Transitioning toward sustainable agriculture production is key in achieving social, economic and environment related United Nations’ Sustainable Development Goals. Current agriculture sector of most low-income and malnourished nations either do not produce enough essential micronutrients or have high environmental impacts transgressing planetary boundaries or both. However, figuring out a nutritionally adequate crop and livestock production mix that is low in environmental impact and is profitable to farmers, is a formidable challenge. A first step towards designing an optimum agricultural production mix is quantitative information on how much damage is being done to different domains of the environment (climate, freshwater, land, nitrogen, phosphorus use) due to different crop and livestock production in a country, what amounts of different nutrients (calories, protein, vitamins, minerals etc.) essential for human health are being produced vis-à-vis population requirements and what monetary profit farmers derive from each agriculture product. Here through a case-study on Indian agriculture, we demonstrate how environmental life cycle assessment (LCA) tool and data analytics can be used to calculate above parameters at a sub-national scale (35 Indian states and Union Territories) and how this information can then be used to derive sustainable production amounts of 140 different food items in each state through scenario analysis and mathematical optimization algorithms. Our results can be useful to policy makers in deciding which foods’ production to promote and discourage in different states for solving India's nutrition problem without jeopardizing the environment and farmers’ income.

Leveraging data analytics and life cycle assessment tool for informing sustainable agricultural production

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