of the predictive models for the study area conditions. In conclusion, these predictive equations can be used to estimate maize nutrient response functions for important maize growing areas throughout SSA.