Fuzzy Logic Approach For Accurate Crop Yield Forecasting (Rice)

Abstract

This paper presents a comprehensive approach to rice crop yield prediction using MATLAB code for data visualization and analysis. We collected and analyzed data at key stages of the rice crop growing cycle, including planting, vegetative growth, reproductive growth, and maturity. Through the visualization of sample data and prediction of yield values, we gained insights into the factors influencing rice productivity and identified trends and variations across different stages of growth. Our analysis highlights the utility of MATLAB code in agricultural decision-making, allowing farmers and practitioners to optimize management strategies for enhanced crop yield potential. By integrating technological advancements into agricultural research and practice, we contribute to the advancement of sustainable rice cultivation practices and global food security efforts.