Disease Assessment in Rice with Pervasive Stationary and Mobile Sensing - Learnings from Rabi 2019-20

Rice is an economically important food crop in South Asian countries including India. It provides two thirds of the calorie intake of more than 3 billion people in Asia and one third of the calorie intake of nearly 1.5 billion people in Africa and Latin America (FAO, 1995). Identifying and diagnosing the symptoms of rice crop diseases is critical to plan effective protection measures in order to provide agro-advisory services. Effective crop protection from diseases requires close and precise monitoring of various parameters towards timely prediction and early detection of symptoms on the crop. IoT can play a pivotal role in this. With granular ambient micro-climate conditions from stationary locations in the region and ground reported events through mobile sensing, we present insights associated with disease forecasts and early disease detection with imaging for effective real-time diagnosis. For a prominent rice-growing region in Tamil Nadu, disease-related stress assessments are discussed for the Rabi (winter) season of 2019-20 which includes calibrated ground surveys for distributed sensing of disease incidents. For three prominent diseases in rice - Bacterial Leaf Blight, Sheath Blight and False Smut - the outcomes of technology interventions were found to be in good agreement with the ground observations paving the way for effective in-season management of the crop.