Estimation of bovine equalizing units in India: A regional perspective

PurposeThe purpose of the study is to identify the factors affecting the entrepreneur's choice of the dairy value chain and evaluate the impact of the value chain on farm performance (profit).Design/methodology/approachPrimary data were collected from dairy entrepreneurs in India, covering nine states. A multinomial treatment effect model (controlling for selection bias and endogeneity) was used to evaluate the impact of the choice of the value chain on entrepreneurs' profit.FindingsDairy entrepreneurs operating in any recognized value chain other than the value chain driven by the consumer household realize a comparatively lesser profit. Dairy farmers have established direct linkages with customers in urban areas – who could pay premium prices for safe and quality milk. Food safety compliance is positively associated with profit and entrepreneurs (who have undergone formal training in dairying) preferred partnerships with a formal value chain. The prospects of starting a dairy enterprise are slightly higher in villages compared to urban areas.Research limitations/implicationsDairy entrepreneurs can make a shift in accordance with the study's findings and boost their profitability. It aids in comprehending how trainees (who obtained advice and training for raising dairy animals from R&D organizations) and non-trainee dairy farmers make value chain selections, which ultimately affect profitability. However, purposive sampling and a small sample size limit the universal implications of the study.Social implicationsDeveloping entrepreneurial behavior and startup culture is at the center of policymaking in India. The findings imply that the emerging value chain not only enhances the profit of dairy farmers by resolving consumer concerns about food safety and the quality of milk and milk products but also builds consumer trust.Originality/valueThis paper offers insight into how the benefits of dairy entrepreneurs vary with their participation in the different value chains. The impact of skill development/training programs on value chain selection and farm profitability has not yet been fully understood. Here is an attempt to fill this gap. This paper through light on how trained and educated dairy entrepreneurs are able to establish a territorial market by approaching premium customers – this is an addition to the existing literature.

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“…The animal herd size was standardized by using conversion coefficients of Standard Animal Units (SAU's) (Sirohi et al. , 2015).…”

Section: Methodsmentioning

confidence: 99%

“…The animal herd size was standardized by using conversion coefficients of Standard Animal Units (SAU's) (Sirohi et al, 2015). Further, dairy enterprises were grouped into small, medium and large categories based on SAU's by employing the cumulative square root frequency method.…”

Section: Dairy Value Chain In Indiamentioning

confidence: 99%

Understating emerging value chains and business performance: evidence from dairy industry in India

Dixit

Sirohi²,

Ravishankar³

et al. 2022

JADEE

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“…For the construction of strata, the cumulative cube root frequency method (Singh and Mangat, 1996) [13] and Standard animal unit method (SAU) Sirohi et al (2019) [12] were used.…”

Section: Stratification Of Sample Householdsmentioning

confidence: 99%

“…The total number of milch animals kept by the sample houses during the study period was taken into account. According to Sirohi et al (2019) [12] , the complete herd of cattle on the dairy farm, which consists of adult and young male and female animals, has been transformed into Standard Animal unit (SAU's). SAUs were assigned based upon animal body weight.…”

Section: Analytical Framework Herd Sizementioning

confidence: 99%

“…SAUs were assigned based upon animal body weight. [12] Cube-root cumulative-frequency method In this study, SAUs was used as the covariate for the post stratification process. Dairy farmer households (360) were categorized into three classes, using the cube-root cumulativefrequency method (Singh and Mangat, 1996; Shyamalie, 2008) [13,15] .…”

Section: Analytical Framework Herd Sizementioning

confidence: 99%

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Techno-economical analysis of crossbreed cattle milk production in Western Himalayas of India

Shrama,

Sharif

et al. 2024

Int. J. Res. Agron.

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The study was undertaken to analyse the prospects of crossbreed cattle farming in Himachal Pradesh state India. Himachal Pradesh is a hilly state majorly shadowed with snowfall with predominance of hilly terrain (68.65%) (Anonymous, 2017) [1] . The state is having self sustained balance between supply and demand with structural change i.e., emigrate from traditional farming practices to modern farming practices results in declining of cost of production and hike in profitability and benefit cost ratio. The research has concluded across the three categories such as small, medium and large category of farmers based upon Standard animal unit (SAU). The net return per liter of milk production from crossbred cattle in overall category was Rs 8.59, whereas, at disaggregate level net returns from crossbred cattle were highest for large category farms (Rs 9.70 per liter), followed medium and least for small category farmers i.e., Rs 7.60 and Rs. 6.80 respectively. The cost per liter of milk production was Rs 28.54 for overall category, whereas, and it was least for large category (Rs 27.66 per liter). Among the cost components the total feed cost alone accounted for about 65.67 percent to the gross cost (GC) across the categories. Among feed cost, concentrate constitutes more than 33.50 percent to the GC. The cost of concentrates varied among categories, such as for small category it was 25.50 percent, for medium category 30.24 percent and for large farmers 32.47 percent of the GC. The maximum likelihood estimates for crossbred cattle across the different farm categories. The results clearly indicate that green fodder, dry fodder, concentrate and labour cost are significant at 5 and 10 percent level of significance and positively influences the milk production. However, labour was found negatively associated with milk production in large category. At the disaggregated level, labour coefficient value (-0.34) indicates that 1 percent increase in the labour results in reduction of milk value by 0.34 percent for large category farms which implied excess use of labour. The coefficient of concentrate (0.55) indicates that 1 percent increase in concentrate results in 0.55 percent increase in milk production at 10 percent level of significance. The household size also negatively (0.07) influenced milk production. Green fodder positively influenced milk production as 0.40 percent with 1 percent increase at 10 percent level of significance. However, in small farm category quantity of green fodder, concentrate and labour cost were positively and significantly influenced milk production at 5 percent level of significance. It was found that 1 percent increase in the green fodder, dry fodder and labour cost increased milk production by 0.20, 0.55 and 0.18 percent respectively. In case of medium farms, green fodder, dry fodder and household size were found affecting milk production positively and significantly by 0.19, 0.60 and 0.18 percent respectively.

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Estimation of bovine equalizing units in India: A regional perspective

Cited by 2 publications

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Understating emerging value chains and business performance: evidence from dairy industry in India

Understating emerging value chains and business performance: evidence from dairy industry in India

Techno-economical analysis of crossbreed cattle milk production in Western Himalayas of India

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