Economic viability analysis of dairy farming in Muzaffarnagar district of Uttar Pradesh

Introduction

Dairy farming has emerged as one of the most critical allied sectors of agriculture in India, contributing significantly to food security, sustainable rural livelihoods, and the overall macroeconomic trajectory. Approximately 25 percent of global milk production, India reinforces its status as the world's leading producer, where animal husbandry functions as an essential livelihood buffer for over 80 million rural households (DAHD, 2024) [2] . The sector is uniquely inclusive, providing regular cash flows and vital protein nutrition to smallholder, landless, and marginal farmers who manage a majority of the national livestock inventory (NDDB, 2020) [11] . Beyond economic insulation, women assume a leading role in livestock management, rendering dairy a central instrument for gender equality and financial inclusion in rural communities. (Kumar et al., 2020) [8] . Despite its structural magnitude, the Indian dairy industry presents a paradox of aggregate dominance coupled with relatively low animal-level productivity. The average annual milk yield per cow in India remains at approximately 1,770 kg, significantly below the global average benchmark of 3,000 kg and drastically trailing highly industrialized, mechanized systems like the United States at 10,500 kg (FAO, 2023) [3] . This productivity gap is exacerbated by feed price inflation, inadequate formalized cold-chain infrastructures, veterinary constraints, and high ambient temperatures causing severe climatic heat stress. Given these micro-level challenges, regional and district-specific costreturn analyses are crucial to formulate effective agricultural policies. (Garg and Singh, 2020; Joshi et al., 2022) [5,6] . The state of Uttar Pradesh represents India's primary 'Dairy Powerhouse,' consistently leading nationwide production by contributing over 15 percent of the country's aggregate output, which translated into 36.54 million metric tonnes during 2022-23 (DAHD, 2023) [1] . Within this state landscape, Muzaffarnagar district in Western Uttar Pradesh a highly vibrant agro-dairy framework. Strategically positioned within the Indo-Gangetic plain, the district has an economy where sugarcane by-products (molasses, tops, bagasse) are recycled directly as cattle feed, reducing overall costs by up to 25 percent during the crushing season (Kumar and Sharma, 2021) [7] . The local producers face immense pressures from concentrate feed price volatility and market price fluctuations. Grounded in this context, the primary objective of this paper is to rigorously evaluate the cost structure and net returns of milk production for independent cow and buffalo sub-enterprises across different farm sizes in Muzaffarnagar district.

Materials and Methods

A multistage purposive and random sampling technique was utilized to execute a systematic primary socio-economic field survey. In the first stage, Muzaffarnagar district was purposively selected. In the second stage, two blocks as Khatauli and Jansath were purposively selected based on elevated animal populations and intensive rural participation. In the third stage, two villages from each block (Thisang and Ahemadgarh in Jansath; Sikandarpur and Tighai in Khatauli) were randomly selected. In the final sampling stage, 20 dairy farmers were randomly drawn from each village in probability proportion to their size, for a total sample size of 80 respondents. Sample households were stratified into three functional production tiers based on their milch animal herd size as small farmers (1-3 milch animals; n=47), Medium farmers (4-6 milch animals; n=21), and large farmers (more than 6 milch animals; n=12). Primary data encompassing capital assets, daily variable feed allocations, veterinary costs, hired and family labour inputs, milk yields, and disposal parameters were gathered through a pre-tested structured interview schedule. Analytical tools involved comprehensive accounting frameworks. (Meena et al., 2011) [9] Total expenditure was decomposed into fixed costs (depreciation on buildings, implements, and milch stock; interest on fixed capital) and variable costs (green fodder, dry fodder, concentrate feeds, mineral supplements, medicine, and human labour values). Hired labour was accrued at prevailing market wage rates, while family labour was imputed. (Mkuna, 2026) [10] .

Total cost = Depreciation on all fixed investments + interest on fixed capital + variable cost of different items + interest on working capital

Gross Returns

Gross returns were calculated from the value of milk, dung, calves, and appreciation in the value of cattle.

Gross Returns = Value of milk + Value of dung + Value of calves + Cattle appreciation

Net Returns

Net returns were calculated by deducting total cultivation costs from gross returns.

Net Income = Gross returns -Total cost

Results and Discussion Livestock structure of sample dairy farmers

In Table-1 small dairy farmers, 87.32 percent of cows and 74.42 percent of buffaloes were in milk, with female calves accounting for 8.45 percent and 18.60 percent, respectively. No heifers were reported. In the medium category, 74.24 percent of cows and 65.22 percent of buffaloes were in milk. The livestock also included 2 non-pregnant heifers, 1 male calf and 12 female calves. In large farmers, 64.71 percent of cows and 61.54 percent of buffaloes were in milk. Heifers accounted for 9.41 percent, while female calves formed 18.82 percent of the cow population. Three female buffalo calves were also reported. Overall, milch animals formed the major share of livestock across all categories. The proportion of cows and buffaloes in milk declined with increasing farm size, while female calves were more numerous than male calves.

Cost and returns of milch buffalo milk production

Similarly, Table-4 presents the cost and profitability of milch buffaloes across different categories of dairy farmers. The overall daily expenditure was Rs. 5,000.60, mainly comprising green fodder (29.42%), concentrate (21.21%), dry fodder (8.81%) and labour (13.23%). After deducting the value of dung, the net cost was Rs. 4,939.68 per day. Buffalo milk production averaged 102.39 litres/day, with a production cost of Rs. 48.06 per litre and a selling price of Rs.60.00 per litre. Category-wise, expenditure was highest among small farmers (Rs. 7,927.39), followed by medium (Rs. 4,677.54) www.extensionjournal.com and large farmers (Rs. 2,396.88). Small farmers recorded the highest milk production (161.25 litres/day), followed by medium (96.32 litres) and large farmers (49.61 litres). However, the cost of production per litre declined with farm size, from Rs. 48.78 for small farmers to Rs. 47.87 for medium and Rs. 47.52 for large farmers. Consequently, profit per litre was highest among large farmers (Rs. 12.48), followed by medium (Rs. 12.13) and small farmers (Rs. 11.22), indicating economies of scale in buffalo milk production.

Conclusion

The study concludes that dairy farming is an economically viable component of farm livelihoods in Muzaffarnagar district, with feed costs constituting the major share of total expenditure. Large dairy farmers achieved higher milk productivity, lower per-litre production costs and greater profit margins for both cows and buffaloes compared with small and medium farmers. The results indicate the presence of economies of scale, as expansion in herd size was associated with improved cost efficiency and profitability. However, the absence of expenditure on livestock insurance and the relatively low veterinary expenditure indicate gaps in access to formal dairy services. Strengthening veterinary facilities, promoting livestock insurance, improving access to quality feed and increasing awareness of government dairy schemes can help enhance productivity and income, particularly among small and medium dairy farmers.

Acknowledgement

AcknowledgementThe authors gratefully acknowledge the dairy farmers of Khatauli and Jansath blocks, Muzaffarnagar district, for their willing participation in the survey. The authors also express their sincere gratitude to the Department of Agricultural Economics, Sardar Vallabhbhai Patel University of Agriculture and Technology, Meerut, for providing institutional support and extending the necessary guidance and facilities during the course of the study.

References

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