Sustainability Assessment of Farming in Northeast India Using PSR Model

Abstract

Agricultural sustainability in India’s North Eastern Region (NER) is challenging due to mounting environmental degradation, socio-economic inequalities, and institutional gaps. The region faces challenges such as land degradation, limited irrigation, and inadequate rural infrastructure despite its rich agroecological diversity and traditional practices. This study assesses the sustainability of agriculture in the eight Northeastern states using the Pressure-State-Response (PSR) model to generate a composite Agricultural Sustainability Index (ASI). A total of 16 indicators across environmental, economic, and social dimensions are selected. These indicators are normalized using the Min-Max method, and objective weights are assigned using the entropy method. The PSR framework was applied to analyze human-induced pressures, the current state of resources, and institutional responses across the states. Findings show significant spatial disparities. Tripura ranks highest in sustainability (ASI = 0.543), owing to better productivity, irrigation, and strong social indicators. Assam (ASI = 0.481) and Meghalaya (ASI = 0.430) follow, while Nagaland (ASI = 0.278) and Sikkim (ASI = 0.313) perform poorly due to ecological stress, low economic security, and weak institutional support. There is a trade-off between environmental conservation and increasing agricultural output. This requires socially inclusive and flexible policies without affecting the local realities of NER. Originality/Value: This study advances a standard PSR application through implementation-level rigor and decision relevance. First, the study provides a fully auditable indicator pipeline—explicit selection rules, polarity checks, and PSR tagging—so readers can reproduce each step. Second, the study report formal robustness of the composite to common researcher degrees of freedom (normalization, outlier handling, imputation, and weighting choices), described transparently in Methods, with qualitative results summarized in the text. Third, the study benchmarks entropy-weighted results against a simple equal-weights baseline to demonstrate that headline findings are not an artifact of a single weighting scheme. Finally, the study translates the composite into policy guidance by identifying the most influential indicators behind each state’s position and explaining why those levers matter in context. These elements yield context-sensitive insights without introducing new data or exotic methods.