Context-dependent agricultural intensification pathways to increase rice production in India

Hari Sankar Nayak (), Andrew J. McDonald, Virender Kumar, Peter Craufurd, Shantanu Kumar Dubey, Amaresh Kumar Nayak, Chiter Mal Parihar, Panneerselvam Peramaiyan, Shishpal Poonia, Kindie Tesfaye, Ram K. Malik, Anton Urfels, Udham Singh Gautam and João Vasco Silva
Additional contact information
Hari Sankar Nayak: Cornell University
Andrew J. McDonald: Cornell University
Virender Kumar: International Rice Research Institute (IRRI)
Peter Craufurd: South Asia Regional Office
Shantanu Kumar Dubey: Indian Council of Agricultural Research (ICAR)
Amaresh Kumar Nayak: ICAR-National Rice Research Institute
Chiter Mal Parihar: ICAR-Indian Agricultural Research Institute
Panneerselvam Peramaiyan: International Rice Research Institute (IRRI) - South Asia Regional Centre (ISARC)
Shishpal Poonia: National Agricultural Science Complex (NASC)
Kindie Tesfaye: International Maize and Wheat Improvement Center (CIMMYT)
Ram K. Malik: National Agricultural Science Complex (NASC)
Anton Urfels: Cornell University
Udham Singh Gautam: Indian Council of Agricultural Research (ICAR)
João Vasco Silva: International Maize and Wheat Improvement Center (CIMMYT)

Nature Communications, 2024, vol. 15, issue 1, 1-11

Abstract: Abstract Yield gap analysis is used to characterize the untapped production potential of cropping systems. With emerging large-n agronomic datasets and data science methods, pathways for narrowing yield gaps can be identified that provide actionable insights into where and how cropping systems can be sustainably intensified. Here we characterize the contributing factors to rice yield gaps across seven Indian states, with a case study region used to assess the power of intervention targeting. Primary yield constraints in the case study region were nitrogen and irrigation, but scenario analysis suggests modest average yield gains with universal adoption of higher nitrogen rates. When nitrogen limited fields are targeted for practice change (47% of the sample), yield gains are predicted to double. When nitrogen and irrigation co-limitations are targeted (20% of the sample), yield gains more than tripled. Results suggest that analytics-led strategies for crop intensification can generate transformative advances in productivity, profitability, and environmental outcomes.

Date: 2024
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DOI: 10.1038/s41467-024-52448-6

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