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Data Science Applications in Indian Agriculture
Author(s) -
Devalkar Sripad K.,
Seshadri Sridhar,
Ghosh Chitrabhanu,
Mathias Allen
Publication year - 2018
Publication title -
production and operations management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.279
H-Index - 110
eISSN - 1937-5956
pISSN - 1059-1478
DOI - 10.1111/poms.12834
Subject(s) - livelihood , agriculture , data collection , task (project management) , face (sociological concept) , computer science , business , data science , economics , geography , management , social science , sociology , archaeology
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.