From Farm-level Tools to State-level Assessment: A Scoping Review of Dairy Sustainability Indicators

Swati Singh

Division of Dairy Economics, Statistics and Management, ICAR-National Dairy Research Institute, Karnal 132001, Haryana, India.

Subhasis Mandal *

Division of Dairy Economics, Statistics and Management, ICAR-National Dairy Research Institute, Karnal 132001, Haryana, India.

Ajmer Singh

ICAR-Indian Institute of Soil and Water Conservation, Research Centre, Chandigarh 160019, India.

Gunjan Bhandari

Division of Dairy Economics, Statistics and Management, ICAR-National Dairy Research Institute, Karnal 132001, Haryana, India.

Kaushik Khamrui

Division of Dairy Technology, ICAR-National Dairy Research Institute, Karnal 132001, Haryana, India.

Sanchita Garai

Division of Dairy Extension, ICAR-National Dairy Research Institute, Karnal 132001, Haryana, India.

Vikas Vohra

Division of Animal Genetics and Breeding, ICAR-National Dairy Research Institute, Karnal 132001, Haryana, India.

*Author to whom correspondence should be addressed.


Abstract

Dairy production is expected to deliver nutritious food, rural livelihoods and export earnings while reducing greenhouse gas emissions, nutrient losses and pressures on land, water, biodiversity and animal welfare. Indicators are the principal means by which these expectations are translated into measurable performance, yet they are developed for different purposes and at different scales, from on-farm diagnostic tools to sector inventories and jurisdiction-wide composite indices. This critical narrative review, conducted with a scoping purpose, maps how dairy sustainability indicators are constructed, applied and aggregated across the farm, supply-chain, regional and state or national levels, and evaluates whether information generated at one level can legitimately inform decisions at another. Peer-reviewed studies, methodological reviews and authoritative institutional sources were identified through multidisciplinary, agricultural, economic and regional scholarly indexes, supplemented by citation tracking, and were appraised qualitatively for relevance, transparency, representativeness and robustness. The synthesis shows that farm-level tools differ widely in normative framing, indicator logic, scoring and aggregation, so that tools applied to the same farms can produce divergent judgements. Environmental indicators are the most mature, but carbon footprints remain sensitive to allocation rules, emission-factor tiers and functional units, and intensity metrics often move in the opposite direction to absolute emissions that matter for state targets. Economic indicators are comparatively well supported by accountancy data, whereas social and animal-welfare indicators remain under-specified and are frequently lost or distorted during aggregation. State-level assessments follow four broad routes: weighting representative farm samples, top-down inventories, modelled regional typologies and composite indices built from administrative statistics. Each route carries characteristic risks, including unrepresentative sampling, spatial misallocation, leakage through imported feed and weighting choices that can reorder jurisdictions. Smallholder and mixed crop–livestock systems, which dominate milk supply in several countries, are poorly served by tools designed for specialised temperate farms. A nested indicator architecture, built on a verifiable core of farm data, explicit scaling rules and paired intensity and absolute metrics, is proposed as a defensible direction. Its validity remains to be demonstrated through longitudinal and cross-jurisdictional testing.

Keywords: Sustainability assessment, indicator aggregation, life cycle assessment, farm accountancy data, greenhouse gas inventory, composite index, animal welfare, smallholder dairy


How to Cite

Singh, Swati, Subhasis Mandal, Ajmer Singh, Gunjan Bhandari, Kaushik Khamrui, Sanchita Garai, and Vikas Vohra. 2026. “From Farm-Level Tools to State-Level Assessment: A Scoping Review of Dairy Sustainability Indicators”. Journal of Scientific Research and Reports 32 (11):824-53. https://doi.org/10.9734/jsrr/2026/v32i114705.

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