International Journal of Plant & Soil Science

Sorghum rust, caused by Puccinia purpurea, significantly reduces crop yield, affecting plant growth and grain quality. Understanding the impact of weather parameters on disease incidence is crucial for timely disease management, to enhance crop resilience and yield stability. This study aims to identify and quantify the relationship between weather parameters and the incidence of sorghum rust, to inform decision-making on disease management strategies. A comprehensive analysis was conducted utilizing 17 years of secondary data (2006-2022) sourced from the All India Coordinated Research Project (AICRP) on Sorghum and the Department of Agrometeorology at the Climate Model Intercomparison Project (CMIP), University of Agricultural Sciences (UAS), Dharwad. The study employed statistical methods, including Multiple Linear Regression (MLR) and Step-wise Regression, to model the dependence of rust disease incidence on independent variables such as precipitation, temperature, relative humidity, wind speed, radiation, and heat flux. The results revealed the MLR model explains 65.45% of the variation and the Step-wise Regression model identifies four critical parameters- relative humidity, heat flux, wind speed, and radiation that together accounted for 65.09% of the variation without exhibiting multicollinearity (Variance Inflation Factor values below 10). These findings enhance the understanding of environmental impacts on sorghum rust and can inform future agricultural management strategies for disease prediction and control.