Decision support algorithm to revamp homestead vegetable production for climate resilience and nutrition security

Abstract

Inadequate micronutrient diversity in diets remains a serious cause of malnutrition which is prevalent in rural areas especially in developing countries. The current study proposed a decision support algorithm for nutrition-sensitive vegetable production in semi-subsistence farming systems to improve their access to micronutrient-diverse and dense foods without compromising on economics of cultivation. Multi-dimensional nutri-economic data was modelled to compute micronutrient profiles along with the relative abundance of vegetables in diets, giving an advantage over other nutrition indices that measured diversity. Besides, a novel micro-planning algorithm was developed for climate-resilient and micronutrient-sensitive vegetable production that generated multiple production plans as per farm properties, crop preferences and consumption patterns of farm households. The algorithm consisted of a cropcombination generator, uncertainty analysis and optimization procedure. The uncertainty analysis incorporated variations in climate, market rates, yields and cost of cultivation. The algorithm was demonstrated using 8 case studies based in India and investigated whether micronutrient diversity, micronutrient density, production diversity and net returns could be improved at the production stage. The results suggested that the generated plans performed better than existing plans for all four parameters in every case study. The improvement in micronutrient diversity, micronutrient density, production diversity and net returns ranged from 5.8 to 60 %, 7.2 to 79 %, 7.8 to 31 % and 5.8 to 60 % respectively. This study provides a simple framework to process large multi-dimensional nutri-economic data to measure essential well-being indices and produces sound food policies at field and regional levels.