On analyzing the multiple regression model for the relationship between yield loss and the four impact factors and TA it is observed that the change in MSE and MCC indicate that the inclusion of m

Upon analyzing the multiple regression model that examines the relationship between yield loss and four impact factors (namely, temperature, precipitation, solar radiation, and temperature anomaly), it was observed that including multiple factors provides a more comprehensive explanation for yield loss in crops. This is evident from the change in MSE and MCC. As the relationships between the four factors are linearly correlated, principal component analysis (PCA) was utilized to reduce dimension analysis. The result indicates that the intensity factors of spring frosts are caused by the temperature anomaly. Additionally, it was found that the temperature anomaly not only causes changes in the intensity of spring frost but also increases the yield loss. This was established through fitting the yield loss with the four factors using a multiple linear regression model