FORECASTING LATE BLIGHT OF POTATO IN TARAI REGION OF UTTARAKHAND USING MODIFIED JHULSACAST MODEL

Abstract

Late blight is the most destructive disease affecting potato crop worldwide. Disease control requires regular application of fungicides at high rates and at short intervals throughout the growing season resulting in health and environment related problems. Timely forecasting of the disease helps in reducing crop losses caused by late blight. Fourteen worldwide published forecasting models were tested for predicting late blight in Tarai region of Uttarakhand. None of the model could predict late blight appearance under Tarai conditions with high efficacy. Since JHULSACAST model developed for western Uttar Pradesh showed highest accuracy for late blight prediction under Tarai conditions, modifications in the input parameters (relative humidity and temperature duration) were made by utilising weather data for 15 years collected at GB Pant University of Agriculture & Technology, Pantnagar for fine tuning the JHULSACAST. The modified JHULSACAST model could predict late blight within 14 days with accuracy of 86% under Tarai conditions if 7 day moving relative humidity (≥85%) period ≥85 hours and 7 day moving congenial temperature (7.2 to 26.6°C) ≥135 hours conditions prevail for 7-consecutive days. The model was validated and predicted late blight successfully for three years.