Optimum Designing and Field Validation of a Multi-Objective Integrated Farming System in Indian North-Western Himalayas

Multi-criteria decision making (MCDM) technique – compromise programming – was utilized to optimize an integrated farming system (IFS) operated by a representative small sized farm of Indian north-western mid-Himalayas (INWH). The optimization was undertaken to provide a better alternative for formulation of an IFS individually for such variable sized farms that are the majority, especially in INWH, as compared to non-mathematical fixed farm-size simulations that have been adopted in India, which follow a one-size-fits-all approach. The optimal IFS aimed to maximize farm income and food energy while minimizing soil loss – conflicting decision criteria chosen and prioritized by the farmer within constraints such as production input-output ratios, available resources, and preferences for local production to meet family needs. Optimization of selected farmers' IFS revealed potential to achieve better values of their farming attributes, more so revealed by its on-field implementation. Implementation of the formulated IFS plan, comprising crop cultivation and animal husbandry components, on the farm continuously for three years could achieve higher average farm income of >10% and food energy production of >1% compared to potential of 10.9% and 0.4% as per the optimal IFS plan, respectively. The success of the implemented IFS model based on the formulated index indicated that it has at least 67% probability of achieving its potential. Formulating farmer-specific IFS with MCDM, considering local needs and traits, helps small farms identify the best options across criteria, enabling them to move beyond subsistence and failure-prone farming.