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Purpose: The 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/approach: Primary 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. Findings: Dairy 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/implications: Dairy 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 implications: Developing 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/value: This 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. [ABSTRACT FROM AUTHOR]

This document highlights the significance of Body Condition Score (BCS) as a crucial tool for assessing the energy reserves and health of cattle in India's dairy industry, with a specific focus on its application to dairy cows. The BCS is pivotal for guiding feeding strategies, optimizing reproductive performance, and enhancing milk production. The document elaborates on the checkpoints and criteria used for BCS assessment, emphasizing its advantages over other assessment techniques. Additionally, it delves into the optimal BCS ranges for different stages of cows and heifers, illustrating the critical role that BCS plays in cattle health and reproduction. The paper underlines the importance of BCS as a nutritional management tool and discusses the normal changes in desired BCS throughout a production cycle. Finally, the review touches upon management factors that influence BCS and concludes by emphasizing the potential benefits of integrating BCS into dairy herd management practices. [ABSTRACT FROM AUTHOR]

Conventional food supply chains are centralized in nature and possess challenges pertaining to a single point of failure, product irregularities, quality compromises, and loss of data. Numerous cases of food fraud, contamination, and adulteration are daily reported from multiple parts of India, suggesting the absolute need for an upgraded decentralized supply chain model. A country such as India, where its biggest strength is its demographic dividend, cannot afford to malnutrition a large population of its children by allowing them to consume contaminated and adulterated dairy products. In view of the gravity of the situation, we propose a blockchain-enabled supply chain platform for the dairy industry. With respect to the supply chain platform, the dairy products of choice include milk, cheese, and butter. Blockchain is one of the fastest growing technologies having widespread acceptance across multiple industry verticals. Blockchain possesses the power to transform traditional supply chains into decentralized, robust, transparent, tamper proof, and sustainable supply chains. The proposed supply chain platform goes beyond the aspect of food traceability and focuses on maintaining the nutritional values of dairy products, identification of adulteration and contamination in dairy products, the increasing economic viability of running a dairy farm, preventing counterfeit dairy products, and enhancing the revenue of the dairy company. The paper collates the mentioned functionalities into four distinct impact dimensions: social, economic, operations, and sustainability. The proposed blockchain-enabled dairy supply chain platform combines the use of smart contracts, quick response code (QR code) technology, and IoT and has the potential to redefine the dairy supply chains on socio-economic, operational, and sustainability parameters. [ABSTRACT FROM AUTHOR]

Purpose: This paper demonstrates a multi-criteria analytic hierarchy process (AHP) framework for evaluating and benchmarking maintenance performance in the select agro-based industry. Design/methodology/approach: Initially, 20 maintenance practices (criteria) have been identified after a detailed literature review and discussion with the agro-based industry (sugar, textile and dairy industry) executives. These are then grouped into six maintenance management areas referred to as group criteria. The multi-criteria methodology consists of three steps: criteria identification, hierarchical modeling and data collection and maintenance performance evaluation, and benchmarking. The multi-criteria methodology proposed in this work facilitates two ways of carrying out benchmarking: (1) within the agro-based industry and (2) between the agro-based industry. The methodology has been explained by taking a case example of 45 agro-based industries (18 dairy, 13 sugar and 14 textile) from the western region of India. The sensitivity analysis of the model has been performed to ascertain the robustness of the results. Findings: There is a difference in the maintenance performance across the agro-based industries due to different maintenance practices perceived differently. Research limitations/implications: The outcome of the model is mainly given by the judgments of the agro-based industry executives. It is also sensitive to any change in the relative importance to the evaluation criteria or the perception about the maintenance performance. Practical implications: The study contributes in identifying the weakness, if any, by comparing the agro-based industry under investigation with the benchmark factory at three levels, namely, overall performance (factory level), group criteria (maintenance management area level) and criteria (maintenance practice level) allowing further improvement. Originality/value: The methodology assists in better decision-making and in improving maintenance performance. [ABSTRACT FROM AUTHOR]

India is currently ranked as the largest milk producer, dairy industry being the major commodity in agriculture contributing 5% of the national economy, witnessing 6.4% (CAGR) in the past 5 years. Indian dairy industry is expected to grow by 9-11% in financial year 2022. Dairy sector is dominated by fluid milk with emerging value-added products such as cheese, yogurt, flavoured UHT milk growing at a faster rate than other products. Pandemic has affected severely the lives of farmers who depended purely on milk produce by decrease in purchase price, Industries faced challenges to sell and supply milk, worker shortages and increase in production costs, consumers faced challenge to purchase the dairy products and raise in dairy products cost, since lockdown was imposed throughout. The study is viewed in three different dimensions, especially farmers, dairy industries, consumers and the problems faced by them in pandemic situation. The new experience of pandemic also led to shut down of many dairy industries due to lockdown that was imposed on schools, restaurants and hotels. The purposes of this study based on the conceptual data to identify the challenges faced by dairy industry in India during COVID-19 pandemic. The authors in the paper have tried to suggest the best progress that is required to overcome the future pandemic situations for dairy industries. Specifically, data has been collected from the online portals and e-papers to identify and analyse the challenges faced by the dairy industry during pandemic condition. The need of the hour is to also identify the best possible actions that can be taken by dairy industries and government to meet the challenges faced. The government cooperation is required for hand in hand program with dairy industries by planning long term strategies like providing financial reliefs to industries, discounting on taxes and setting up standard MSP (Minimum Support Prices) to farmers and allowing the best possible supply chain to reach customers. The basic challenge in faced to maintain quality and quantity with supply chain being diversified. The dairy product being perishable requires suitable logistics with supply chain operations to ensure the freshness. [ABSTRACT FROM AUTHOR]

The dairy sector has been poised for fierce competitiveness due to the commercialization of the dairy sector and the presence of a global market size of 893 billion dollars. It has received a new dimension with the challenge of environmental sustainability. Considering all these challenges, the present research paper studies the major growth factors and the sustainable approach to dairy development in an emerging economy like India. Fifteen major dairy-developed states of India have contributed 90% of the milk production of the country examined from 2001 to 2019. The significance of key growth factors for dairy farming and the dairy value chain is assessed. The opportunity for sustainable dairying is examined. The authors have found that the growth factors of dairy farming and dairy value chain are significant by 1% through the fixed effect (FE) model and random effect (RE) model respectively. Indian dairy farming practices and their approach create optimism about environmental sustainability. The present study has observed a series of operational activities that are conducive to the triple bottom approach. With that, this study has mentioned strategies that can steer growth momentum and support sustainable Indian dairy development in the coming times. [Display omitted] • Three key areas, namely, dairy farming, dairy value chain and environmentally friendly practices for sustainable dairy development. • Two main types of variables (internal and external growth factors) are involved in the development of the dairy farming. • Strategies are formulated to improve milk productivity. • In line with the triple bottom line approach, a series of operational activities are suggested. [ABSTRACT FROM AUTHOR]

Dairying has played a significant role in providing a livelihood to farmers in India. About 80 million rural Indian households are engaged in milk production with a very high proportion being landless, small and marginal farmers. The study aims to analyse the challenges faced by the dairy industry in generating employment and expanding their business. The paper has taken data from annual survey of industries over 20 years and a case study with a detailed interview of a cooperative society working in the dairy sector. The analysis is based on autoregressive distributed lag model. With the help of analysis, the study found that the dairy industry has the potential to generate employment. During the interaction for the case study, it was observed that firms in the dairy industry undertake the production of value-added products to yield profits which is limited due to low investments. However, the lack of advertisements of these products results in restrained sales and limits income of the farmers. Therefore, the study suggests that the private sector should be encouraged through product link incentive scheme and the government should intervene as a facilitator for their growth and expansion on international levels. [ABSTRACT FROM AUTHOR]

Background: The Indian dairy industry is contributing significantly to the country's economic growth. Since the variations in milk production will be a huge matter for dairy products as well as for farmers, investors and policymakers in the country, an accurate forecast of milk production is extremely very important. Methods: This study represents an ARIMA modelling approach for forecasting the milk production in India and milk production by five major milk producing animal species namely, cow, buffalo, goat, sheep and camel by using annual data from 1961 to 2018. ARIMA (0,2,1) model was selected as the best model in forecasting milk production in India. Result: There will be an increment in the overall milk production in India according to the study. Further, there will be an increase in buffalo, cow and goat milk production while a decrease in milk production by camels and sheep. [ABSTRACT FROM AUTHOR]

India has the largest dairy industry in the world and accounts for a significant share of the global emission of livestock methane ( CH 4 ), a potent greenhouse gas (GHG). While previous works have examined the large-scale livestock CH 4 emissions in India, bottom-up studies are essential to account for the diverse farm conditions and practices across the subcontinent. We developed a Methane Calculator for Indian livestock sector using the Intergovernmental Panel on Climate Change (IPCC) Tier 2 methodology for estimating methane emissions from enteric fermentation and manure management. Using this calculator, we undertook a study of emissions from four dairy farms in the tropical coastal district of Thiruvananthapuram, Kerala, in June 2019. Livestock population and milk production data were collected from the four farms, to compute a mean CH 4 emission of 0.7183 kg CO 2 equivalents/kg of fat and protein corrected milk (kg CO 2 e/kg FPCM), with a notable farm-to-farm variability (63.3%). Having implemented the latest available guidelines outlined by the IPCC, our results are a valuable new addition to the existing body of knowledge in the measurement of dairy farm GHG emissions. We present this as a pilot study, demonstrating a simple method to perform bottom-up investigations of dairy GHG emissions and further formulate policy interventions and mitigation strategies at the farm level. [ABSTRACT FROM AUTHOR]

Background: The study focuses on India’s trade competitiveness in Cheese and Curd (HS 0406)’. It also gives a global overview of the dairy industry. Over the last two decades, the exports of Indian dairy products have increased tremendously. Milk oil products, cheese and curd, as well as milk powder exports, are the key contributions. Although India’s contribution in global dairy exports is modest, milk oil products, as well as cheese and curd, have seen significant growth in the previous two decades. This study analyses the growth in exports of Indian Processed Cheese over the last two decades and examines the competitiveness and comparative analysis of Indian trade in this product. Methods: All the data were collected during 2019-2020. This study is based on secondary data from the ITC Trade Map for the years 2001 through 2020 and the main tools used to analyze the data were the Linear Growth Model, Instability Index, Unit Price Analysis, Protection Coefficient (NPC) and Comparative Analysis (RCA and RSCA). Result: The key findings reflect on the growth, market share, instability, market competitiveness and comparative analysis of the ‘Processed Cheese’ (HS 040630)’. The findings of the studies concluded that the trade of ‘Processed Cheese’ from India has increased significantly over the last two decades, even though its share of Indian exports remains minimal. Over the last two decades, both the volume of trade and the unit price received per unit for ‘Processed Cheese’ has increased significantly. The NPC, RCA and RSCA analysis revealed that the product was neither competitive nor it is showing comparative advantage for most of the period of consideration. [ABSTRACT FROM AUTHOR]