Optimization of arable land use towards meat-free and climate-smart agriculture: A case study in food self-sufficiency of Vietnam

UN Sustainable Development Goals and the Paris agreement for climate change indicate that a transition to sustainable and healthy diets is necessary. Additionally, the fact that agricultural sector is responsible for near a quarter of global greenhouse emissions (IPCC 2019 - special report on climate change), such transition will require substantial dietary shifts, including reduction of sugar and red meat consumption. Vietnam, with more than 95 millions of population, have a challenge to significantly reduce the rice consumption and convert some of the land used for it to production of more legumes. However, correct allocation of arable land for cultivation of particular crops’ combination that would ease the transition, and comply with recommendations for healthy nutritional intake, is a challenge of the society. We approached the problem of arable land allocation with mathematical optimization, in particular stochastic evolutionary computing. Arable land allocation to crops’ combination is evaluated through three objectives: food self-sufficiency, climate efficiency and crop diversity. Candidate solutions (crops’ combinations) were analysed through the non-dominated Pareto front with prioritizing the objective of food self-sufficiency of Vietnam. The results suggest significant change in production of certain crops. As such, sugar cane and rice are required to be reduced on expense of increased production of soybeans, maize, brassicas, and nuts. Therefore, the current surplus of produced carbohydrates would be reduced while proteins increased, which leads to balanced production of macronutrients.