Improved Crop Yield Loss Prediction Using Multiple Regression Model with Environmental Factors

This study investigates the relationship between crop yield loss and four key environmental impact factors: temperature, precipitation, soil moisture, and topography. By utilizing a multiple regression model, we aimed to determine the influence of these factors on yield loss. Our analysis revealed that the inclusion of multiple factors, as opposed to considering them in isolation, significantly improved the model's accuracy in predicting yield loss. This improvement was evidenced by a notable change in both the mean squared error (MSE) and the Matthews correlation coefficient (MCC). These findings highlight the importance of considering the combined effects of environmental factors when predicting and understanding the impact of environmental conditions on crop yield.