The Optimization of Maize yield Production Using Simplex Lattice Design for Third Degree Mixture Model

This study involved mixture experiment for fertilizer components in maize crop production. Researchers in agriculture have conducted research on maize plants with different levels of single fertilizers with a view of obtaining an appropriate amount for optimal yield. However, studies based on fertilizer blending are not very common. This has left farmers with no option other than to continue applying fertilizer in random proportions that may not guarantee the optimal yield with respect to fertilizer components available. The objectives was to determine appropriate statistical models expressing the maize yield as response variable and to evaluate optimal sets of mixture of fertilizer components that could maximize the response variables of interest. Di-Ammonium Phosphate (DAP), Poultry manure (guano), Sheep manure, and Farmyard manure were the four independent variables to optimize the response value of the maize yield. Mixture experiments entail the blending of these components to determine if synergism exists in the mixture or blends of these fertilizer components. The statistical model formulated for the maize yield demonstrates the effects of each component and the interaction with other components displaying the trend of the response parameter. From the model, it can be concluded that farmyard manure and poultry manure have greater effect on the production of maize yield and hence, this study conclusively attained the optimal conditions of 6.67 tons ha -1 of farmyard manure mixed with 1.3467 tons ha -1 of poultry manure. Under these conditions, the farmer achieves maximum output of 12.17 tons ha -1 of maize yield. The study upholds that mixture experiments are appropriate in modeling agricultural production involving various independent parameters that produces synergetic effect on the output parameter. KEY WORDS: Maize yield; Fertilizer; Model; Mixture experiment; Simplex Lattice Design. DOI : 10.7176/MTM/9-7-07 Publication date : July 31 st 2019