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This study examined the effects of adopting dairy feed technology bundles on the milk production of smallholder dairy farmers.

The study was based on Multinomial Endogenous Switching Regression (MESR) to estimate the effects of the adoption of three feed technology bundles on milk production using data collected from 518 dairy farm households in West Java, Indonesia.

The findings indicated that adopting technology bundles had positive and robust effects on milk production, with gradual positive effects between non-adoption and the adoption of different bundles of technologies.

This study focused on the association between the adoption of feed technology bundles and milk production. However, further analysis of the causal links between the adoption of feed technologies and milk production as well as the inclusion of other outcomes in the analysis, such as production costs and risk mitigation, are required.

Most of the literature on agricultural technology adoption focuses on the adoption of individual technologies, crop farming and conservation practices. Therefore, this study examined the effects of the adoption of dairy feed technology bundles.

The presence of heavy metals in milk causes many acute and chronic physiological dysfunctions in human organs. The present study aims to investigate the heavy metals in cow's and buffalo's milk of two major cities, Karachi and Gujranwala, Pakistan to estimate metal intake by humans from this source.

In total, 48 milk samples from 2 cities were drawn from animals' udder to avoid contamination. Each sample was digested with nitric acid at 105 ^oC (degree Celsius) on a pre-heated electric hot plate to investigate the metals by atomic absorption spectroscopy (flame type). Air-acetylene technique analyzed chromium, cadmium and lead, and the hydride method analyzed arsenic in the milk samples.

The results revealed the highest mean lead concentration (19.65 ± 43.86 ppb) in the milk samples, followed by chromium (2.10 ± 2.33 ppb) and arsenic (0.48 ± 0.73 ppb). Cadmium was not detected in any sample, assuming cadmium's occurrence was below the detection level. The concentrations of all the metals in the samples of the two cities do not differ statistically. Lead concentrations in the buffalo's milk were higher than in cow's milk (p < 0.05). However, the concentrations of arsenic and chromium between buffalo's and cow's milk do not differ statistically. The present study reveals a lower level of metals in the milk than those conducted elsewhere. The mean concentrations of all the metals met the World Health Organization's (WHO) safety guidelines (1993).

Although cadmium causes toxicity in the human body, cadmium could not be measured because cadmium's concentration was below the detection level, which is 1 ppb.

This study will help reduce the toxic metals in our environment, and the sources of heavy metals, particularly from the industrial sector could be identified. The feed and water consumed by the milking animals could be carefully used for feeding them.

This study will help reduce the diseases and malfunction of human organs and organ systems since these heavy metals cause toxicity and carcinogenicity in humans. Arsenic and chromium cause cancer while lead causes encephalopathy (a brain disease).

The study reports heavy metal concentrations in the two attributes of four independent variables of raw milk samples that were scarcely reported from Pakistan.

This article examines the dairy value chain in Southern Peru and identifies four critical success factors that can enhance the local situation.

The study employed descriptive research using semi-structured interviews with entrepreneurs from 17 cheese factories across eight districts, namely Azángaro, Ayaviri, Pucara, Lampa, Cabana, Acora, Pomata and Puno. Quantitative market data were also gathered and analyzed alongside qualitative views.

The study identified four critical issues: quality concerns in milk production, suboptimal managerial practices of cheese-processing plants, lack of compliance to regulations, particularly hygiene and environmental ones, and inadequate access to finance. The findings reveal a gap between the practices of the Puno region's dairy industry and world-class standards for cheese production. Urgent actions are required to improve product quality, increase access to finance, enhance managerial education and ensure compliance with regulations.

Results suggest critical issues to be prioritized, but the article does not propose how to solve the problems identified. External factors, such as economic changes, were also not considered. Interviews were conducted exclusively with cheese processing entrepreneurs, not milk producers.

This case study provides an insight into the interior of Peru, an under-researched region facing several development challenges. The findings have significant implications for dairy value chain stakeholders in Peru and other similar contexts.

The global research evidences indicate that the technology adoption in case of agribusiness has a potential to enhance the performance and bring operational efficiency. India is the world’s largest producer as well as consumer of milk but struggles with yield per cattle, overall productivity, low rate of technology acceptance and adoption, health detection of milching units, animal data recording and presence of dairy products in the global market. The purpose of this study is to focus on identifying the challenges of technology adoption in dairy farms and constructing a hierarchical model using soft systems methodology.

This study uses nominal group technique-based discussion with domain experts and personal interviews with dairy farm owners/managers for the identification of challenges, fuzzy interpretative structural modeling as well as FMICMAC to develop a hierarchical model of challenging elements and to divide the identified elements into four categories based on the dominance of driving-dependence power.

This research has developed a list of 12 challenges affecting the technology adoption in a dairy farm business unit, identified through the personal interviews with 60 dairy farms across three highest milk-producing states of India in terms of annual milk output – Haryana, Punjab and Uttar Pradesh. Lack of government support followed by lack of educational opportunities in dairy-based education were found as the most crucial and high driving challenges, whereas high cost, huge investment and low acceptance of decision-maker were found as the most dependent challenges of technology adoption.

This research is one step ahead of interpretive structural modeling that considers the fuzzy-based dominance in the model to showcase the degree of relationship along with its existence, but it lacks to statistically validate the findings using techniques like SEM.

This paper has developed a list of challenges in adoption of technology along with their inter-relationships to highlight the required focus challenge that drives or is dependent on the other challenges. The goal is to bring performance improvement and assist Indian dairy farm business stakeholders or decision-makers in formulating strategic and action plans and help policy planners to make favorable policies based on the understanding of contextual relationship between challenges.

In Indian context, dairy is an important part of agriculture sector, and milk is an essential item that facilitates income generation to small and rural households and a source item for several other businesses and activities. The results of this research suggested the policy planners and government to ensure subsidized and insured technologies, training support and facilities, educational opportunities and efforts for promotion of technology adoption among dairy farmers. The suggestions are purely on the basis of the relevance of challenges in the hierarchy and can play a significant role in improving the level of technology adoption and can ultimately uplift the social and economic well-being from micro-level of farmers to macro-stage concerning economic development of India.

To the best of the authors’ knowledge, this study is purely original and outcome of the research conducted by authors.

The global outbreak of COVID-19 and its subsequent varied impacts on different economic activities necessitate to examine its disruptions and impacts on livestock sector in India due to its recently surging potential as an unrivaled alternative to boost farmer’s income.

The studies for review were identified through search in different databases using relevant keywords. Only full text papers written in English language were reviewed. The review was organized and streamlined using Covidence software.

Analysis of the literature reveals adverse effects of COVID-19 on functioning of input and output stages of livestock supply chains. This has resulted in upstream and downstream economic losses that affect livelihoods of the producers.

Scale of unprecedented crisis due to COVID-19 pandemic requires creative policy decisions to make livestock production systems robust, resilient and sustainable. Organized production systems are required to integrate with livestock-tech startups to modernize their supply chains, whereas local supply chains are required to reorient with government’s intervention in terms of developing on-farm production and postproduction processing facilities.

Although there exist some evidence on COVID-19-related impacts on livestock sector of India, but an integrated review of evidence on COVID-19 related disruptions at all the stages (from input supply to marketing) of livestock supply chains was missing.

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).

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.

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.

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.

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.

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.

The purpose of this paper is to gain insight into how management accountants can become relevant business partners out of respect for existing locally developed accounts of economic performance for decision-making.

The paper is based on qualitative semi-structured interviews with local business actors, in this case, families from seven financially successful Danish dairy farms. The casework and the analysis have been informed by pragmatic constructivism.

The local business actors do not use the official accounting system for ongoing cost-management-related decision-making. Instead, they use several epistemic methods that include locally developed decision models, experiences, rules of thumb and intuition. The farmers use these vernacular accountings to compensate for the cost management illusion that the formal accounting system tends to create. What the study suggests is that when management accountants engage as business partners, they are likely to enter a space where accounting is already present.

This paper argues that local business actors practice epistemic methods where they develop and use vernacular accountings to support their managerial practice, also in the absence of a professional management accountant. These vernacular accountings may lead the local actors into an illusion because the vernacular accountings do not necessarily have an inherent economic logic and theoretical reliability. The role of the management accountant in such a setting is hence to understand, support and advance local epistemic methods. Becoming a business partner requires a combination of management accounting analytical skills and a sense of empathy and sensitivity regarding what is already at play and how this can become an object of discussion without violating the values of the other.

This paper examines the impact of the COVID-19 pandemic on low-carbon consumption of dairy products through informational interventions. The empirical findings seek to enlighten developing countries' efforts in coping with climate change and potential dietary transitions.

A randomized controlled trial was designed to examine the effects of purpose-differentiated information interventions on individual dairy consumption. The experiment recruited and randomly assigned 1,002 college students into four groups to receive (or not) environmental or/and health information interventions.

The empirical analysis finds that health and combined information interventions have a positive impact on dairy consumption, while environmental information interventions' effect on dairy consumption is insignificant. In the context of the pandemic, health information interventions positively affected participants' perceptions and preferences for dairy products by delivering knowledge about their role in boosting immunity. However, environmental information interventions failed to do the same things as their insignificant effects on both perception and preference.

Macro-external shocks, such as public health events, may offset the impact of universal information interventions promoting pro-environmental behaviors. For a smooth dietary transition to achieve long-term environmental sustainability, diverse stakeholders must be included in more individualized interventions to guide daily consumption, especially in developing countries with large populations.

With the current wave of modernization in the dairy industry, the global dairy market has seen significant shifts. Making the most of inventory planning, machine learning (ML) maximizes the movement of commodities from one site to another. By facilitating waste reduction and quality improvement across numerous components, it reduces operational expenses. The focus of this study was to analyze existing dairy supply chain (DSC) optimization strategies and to look for ways in which DSC could be further improved. This study tends to enhance the operational excellence and continuous improvements of optimization strategies for DSC management

Preferred reporting items for systematic reviews and meta-analyses (PRISMA) standards for systematic reviews are served as inspiration for the study's methodology. The accepted protocol for reporting evidence in systematic reviews and meta-analyses is PRISMA. Health sciences associations and publications support the standards. For this study, the authors relied on descriptive statistics.

As a result of this modernization initiative, dairy sector has been able to boost operational efficiency by using cutting-edge optimization strategies. Historically, DSC researchers have relied on mathematical modeling tools, but recently authors have started using artificial intelligence (AI) and ML-based approaches. While mathematical modeling-based methods are still most often used, AI/ML-based methods are quickly becoming the preferred method. During the transit phase, cloud computing, shared databases and software actually transmit data to distributors, logistics companies and retailers. The company has developed comprehensive deployment, distribution and storage space selection methods as well as a supply chain road map.

Many sorts of environmental degradation, including large emissions of greenhouse gases that fuel climate change, are caused by the dairy industry. The industry not only harms the environment, but it also causes a great deal of animal suffering. Smaller farms struggle to make milk at the low prices that large farms, which are frequently supported by subsidies and other financial incentives, set.

This paper addresses a need in the dairy business by giving a primer on optimization methods and outlining how farmers and distributors may increase the efficiency of dairy processing facilities. The majority of the studies just briefly mentioned supply chain optimization.

Globally, consumer’s inclination towards functional foods had noticed due to their greater health consciousness coupled with enhanced health-care cost. The fact that probiotics could promote a healthier gut microbiome led projection of probiotic foods as functional foods and had emerged as an important dietary strategy for improved human health. It had established that ice cream was a better carrier for probiotics than fermented milked due to greater stability of probiotics in ice cream matrix. Global demand for ice cream boomed and probiotic ice cream could have been one of the most demanded functional foods. The purpose of this paper was to review the technological aspects and factors affecting probiotic viability and to standardize methodology to produce functional probiotic ice cream.

Attempt was made to search the literature (review and researched papers) to identify diverse factors affecting the probiotic viability and major technological challenge faced during formulation of probiotic ice cream. Keywords used for data searched included dairy-based functional foods, ice cream variants, probiotic ice cream, factors affecting probiotic viability and health benefits of probiotic ice cream.

Retention of probiotic viability at a level of >10⁶ cfu/ml is a prerequisite for functional probiotic ice creams. Functional probiotic ice cream could have been produced with the modification of basic mix and modulating technological parameters during processing and freezing. Functionality can be further enhanced with the inclusion of certain nutraceutical components such as prebiotics, antioxidant, phenolic compounds and dietary fibres. Based upon reviewed literature, suggested method for the manufacture of functional probiotic ice cream involved freezing of a probiotic ice cream mix obtained by blending 10% probiotic fermented milk with 90% non-fermented plain ice cream mix for higher probiotic viability. Probiotic ice cream with functional features, comparable with traditional ice cream in terms of technological and sensory properties could be produced and can crop up as a novel functional food.

Probiotic ice cream with functional features may attract food manufacturers to cater health-conscious consumers.