Constraints faced by dairy farmers in adoption of nutritional technologies in the indo-Pak border region of Punjab

Introduction

India became the world's leading milk producer in 1998, surpassing the United States of America and has continued to be the largest producer of milk since then. India contributes nearly 25% of global milk production (Kona et al., 2025) [14] . The livestock sector contributes 5.2% to the GDP of the nation and the dairy sector contributes nearly 66.56% to the livestock sector. Since independence, the livestock sector has remained an integral part of the rural economy. The dairy sector provides regular cash income, nutritional security and employment to farm households. At the national level, 65 to 70% of these households are characterised as landless, marginal and small farmers (Sarkar et al., 2024) [26] . It also plays an important role in women's empowerment as women constitute approximately 70% of the workforce engaged in the livestock sector (Shilpa Shree and Prabu, 2019) [28] . Success in dairy production depends on feeding, housing, breeding and management practices. Among these factors, nutrition plays a pivotal role in determining the production, reproductive performance and health of dairy animals as well as contributing to environmental sustainability (Kavithaa et al., 2020) [13] . Adequate provision of green fodder can contribute to improved milk production in dairy animals (Mishra et al., 2024) [19] . Improved nutritional practices also have the potential to substantially reduce enteric methane emissions from livestock with reductions of up to 60% under certain nutritional interventions (Hristov, 2024) [8] . Supplementation with bypass fat and bypass protein has been reported to improve milk yield, nutrient utilisation and immune function (Ganai et al., 2019) [7] . Similarly, adequate supplementation of vitamins and minerals can have significant positive effects on immunity, reproduction and production performance (Ahmad et al., 2022) [2] . Despite the potential benefits of improved nutritional technologies, their adoption among dairy farmers may remain limited. Non-adoption of improved nutritional technologies and continued reliance on traditional practices may result in reduced productivity and lower economic returns from dairy production (Kaur & Toor, 2022) [12] . Non-adoption of such technologies may be attributed to a range of factors that act as constraints to their adoption. Constraints in the adoption of nutritional technologies may include non-availability of feed, purchasing power limitations, inadequate economic returns, knowledge gaps, poor infrastructure and other technical and institutional factors as reported by various studies (Adhikari et al., 2020) [1] . The dairy sector across the states of India has not developed uniformly over time. States such as Punjab, Kerala, Haryana, Goa and Gujarat are categorised as progressive dairy states (Kale et al., 2016) [9] . The dairy sector of Punjab is among the most advanced in terms of technology and genetic potential. Punjab not only ranks first in per capita milk availability but also contributes approximately 6.7% of the total milk production of India while accounting for only 2.53% of the country's dairy animals (Kaur et al., 2022) [11] . However, the level of dairy production and modernisation is not uniform across all districts of Punjab. Border regions of developing countries face greater challenges related to infrastructure, accessibility and availability of institutional and technical services compared with mainland regions. Punjab has six districts sharing an international border with Pakistan and Fazilka is one of these border districts (Singh et al., 2022) [30] . However, limited literature is available regarding the constraints faced by dairy farmers in the adoption of improved nutritional technologies and practices in Fazilka district. Therefore, the present study was undertaken to assess the constraints faced by dairy farmers in the adoption of improved nutritional technologies in the border region of Fazilka district. The findings of the study may provide useful insights for extension agencies and policymakers in developing appropriate interventions to address the constraints faced by dairy farmers in the region.

Materials and Methods

The study was conducted in the border region of Fazilka district, Punjab, to explore the constraints faced by dairy farmers in the adoption of nutritional technologies. The study was carried out from April to June, 2026. Fazilka district was selected because of the limited literature available on the constraints associated with the adoption of nutritional technologies among dairy farmers in this region. Furthermore, the area falling within a 10-km belt along the Indo-Pakistan border was purposively selected, as, to the best of our knowledge, limited studies have previously examined the constraints associated with the adoption of nutritional technologies among dairy farmers in this specific region. Five villages namely Bandiwala, Sabuana, Shatirwala, Siwana and Tilanwali, falling within the border belt were randomly selected for the study. 20 respondents from each village were selected randomly, with the inclusion criterion that each respondent owned at least one cattle or buffalo. Thus, a total of 100 respondents were selected. Socio-economic characteristics of the respondents were also recorded. A list of possible constraints affecting the adoption of improved nutritional technologies was prepared based on a review of relevant literature and the objectives of the study. The identified constraints were classified into six major technology-specific categories, namely green fodder, silage, self-prepared concentrate, commercial concentrate, feed additives and supplements, and feed testing. Data were collected from the selected dairy farmers using a pre-tested, structured interview schedule.

For each nutritional technology, respondents were presented with the relevant list of possible constraints and were asked to indicate whether they perceived each constraint as a valid barrier to its adoption. For each constraint, responses were recorded dichotomously as 'Yes' or 'No'. The frequency of respondents reporting a particular constraint was calculated within each technology category. The constraints were then ranked in descending order of frequency, with the constraint reported by the highest proportion of respondents receiving Rank I, followed by subsequent ranks (Karthikeyan et al., 2018) [10] . The frequency and corresponding percentage of respondents reporting each constraint were calculated and the results were systematically compiled and presented in tabular form.

Results and Discussion

Socio-economic characteristics

The socio-economic characteristics as well as dairy Farming profile of the respondents from the study are summarised in table 1. Among the respondents, 96% were male and 4% were female. These findings were in contrast to Tudu and Roy (2015) [31] where they found that majority (61.2%) of the respondents were female. Regarding age, 30% of the respondents were below 30 years of age, 25% belonged to the 31-40 years age group, and the remaining 45% were above 40 years of age. In another study by Mahesh et al.

(2020) [17] 63% of the respondents belonged to middle age category of age 36-45. In terms of educational qualification, 9% of the respondents were illiterate, while 36%, 31% and 24% had education up to high school(10th), higher secondary(12th) and graduation or above respectively. These finds were same as found by Devansh et al. (2023) [6] were majority (64.67%) of the respondents studied up to the high school. With respect to landholding, 12% of the respondents were landless, whereas 64%, 18%, and 6% belonged to the small, medium and large landholding categories respectively. Crop farming was the major source of income for most of the respondents, while 5% reported dairy farming as their primary source of income. Dairy and crop farming contributed equally to the income of 18% of the respondents, whereas 11% were primarily engaged in other income-generating activities. Out of the 100 respondents, 18% had received formal training related to livestock production, while the remaining 82% had not received any formal livestock-related training. In the study by Devansh et al. (2023) [6] only 30% of the respondents received training about livestock.

Dairy Farming Profile of the Respondents

Regarding livestock composition, 49% of the respondents reared only cows, 11% reared only buffaloes and 40% reared both cows and buffaloes. These were in line with the study conducted by Kumar et al. (2020) [15] where only buffalo rearing farmers were 36.80%, only cow rearing were 53.90% and those who reared both were only 9.30% of the total. In terms of herd size, 50% of the respondents maintained herds of fewer than five animals, while 39% and 7% maintained herds of 5-10 and 11-15 animals respectively. Only 4% of the respondents maintained herds comprising more than 15 animals. It has been estimated that nearly 75 million farmers in India rear less than 5 milk animals each (Kona et al., 2025) [14] . With regard to total milk production, 25% of the respondents reported milk production of less than 10 L/day, whereas 31%, 18% and 7% reported production levels of 10-20, 21-30 and 31-40 L/day respectively. A comparatively higher level of milk production, more than 40 L/day, was reported by 19% of the respondents. Regarding the constraints in adoption of green fodder (Table 2), it was observed that the majority (84%) of the respondents reported year-round unavailability of fodder as the main constraint in adoption of green fodder. Same was reported by Adhikari et al. (2020) [1] , where 100% of respondents reported non-availability of green fodder throughout the year. Transportation constraints were ranked at last (6 th ) as a constraint in adoption of green fodder as reported by 4% of the respondents only. Limited availability of grazing land, limited land for fodder cultivation and labour scarcity were ranked at 2 nd , 3 rd and 4 th rank as reported by 50%, 40% and 32% of the respondents respectively. In a study by Pawar et al. (2019) [23] , 82.50% respondents mentioned non-availability of land for cultivation of fodder crops as a constraint in adoption of green fodder. Lack of grazing land was reported as constraint by 59% of the respondents in a study by Singh et al. (2017) [29] . Inadequate knowledge for fodder production was reported as constraint by 63.33% respondents in a study conducted by Patel and Sabapara (2023) [21] . In the adoption of silage feeding (Table 3), inadequate training on silage preparation was ranked at first position as it was perceived as constraint by 74% of the respondents. These findings were in line with findings of Sabapara and Fulsoundar (2015) [25] , where 64% respondents lacked knowledge on silage preparation. Insufficient herd size and high cost of preparation were the next at 2 nd and 3 rd rank as reported by 63% and 53% of the respondents as constraint in adoption silage feeding. In a study by Reiber et al. (2010) [24] , more than 30% of medium farmers perceived silage as expensive. Following constraints were limited machinery, limited land and fear of spoilage. Nearly 40% of the respondents dependent on loaned equipment for silage making in a study by Bernardes and do Rêgo (2014) [3] . Limited availability of quality seed was the least (1%) reported constraint and hence ranked last at 9 th place. Constraints like labour scarcity and inadequate storage infrastructure was mentioned by 23% and 13% of the total respondents, hence ranked at 7 th and 8 th place respectively. [20] , high cost of ingredients was ranked as first constraint as reported by 62.5% of the respondents. Only 12% and 8% of the respondents reported limited availability of raw material and limited access to feed mills as constraints, making them to rank last in the list. Non-availability of machines and lack of technical guidance was reported by 95.3 and 69.3% of the respondents (Chavan, 2015) [4] . [18] , where 80% of the respondents reported high cost of commercial concentrate as constraint in its adoption. Adulteration concerns and low economic return was perceived as constraint by 68% and 28% of the respondents gaining it 2 nd and 3 rd rank. Adulteration as constraint was ranked 12 th among 15 constraints in adoption of concentrate feeding in a study by Kumar et al. (2014) [16] .

Difficulty in brand selection and low effectiveness ranked 4 th and 5 th respectively as they were reported as constraints by 23% and 19% of the respondents. Inadequate awareness was not perceived as constraint by most of the respondents but by 3% only, gaining it the last rank at 6 th in the list.

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