Abstract
Background: Groundnut (Arachis hypogaea L.), a globally prominent oilseed crop, is experiencing significant losses due to the Groundnut Bud Necrosis Virus (GBNV). The extended range weather forecast (ERWF) provides timely weather information and protects crops from weather-induced biotic and abiotic risks. Methods: An ERWF-based GBNV disease forewarning study was conducted at Coimbatore, Tamil Nadu in 2023 and 2024. The ERWF output from Weather Research and Forecasting (WRFv4.4) with two microphysics (WSM3 and Kessler) were leveraged to forewarn the GBNV disease, using the thumb rule as adapted in Tamil Nadu Agricultural University-Agro Advisory Service (TNAU - AAS): Web cum Mobile App, which is maximum temperature ( greater than 33oC), relative humidity (40-70%), wind speed ( greater than 5 kmph) and rainfall (0 mm). Result: Among the two microphysics options, the WSM3 performed better and provided more usable ERWF than the Kessler scheme. The WSM3 based ERWF usability percentage was 50 to 100 for rainfall and 80-100 for all other weather variables. The higher performance of ERWF resulted in a more precise forewarning of thrips and GBNV. The first and peak activity of thrips and GBNV incidence was well correlated (70-80%) with the ERWF based forewarning.
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