Climate change will increase the vulnerability of agricultural production systems, unless scientists and farmers reorient their present approaches toward making them climate smart or climate resilient. The integration of recent developments in big data analytics and climate change science with agriculture can greatly accelerate agricultural research and innovation for climate smart agriculture (CSA). CSA refers to an integrated set of technologies and practices that simultaneously improve farm productivity and incomes, increase adaptive capacity to climate change effects, and reduce green house gas emissions from farming. It is a multi-stage, multi-objective, data-driven, and knowledge based approach to agriculture, with the farm as the most fundamental unit for both strategic and tactical decisions. This paper explores how big data analytics can accelerate research and innovation for CSA. Three levels at which big data can enhance farmer field level insights and actionable knowledge for the practice of CSA are identified: (i) developing a predictive capability to factor climate change effects to scales relevant to farming practice, (ii) speeding up plant breeding for higher productivity and climate resilience, and (iii) delivery of customized and prescriptive real-time farm knowledge for higher productivity, climate change adaptation and mitigation. The state-of-art on big data based approaches at each of the three levels is assessed. The paper also identifies the research and institutional challenges, and the way forward for leveraging big data in research and innovation aimed at climate smart agriculture in India.
Rao, NH
Big Data and Climate Smart Agriculture - Status and Implications for Agricultural Research and Innovation in India
Proceedings Of The Indian National Science Academy