Beta regression model for predicting development of powdery mildew in black gram

Abstract

Black gram is a widely grown pulse crop in Asia, prized for its nutritional value and compatibility with various cropping systems. However, the occurrence of powdery mildew, Erysiphe polygoni DC disease poses a significant challenge to black gram production, resulting in potential yield losses in Tamil Nadu. Over a six-year period, spanning from 2017-2018 to 2022-2023, field experiments were conducted during the rabi season at the black soil farm of the Agricultural Research Station in Kovilpatti. The primary objective was to evaluate the incidence of powdery mildew in black gram and establish a statistical model by correlating it with weather variables. Notably, observations of disease index were most frequent during the flowering and pod development stages of the crop. Among the eleven weather parameters considered in the study, maximum temperature, afternoon relative humidity, and sunshine hours emerged as the key contributors to explaining the variation in the Disease Index. Further, a betareg model was developed using these selected variables to predict powdery mildew incidence in black gram.

Keywords

• Beta regression model
• Powdery mildew
• Black gram
• Prediction
• Weather