Influence of weather parameters on cotton leaf curl disease development and white fly population dynamics in S.W. haryana

Cotton leaf curl disease is a major devastating disease of cotton causing significant reduction in yield in the northern region of India where around 17.96 lakh hectare areas exists in the states of Punjab, Haryana and Rajasthan. Present study was under taken to evaluate the relationship between weather parameters and whitefly population in the CLCuD development of cotton under consideration in south west zone of Haryana over a period of four years i.e. Kharif, 2021 -2024. The maximum disease intensity was recorded as 33.62 % (45th SMW) in the year 2021 and the lowest (0.1%) during 30th SMW during all the years of experimentation. It was inferred that across all years, Tmax and Tmin exhibited consistently negative correlations with both CLCuD PDI and incidence, suggesting that lower temperatures favoured increased disease expression. Notably, Tmin showed stronger negative correlations than Tmax, indicating that cooler night temperatures play a critical role in promoting virus development. In contrast, morning relative humidity (RHm) displayed a positive correlation with CLCuD severity and incidence supporting the notion that high morning humidity favours both whitefly activity and virus infection. Evening relative humidity (RHe) showed weak and inconsistent correlations. Rainfall showed variable and generally weak correlations. Among all parameters, whitefly population consistently showed significant positive correlations with both PDI and disease incidence. This clearly highlights the central role of whitefly as the vector of cotton leaf curl virus (CLCuV). Furthermore, whitefly population was negatively correlated with Tmax and evaporation and positively with RHm indicating that cooler, more humid environments support vector proliferation and subsequent virus spread. The regression analysis clearly identifies low minimum temperature, high morning humidity, and increased sunshine hours as the most important weather parameters influencing CLCuD epidemics and vector build-up in cotton.The highest model fits were recorded for CLCuD PDI (R² = 0.9238) and incidence (R² = 0.9143), underscoring the reliability of these models for long-term disease forecasting.