2019 Articles
Assessing the sustainability of post-Green Revolution cereals in India
Sustainable food systems aim to provide sufficient and nutritious food, while maximizing climate resilience and minimizing resource demands as well as negative environmental impacts. Historical practices, notably the Green Revolution, prioritized the single objective to maximize production over other nutritional and environmental dimensions. We quantitatively assess outcomes of alternative production decisions across multiple objectives using India’s rice-dominated monsoon cereal production as an example. We perform a series of optimizations to maximize nutrient production (i.e., protein and iron), minimize greenhouse gas (GHG) emissions and resource use (i.e., water and energy), or maximize resilience to climate extremes. We find that increasing the area under coarse cereals (i.e., millets, sorghum) improves nutritional supply (on average, +1% to +5% protein and +5% to +49% iron), increases climate resilience (1% to 13% fewer calories lost during an extreme dry year), and reduces GHGs (−2% to −13%) and demand for irrigation water (−3% to −21%) and energy (−2% to −12%) while maintaining calorie production and cropped area. The extent of these benefits partly depends on the feasibility of switching cropped area from rice to coarse cereals. Based on current production practices in 2 states, supporting these cobenefits could require greater manure and draft power but similar or less labor, fertilizer, and machinery. National- and state-level strategies considering multiple objectives in decisions about cereal production can move beyond many shortcomings of the Green Revolution while reinforcing the benefits. This ability to realistically incorporate multiple dimensions into intervention planning and implementation is the crux of sustainable food production systems worldwide.
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Also Published In
- Title
- Proceedings of the National Academy of Sciences
- DOI
- https://doi.org/10.1073/pnas.1910935116
More About This Work
- Academic Units
- Data Science Institute
- Ecology, Evolution, and Environmental Biology
- School of International and Public Affairs
- Published Here
- January 31, 2022