Swagatam Bose Choudhury, Vidit Patil, Abhishek Kumar, R. Kulat, Sanat Sarangi, Hemavathy B, S. Pappula
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Scalable Prediction of Potato Pests and Diseases with Insights from Mobile Sensing for Rabi 2021–22
Large scale adoption of digital technologies in farming is expanding the reach of precision agriculture. The Indo-Gangetic region in northern India is a major potato growing belt where West Bengal is one of the prominent states with Early Blight, Late Blight, Septoria Leaf Spot, and Thrips being some key disease and pest conditions. Forecasting stress across the region requires models that understand the crop, its stress behaviour dynamics and variation of ambient conditions across the zone of interest. For rapidly changing conditions on the ground, predicting the likelihood of stress could be combined with detection of stress incidents through images to course-correct timely during the season thereby mitigating risks. We present the work on region-level stress forecast in potato supported by automated detection of reported conditions for the Rabi season of 2021–22 in West Bengal. The results with various proposed approaches are presented and contrasted to address the related scenarios.