Response Surface Methodology for Optimization and Modeling of Cassava Yield

O. Akinyemi, O. Faweya, F. B. Ogundele and A. O. Ilesanmi
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O. Akinyemi: Department of Statistics, Ekiti State University, Ado Ekiti Nigeria
O. Faweya: Department of Statistics, Ekiti State University, Ado Ekiti Nigeria
F. B. Ogundele: Department of Statistics, Ekiti State University, Ado Ekiti Nigeria
A. O. Ilesanmi: Department of Statistics, Ekiti State University, Ado Ekiti Nigeria

International Journal of Research and Innovation in Applied Science, 2025, vol. 10, issue 4, 763-769

Abstract: This study utilized Response Surface Methodology (RSM) to optimize cassava yield by analyzing the effects of four key factors: planting date, fertilizer application, cassava variety, and harvest date. Data were collected from the International Institute of Tropical Agriculture (IITA) using a Central Composite Design (CCD), which assessed the impact of these variables at different levels. The findings revealed that planting date, fertilizer, and harvest date significantly influenced cassava yield, with fertilizer application and harvest date showing the most substantial effects. Specifically, the regression model showed that a unit increase in planting date, fertilizer, cassava variety, and harvest date contributed to increases of 0.88, 1.698, 0.034, and 4.554 in cassava yield, respectively. The model analysis showed that harvest date had a greater influence on yield than other factors, suggesting its critical role in optimizing cassava production. Furthermore, the study demonstrated the effectiveness of RSM in analyzing agricultural data, optimizing experimental design, and reducing both costs and time. Based on the findings of this study, it is recommended that cassava farmers prioritize the optimization of planting and harvest dates, alongside appropriate fertilizer application, to maximize yield and improve farming practices and greater food security.

Date: 2025
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