Temporal Dynamics and Weather-based Predictive Modeling of Powdery Mildew (Leveillula taurica) in Chilli (Capsicum annuum L.)

Abstract

Powdery mildew, incited by the endophytic fungus Leveillula taurica (Lev.) Arn., is a major foliar constraint in chilli cultivation. To quantify the epidemiological progression of the disease and establish a predictive relationship with microclimatic variables, a field study was conducted using 35-day-old transplanted seedlings. Disease monitoring began upon the first natural appearance of powdery mildew symptoms and continued for an active observation period of thirteen Standard Meteorological Weeks (SMW 48 to SMW 8). The disease initiated at a baseline PDI of 4.44% during SMW 48 and entered a rapid logarithmic phase, reaching a peak severity of 68.88% by SMW 4 (January 22 – 28). The cumulative disease pressure, measured as the Area Under the Disease Progress Curve (AUDPC), was 3204.21. The maximum apparent rate of infection (r) reached 0.14 units/day during the initial outbreak phase between SMW 48 and 49. Correlation analysis revealed that wind speed (r = 0.80) and maximum temperature (r = 0.60) acted as strong positive drivers for disease progression, whereas rainfall exhibited a deterrent effect (r = -0.50). An Ordinary Least Squares (OLS) multiple linear regression model was developed (R2 = 0.88, Adjusted  R2 = 0.79), indicating that weather variables collectively explained a highly significant portion of the variance in disease severity (P = 0.0043). This weather-based forecasting model provides a crucial decision-support tool for optimizing integrated disease management (IDM) strategies.