Determination of optimal cropping plan for dryland agrosilvipastoral systems in western Tamil Nadu

Abstract

Indian rainfed agriculture is highly vulnerable to climate change and other factors, including topography, land size, and soil management practices. Consequently, optimizing cropping patterns is crucial for enhancing resilience and profitability. The study employed the MOTAD model to explore alternative cropping strategies for crop-livestock dryland farms under varying climatic risks. The research focused on western Tamil Nadu, a drought-prone region in south India’s rain-shadow zone, where agrosilvipastoral systems incorporating Cenchrus ciliaris grass and Acacia spp trees support livestock rearing. Based on a survey of 180 farmers, a representative six-hectare farm was optimized across different risk levels. The results revealed that under optimal cropping patterns, high-risk farms have a maximum of 60% area allotted to silvipasture, about 26% for profitable black gram, and only 9 and 6% to the sorghum and horse gram, respectively. This strategic land allocation adjustment significantly improves farmers’ net returns compared to existing practices, offering insights into risk-informed farm planning for enhanced sustainability.