Predicting yields prior to harvest is critical for decision-making: for Governments to plan procurement, pricing and policy and as a digital tool for crop insurance.
Crop Insurance in India necessitates the use of intermediaries for assessing crop losses, a process that likely contributes towards low adoption rates of crop insurance schemes amongst farmers. In the face of increasing weather variability and climate change, accurate and dynamic prediction of crop yield prior to harvest using multi-modal data, including crop photos from farmers, weather data and forecasts, as well as soil data and agronomic inputs, is the need of the moment. Purely satellite or drone based imaging cannot have the predictive power of analysis from the ground.
BKC Aggregators has developed a Climate Smart Tool for Crop Yield Forecasting that uses this multimodal approach. Coupled with real-time crop advisories, our tool has additional advantage of potentially increased adoption rates of crop insurance schemes.
In this paper, we report the results of a pilot project with HDFC and IFPRI, USA , for predicting predicting wheat crop yields for two crop seasons of wheat in six districts of Punjab and Haryana (Rabi of 2016-17 & 2017-18).
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