India's agritech startups are employing data mining and AI to improve crop yield, make farming profitable

Bangalore: In 2016, The Times of India reported that 253 farmers from Lalkheda village in Khargone district of Madhya Pradesh received an average of Rs 2.83 each as insurance payouts for the loss of their soybean crop under the Pradhan Mantri Fasal Bima Yojana. The four of them went on to form SatSure, a data-analytics startup with “a mission to evolve crop insurance products and provide an accurate risk assessment of crop yield by integrating climatic variables with geospatial and economic datasets.” Agritech startups seem to be having their moment in the sun. And we do all this by analysing data gathered from satellite imagery.” SatSure’s website says the company helps “make sense of disparate operational and agronomic data to simplify complex decisions related to crop risk management and for making agriculture predictable and profitable.” SatSure has tied up with the government of Andhra Pradesh to provide the data to build a reliable credit-rating system for farmers. I would say that investments and startups in the sector are growing incrementally.” According to the State of Indian Agriculture report released by the ministry of agriculture in May 2016, “Out of the total land mass of 328.73 million hectares in the country, about 181.95 million hectares is agricultural land, which consists of 139.9 million hectares net sown area.” The problem is that the net sown area, which measures the amount of land cultivated in a given year, whether once or multiple times, is declining. We aim to supplement this with crop-sowing data, weather predictions, soil quality, and price visibility to give a holistic tech platform for income augmentation.” Pankaj Rai, senior vice-president for strategy at Wells Fargo Enterprise Global Services, believes that while agritech and AI can help cure some of the problems afflicting Indian agriculture, many challenges remain.