A Study on Applications of Mathematical Modelling in Agriculture: Enhancing Crop Productivity and Food Security in Kogi State, Nigeria

This study investigates the applications of mathematical modelling in enhancing crop productivity and food security in Kogi State, Nigeria. We considered various modelling approaches, including crop growth models, pest population dynamics, irrigation management, and fertilizer optimization, to analyze their impacts on agricultural practices. Using MATLAB, we simulate a pest population dynamics model, which revealed critical insights into the interactions between pests and crops. The results indicate a gradual decline in pest populations, ultimately reaching zero, due to effective pest management practices and diminishing food resources as crop health declined. Initially, the crop population showed robust growth, benefiting from favorable environmental conditions and effective early pest management. However, as pest pressures increased, crop health deteriorated, leading to reduced yields. The Whether Research and Forecasting (WRF) model helped rice farmers adjust planting schedules, resulting in 15% yield increase compared to those using traditional methods. The CERES model optimized fertilizer use for maize, reducing fertilizer by 20% while increasing yield by 25%. The SIMPEST model for pest control on tomato farms reduced pesticide use by 25% and crop loss to 10%. This study emphasizes the importance of integrated pest management strategies that not only control pest populations but also promote crop resilience. In practical applications. Our findings demonstrate how mathematical models enhance crop productivity and resources efficiency, it advocates for collaborative efforts among farmers, researchers, and policymakers to leverage mathematical modelling as a tool for developing sustainable agricultural practices that address food security challenges in Kogi State and beyond.