A data-driven approach for devising and assessing precision nitrogen management strategies applied to wheat systems in India
Year: 2025
Type: article
Abstract: Limiting nitrogen pollution from crop production is essential for mitigating greenhouse gas emissions and protecting aquatic ecosystems while maintaining food security. Precision nitrogen management (PNM) provides a conceptual framework for achieving yield goals while maintaining nitrogen pollution within planetary boundaries by matching fertilizer rates to specific production conditions. Nevertheless, PNM strategies for smallholder contexts like India, a global nitrogen pollution hotspot, have proven costly to implement and are often ineffective. By combining survey data of production practices from 8705 wheat fields with digital soil mapping, we develop a novel PNM strategy that ‘learns from landscapes’ to generate and evaluate novel decision logic for nitrogen management. With this approach, ex-ante simulations indicate that reductions of 9% in nitrogen use and 16% in N 2 O emissions can be achieved without compromising yields, saving US$ 28 million per year in subsidies for the Indian state of Bihar alone. In contrast, conventional soil test-based recommendations may increase nitrogen use by 5% without corresponding yield gains. Our method that leverages large- n survey data and predictive modeling may provide a scalable pathway for PNM in similarly complex crop production environments where field and management heterogeneity is high.
Institutions: International Maize and Wheat Improvement Center, Cornell University, International Maize and Wheat Improvement Center, Environmental Defense Fund, International Rice Research Institute, Leibniz University Hannover, Indian Council of Agricultural Research, Australian Government, Department of Primary Industries and Regional Development
Language: English
Subfield: Soil Science
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,515
OpenAlex ID: W4415638858
