Effect of weather variability on foliar blight severity in wheat (Triticum aestivum) across different agroclimatic locations of Punjab - ANAND, SHUBHAM; SANDHU, SARABJOT KAUR; TAK, PARMINDER SINGH; BISWAS, BARUN (The Indian Journal of Agricultural Sciences, 2026)
Foliar blight severity in wheat (Triticum aestivum L.) is highly dependent on prevailing weather conditions, sowing time and crop microclimate that together influence disease dynamics. In line with this, present study was carried out during winter (rabi) seasons of 2021–22 and 2022–23 at Punjab Agricultural University, Ludhiana, Punjab and Regional Research Station, Gurdaspur Punjab to investigate the effect of weather variability on severity of foliar blight with three wheat varieties, viz. PBW 725, HD 2967 and HD 3086 sown on different dates (14th–15th October, 8th–9th November and 3rd–4th December) under two microclimate modification levels i.e. M1 (recommended irrigation) and M2 (additional water sprays). The experiment was laid out in split plot design (SPD) with four replications. It was observed that early date of sowing (14–15th October) recorded higher foliar blight severity at Ludhiana (28.52%, 29.35%) and Gurdaspur (21.69%, 30.65%) in variety HD 3086 in M2 than other treatments, respectively. The highest mean Area Under Disease Progress Curve (AUDPC) (71.4, 79.1), relative AUDPC (11.1, 12.7) and total AUDPC (571.5, 711.7) in Ludhiana, as well as mean AUDPC (56.5, 83.3), relative AUDPC (9.2, 13.4) and total AUDPC (451.6, 750.1) in Gurdaspur were consistently higher in early sowing under M2 treatment in variety HD 3086 during both years of the study. Correlation and multiple regression analyses were employed to quantify the relationships between key weather parameters and foliar blight severity, identified minimum temperature, morning relative humidity and rainfall as key parameters in development of this disease. Warm and humid weather, especially after continuous rains, favours rapid foliar blight development. The suitability of regression models can be assessed for real time data in Punjab.