Response Surface Optimization of Sugarcane Yield under Varying Agronomic Inputs in Chiredzi District, Zimbabwe.

Edwin Rupi; Philimon Nyamugure; Peter Chimwanda

doi:10.52589/AJMSS-5HAT9F7V

Response Surface Optimization of Sugarcane Yield under Varying Agronomic Inputs in Chiredzi District, Zimbabwe. | AB Journals

Response Surface Optimization of Sugarcane Yield under Varying Agronomic Inputs in Chiredzi District, Zimbabwe.

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African Journal of Mathematics and Statistics Studies

Vol. 9Issue 12026pp. 72–86Published 19 February 2026

DOI 10.52589/AJMSS-5HAT9F7V

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Abstract:

This study aimed to optimize sugarcane yield using Response Surface Methodology (RSM). Through stratified random sampling and an emphasis on key agronomic variables, the research offered valuable insights to help farmers enhance their production practices. The yield, measured in tonnes per hectare for individual farmers, was analysed in relation to three influencing factors: the area planted, soil pH, and the organic matter content in the soil, across ten different plots. RSM was employed to develop a statistically validated predictive model, which was further refined through an optimization process. The analysis revealed a minimum yield of 87.5 tonnes per hectare, with soil pH and organic matter emerging as critical determinants. Optimal yield conditions were associated with a soil pH of 6.5 and organic matter levels exceeding 1.85%.

Keywords:Response Surface Methodology Steepest Ascent Optimization Central Composite Design (CCD).

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