Abstract
Rice crops, which currently feed more than half of the world’s population, is crucial in global food systems. Creating more efficient and sustainable rice value chains can facilitate the realisation of United Nations’ Sustainable Development Goal of achieving zero hunger by 2050. Rice farming and milling suffer from interrelated techno-economic, policy and environmental constraints, whereas inefficient transport hamper rice distribution. Systematic and data-driven decision-making tools can help in understanding the complexity and in the formulation of effective strategies of national-level rice provision. For the first time, a multi-objective spatio-temporal mixed-integer linear programming model, based on the Value Web Model, was developed for rice value chains. The model can simultaneously optimise the value chains’ planning, design and operation for efficient and sustainable food provision with integrated production of energy, fuels and chemicals. It considers various impacts, such as costs and greenhouse gas (GHG) emissions, in order to quantify their trade-offs and identify synergies between food and energy sectors. The model was applied to the Philippines in order to determine rice value chains that will result in lowest cost and GHG emissions. Streamlining value chains can prompt the country to be 100% rice self-sufficient without additional farmlands expansion and potentially reduce retail prices. Integrating energy and food production can result in increased total farm productivity and reductions in GHG emissions by 25% and 24%, respectively, with minimal land expansion required. However, careful and strategic planning is required when implementing multi-product rice value chains as integrated production of food, energy, fuels and chemicals could require 70% more farmlands and generate twice more GHG emissions relative to the food production only scenarios.
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