Data Science Applications in Indian Agriculture

Sripad K. Devalkar, Sridhar Seshadri (), Chitrabhanu Ghosh and Allen Mathias

Production and Operations Management, 2018, vol. 27, issue 9, 1701-1708

Abstract: Agricultural supply chains in the developing world face the daunting task of feeding a growing population in the coming decades. Along with the provision of food, sustaining livelihoods, enhancing nutrition and the ability to cope with rapid changes in the environment and marketplaces are equally important to millions of small farmers. Data science can help in many ways. In this article, we outline the beginnings of data science applications in Indian agriculture. We cover various initiatives such as data collection, visualization and information dissemination, and applications of algorithmic data analysis techniques for decision support. We describe one application under development that provides timely price information to farmers, traders, and policy makers.

Date: 2018
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