Stepwise Regression Models-Based Prediction for Leaf Rust Severity and Yield Loss in Wheat

Leaf rust is a devastating disease in wheat crop. The forecasting models can facilitate the economic and effective use of fungicides assist limiting crop yield losses. In this study, six cultivars were screened against leaf at two locations, during three consecutive growing seasons. Subsequently, stepwise regression analysis was employed to analyze correlation epidemiological variables (minimum temperature, maximum minimum relative humidity, rainfall wind speed) with severity loss (%). Disease predictive developed for each cultivar final prediction. Principally, all indicated positive association (%) except humidity. effectiveness estimated using coefficient determination (R2) values models. Then, these validated forecast another location Faisalabad. R2 tested high, evincing that our could be effectively predict anticipated loss. validation results explained 99% variability, suggesting highly accurate prediction (leaf loss). research used by farmers epidemics make management decisions accordingly.