Dairy Business Research Articles

Technology of production and primary processing of milk in farm conditions

The introduction of new criteria for the safety of milk raw materials at the legislative level, on the one hand, made it possible to improve the supply of quality food to the population, and on the other hand, caused a decrease in the profitability of farms due to the deterioration of the marketability of milk and its price. Such a situation in the dairy business requires the search for solutions for commodity farms regarding possible ways to improve milk safety indicators as soon as possible in order to avoid a further reduction in the number of dairy cattle in Ukraine. The purpose of the research was to study the technology of obtaining and individual elements of the primary processing of milk for the number of somatic cells and the level of microbial contamination of milk raw materials. The work used general scientific methods, arbitration method, and the method of variational statistics. For this, combined samples of milk from 3 farms that used different approaches to keeping animals and technologies for obtaining milk from them, and a number of personal farms of the population were examined quarterly for one year to study the dynamics and relationships between indicators of raw material safety. A significant influence of paratypic factors on the number of somatic cells in milk was revealed, such as: milk production technology, seasonality of production, and the level of morbidity of animals for hidden forms of mastitis. At the same time, a direct correlation was established between indicators of the number of somatic cells and microbial contamination of milk at the level of 0.91 (P<0.001), which suggests that measures aimed at improving one of them will automatically improve the other. Violations of the requirements of the primary processing of milk caused a significant increase in the microbial load. Elimination of identified technological deficiencies will contribute to the increase of raw materials at milk processing enterprises

Exploitative leadership effect on employee well-being in the Egyptian dairy industry

The purpose of this study is to shed light on how exploitative leadership impacts employee well-being. Studying the effect of exploitative leadership on employee well-being helps researchers and organizations understand the harmful consequences of poor leadership practices on staff members' mental and physical health. The research focuses on the Egyptian dairy industry, which is a substantial contributor to the country's economy. A sample of 353 employees are randomly chosen in Dina Farms and Juhayna owing to their dominance in Egypt's dairy business. Structural Equation Modelling (SEM) is used to investigate the impact of variables on each other. Based on the statistical analysis, exploitative leadership, and employee well-being have a negative significant relationship. Therefore, it is recommended that managers should follow a few approaches to eliminate this type of behavior such as developing clear policies and procedures, encouraging better communications with continuous feedback, and creating a supportive work environment that values the well-being of its employees.

Smallholder milk-quality awareness in Indonesian dairy farms

In most low- and middle-income countries, milk is produced by smallholders, thereby contributing to the livelihood of their households. With the increasing importance of milk production in these countries, it is essential that milk quality is of a high level to ensure a safe product for consumers. It is, however, unclear whether smallholder dairy farmers are aware of the quality of their milk. The aim of this cross-sectional study was to gain insight on Indonesian smallholder dairy farmers' awareness of milk quality parameters and to identify factors associated with the total plate count (TPC) and somatic cell count (SCC). A stratified sampling method was utilized to select smallholder farms in 5 districts in West Java, Indonesia that were interviewed between August and September 2017. Factors putatively associated with awareness of TPC were investigated with multinomial regression models while a Firth-type logistic regression was applied to identify factors associated with SCC awareness. Of the total 600 farmers surveyed, 264 (44%), 109 (18%), 170 (28%), 111 (19%), and 23 (4%) farmers were aware of TPC, total solid (TS), fat content, milk density, and SCC, respectively, but did not know its value. Those that were conceptually aware of these quality parameters were generally unaware of their value. Furthermore, this study revealed that the following variables: cooperative, distance to neighboring dairy farmer, technology adoption index, TPC as the most important quality factors for the buyer, milk production information from cooperatives, and cow's health information from veterinarians were significantly associated with dairy farmers awareness of TPC. Similarly, cooperative, dairy business experience, and milk quality test adoption were significantly associated with dairy farmers' awareness of SCC. Cooperative was the only variable that was significant in both final statistical models. This indicates that cooperatives play an important role in increasing farmers' awareness of milk quality parameters in these smallholder dairies. This may be valid for other regions in the world also where milk production is dominated by smallholder dairy farmers.

Design and Fabrication of Automatic Cattle Feeder System Using IOT

The old-fashioned method of physically feeding cattle takes time. Before feeding the animals along the side of the feed fence, the autonomous cow feeding system employed in this research travels a predefined path for a specified amount of time. The feed mechanism is operated over a predetermined time period by the prototype using an Arduino circuit. Considering that more than 40 percent of total work time is devoted to this activity, feeding constitutes one of the higher expenditures for farm owners in addition to being directly tied to the production of the cattle. Due to the lack of technological utilization, the dairy business has a significant Labor need. These labors are particularly expensive for the owner of the dairy farm since they are only required for 3 hours each morning and three hours in the evening, but they must be paid for the entire day. Hence, an automatic cow feeding equipment has been created to decrease the owner effort and expense. In this research we use two barrels to store the cattle food and a sensor is placed to open the barrel opening to fill the food in the collector in which the cattle eat their food. This process is done for period like morning once and evening once.

Sustainability of Rural Small-Scale Farmers Using a Thematic Content-Fed Analytic Hierarchy Process

Small-scale dairy farming plays a pivotal role in the development of rural economies and has become a key source for job creation and poverty alleviation. However, the survival rate of these enterprises is compromised due to multifaceted challenges. As a result, the newly established or emerging small scale dairy businesses are not sustainable. The objective of this paper is to therefore investigate the determinants affecting sustainability of small-scale dairy enterprises and to develop a framework for failure minimization. The study used purposive snowball sampling techniques to invite small-scale dairy farmers (SSDFs) in Bojanala Platinum District, North West Province, South Africa. The data were analyzed using thematic content analysis (TCA) for factor derivation and ranked using the analytic hierarchy process (AHP). The study revealed the high cost of agricultural inputs, medication and electricity, followed by a lack of agricultural services, and unpredictable weather patterns due to climate change, which were regarded as priority factors proliferating high failure levels and unsustainability by the local farmers. Meanwhile, loadshedding and cattle theft were regarded as low priority factors affecting farming sustainability. The high level of failure in this industry diminishes the chances of farmers to obtain funding or credit; poorer farmers end up falling back into poverty as a consequence of market circumstances beyond their control. The paper concludes that small-scale dairy farming should be revised as part of a broader livelihood strategy by all stakeholders, while continuously pursuing alternative access points to achieve prosperous rural livelihoods, local market information and access, and risk optimization. With the prospects of future climate, geopolitical and environmental crisis, considering how local small-scale dairy farmers (SSDFs) react and use information technology is vital to their sustainability and providing policy relevant knowledge. Furthermore, the SSDFs should be exposed to agricultural funders in their localities, and also access to agricultural sector training authority (AGRISETA) services should be made available for local farmers to receive training for proposal writing to apply for funds.

Determinants of profitability of dairy farming enterprises among smallholder dairy farmers in south-west Nigeria

Dairy farming is essential to most developing economies, including Nigeria, due to its contribution to livelihoods in terms of food supply, income and employment generation. This study examines the determinants of profitability of dairy business among smallholder dairy farmers in Nigeria. Data were collected from 150 dairy farmers selected through a multistage sampling procedure and analyzed using descriptive statistics and the ordinary least square (OLS) regression method. The majority of the dairy farmers had primary education (45.45%). Most were married (92.91%), while many were economically active (60.67%). Most (50%) of the respondents had 7 household members and above and the majority (76.67%) had 20 years of experience in dairy farming. Age, vocational education, other forms of education, herd size and total production cost significantly influence the profitability of the dairy business. Major constraints include insufficient forage access, low-quality fodder and lack of credit. Feed technology training, health care management and dairy cooperatives are strongly advocated. Dairy cooperatives are also important for better bargaining in input delivery and better prices for output supply to the market. It will also enable the farmers to pull resources together and guarantee access to benefits like soft loans, literacy programmes, and social protection, among others.

Sustainable Performance Assessment towards Sustainable Consumption and Production: Evidence from the Indian Dairy Industry

The current global economic status quo is widely seen as unsustainable in the food sector. The field of sustainability science is still rather fragmented, covering a wide range of techniques and issues, despite the large number of publications in this area. Due to population growth, the food supply chain (FSC) and farmers have to produce more food. The UN estimates that one-third of edible food is wasted, producing greenhouse gases. A balance must be struck between company operations and social, environmental, and economic activities for sustainable development of the FSC. To assist FSC organizations in managing sustainable advancement, this study created a methodology for the assessment of sustainable performance. We provide a sustainable assessment system using a fuzzy analytic hierarchy process, fuzzy VIKOR, and fuzzy TOPSIS. Our research framework evaluated the sustainability of three cooperative-society-run Indian dairy firms. Our study gives environmental criteria the highest weight (0.33) and social criteria the lowest (0.16), with economic reasons (0.306) and business operations (0.204) falling in the middle. Supply chain costs, on average, are given the highest weight, and capacity utilization, the lowest weight. Three dairy industries are ranked (DPI3, DPI1, and DPI2) based on sustainable performance. By modifying the maximum set utility value and validating VIKOR results with TOPSIS, we have checked the robustness of this performance assessment tool. This research aids dairy businesses in achieving several Sustainable Development Goals, including sustainable production and consumption, through the regular assessment of their sustainable performance.

Modeling and Forecasting of Milk Production in the Western Zone of Tamil Nadu

Background: In India, the dairy business is expanding dramatically. Tamil Nadu milk cooperatives significantly contribute to the growth of the dairy sector in the state. In terms of delivering economic income for dairy smallholders and satisfying customer demand, the identification of milk production is one of the primary financial operations made in India. Considering this, it is crucial to understand future production to enhance and sustain the sector’s growth and development. Methods: The present investigation attempts to predict and forecast milk production in Tamil Nadu using time series models. Yearly milk data from 1976 to 2020 was taken. The study considered Auto-Regressive Integrated Moving Average (ARIMA) and Artificial Neural Network (ANN) to select the appropriate stochastic model for forecasting milk production in Tamil Nadu. Further statistical modeling procedures employed for milk production reveal that the selection of a suitable time series model will always depend on the nature of the data. Result: Results revealed that the ARIMA model is selected as the best model despite ANN, even if it is considered the most powerful model. The CAGR for forecasted milk production from 2020-2025 was 0.02%. Model adequacy criteria like RMSE, MAPE and MAE are used. Based on observation ARIMA model (1, 1, 2) is chosen as the best model over the ANN model.

Modeling the challenges of technology adoption in dairy farming

Purpose 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. Design/methodology/approach 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. Findings 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. Research limitations/implications 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. Practical implications 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. Social implications 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. Originality/value To the best of the authors’ knowledge, this study is purely original and outcome of the research conducted by authors.

Predictable inventory management within dairy supply chain operations

PurposeWith 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 managementDesign/methodology/approachPreferred 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.FindingsAs 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.Practical implicationsMany 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.Originality/valueThis 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.

Exploring farm level response to multiple drivers of change, a West Coast case study.

Developing resilient, profitable, and robust dairy farm businesses in response to multiple drivers of change (e.g., water quality regulations, a low carbon economy) is challenging. This study explored methods for working with dairy farmers and stakeholders from the West Coast of New Zealand to evaluate options for system change. Physical, financial, and environmental data from the study farms were analysed and benchmarked to provide farmers with information on how their financial and environmental performance compared with others. The most profitable farm had the lowest purchased nitrogen (N) surplus. However, high pasture production and utilisation resulted in higher methane emissions for this farm. FARMAX and OVERSEER models were used to apply principles of the top performing farm to two selected study farms.These study farms largely succeeded in reducing N surplus and methane emissions, but operating profit was reduced, suggesting a complete system rethink is needed including focusing on growing and harvesting more home-grown feed with less N input, and scrutiny of farm working expenses. This study showed that benchmarking, farmer participation and modelling has the potential to create a positive environment thatmotivates farmers to review their current performance, extract solutions from their local peers and partner with researchers.

Cовременные проблемы и актуальные подходы в молочном животноводстве

Purpose. An overview of the main modern problems in the dairy business and an assessment of promising approaches to the development of this branch of animal husbandry based on the research of the staff of the VRIMMP. Materials and Methods. The scientific research was carried out through the use of generally accepted scientific methods of studying and processing the studied material in the form of sequential operations of generalization, systematization, logical analysis and conclusions on an extensive array of data from the materials of published works on numerous scientific and practical studies carried out in the agroecological conditions of the South of Russia. Discussion. The existing knowledge has been deepened and the obtained results of the lifetime formation of increased both quantitative and qualitative characteristics of dairy raw materials, and as a result, dairy products of increased nutritional value obtained from it, are reflected. The main technological innovations that have begun to be applied by advanced enterprises of the dairy industry are considered: robotic milking, software for automating routine tasks in animal maintenance. Conclusion. Currently, extensive scientific work has been carried out, the results of which are the key points for solving the most important tasks to improve the quality and volume of production of dairy raw materials and final products from it. The proposed approaches for enterprises engaged in the breeding of dairy cattle in the field of productivity, with proper implementation, are able to bring production indicators to a new level. The developed new approaches to the production of dairy products will allow milk processing enterprises to expand the product range of eco-friendly and healthy products.

Effects of grazing management and concentrate supplementation on intake and milk production of dairy cows grazing orchardgrass

In pasture-based dairy systems, grazing management strategies have focused mainly on achieving a high herbage harvest per hectare, whereas strategies oriented to maximizing the intake rate of herbage have been recently explored. The objectives of the study were (i) to evaluate the herbage nutritional value, intake and milk production per animal and per hectare of mid-lactation Holstein dairy cows grazing orchardgrass (Dactylis glomerata) in response to grazing management strategies that prioritize either herbage harvest per hectare or herbage intake rate, and (ii) to assess whether concentrate supplementation affects this response. The experiment was conducted in Uruguay using twenty-four mid-lactation Holstein dairy cows grazing orchardgrass under rotational stocking over an 81-day period. The experimental design was a randomized complete block with a 2 × 2 factorial arrangement consisting of two grazing management strategies [i.e. “high intake rate” (HIR) with pre- and post-grazing sward target heights of 21 and 13 cm, respectively, vs. “high herbage harvest per hectare” (HHH) with a pre-grazing target of 3.5–4 leaves per tiller and a post-grazing target of minimum leaf area corresponding to sward heights between 7 and 11 cm] in combination with concentrate supplementation levels of 0 (CS0) or 4 (CS4) kg of dry matter/cow per day. Sward height, number of leaves, herbage morphological and chemical composition, body weight (BW), body condition score (BCS), feed intake, and milk production per cow and per hectare were measured. Statistical analyses were performed using linear mixed models. Compared to cows under HHH, cows under HIR grazed herbage with greater nutritional value and achieved a greater feed intake and greater milk production per cow (P < 0.05), regardless of concentrate supplementation level. Conversely, under HHH milk production per hectare was marginally greater (P < 0.10) and milk solids production per hectare was greater (P < 0.05). Yet, cows under HHH lost BCS when were managed without supplementation (P < 0.05). In conclusion, HIR grazing management is an effective option for grazing dairy production systems that seek to maximize individual productivity of high-producing cows. On the other hand, HHH grazing strategies remain relevant to dairy farm businesses in which profit is driven by production per hectare. Yet, high producing dairy cows under this strategy are likely to lose BCS if not supplemented.

The Development of Dairy Business Enterprise: A review

The Development of Dairy Business Enterprise: A review

An update on prevention and control of livestock diseases in India

Millions of farmers keep livestock for the purpose of milk production, and every year a wide variety of diseases, some of which can be fatal, cause illness in these animals. Even cattle and buffalo that have a significant threat of disease transmission. They are among the most susceptible people to the introduction of zoonotic diseases into the human population. Milk is in danger of running out in the not too distant future since both consumer demand and the dairy business are both on the rise. Dairy products are progressively used in more and more foods. Farmers take a financial hit each year as a result of illnesses that affect milking dairy animals; the scale of these losses can approach millions of dollars at the national level. At both the state and the national level, there needs to be a diseases control policy in order to put a stop to the losses. In addition to this, the tight interaction that exists between humans and the animals that they have domesticated presents the highest risk of the spread of a range of infectious diseases. The state animal department and the government of India need to conduct an active review of the situation across the state because the number of households that have milk animals has increased. They should also give the process of establishing new rules and putting them into practice the utmost significance, both with the purpose of strengthening the regulation of diseases that are prevalent among the population and with the purpose of reducing the risk of zoonotic transmission. The purpose of this review is to identify and put into effect those measures that will contribute significantly to the eradication of the cattle illnesses that are most prevalent. In this review, we provide a summary of the most prevalent livestock diseases, probable zoonotic diseases, and developing diseases, as well as present and potential regulations that ought to be put into place.

Determining Point of Economic Cattle Milk Production through Machine Learning and Evolutionary Algorithm for Enhancing Food Security

Artificial neural networks (ANNs) in conjugation with genetic algorithms (GAs) have been demonstrated to be an effective tool for system modelling and optimization in a variety of applications. The current communique is about assessing the capacity of ANN to predict investment on cattle till age at first calving (AFC) and milk production based on the data of 340 Vrindavani crossbreed cattle developed at the ICAR-Indian Veterinary Research Institute in Izatnagar, India. Three distinct artificial neural network (ANN) algorithms, namely, Levenberg–Marquardt (LM), Bayesian regularization (BR), and gradient descent momentum with adaptive learning rate backpropagation (GDX) were used to train the ANN infrastructure for determining milk production and investment based on body weight and AFC as input variables. The results showed that BR with 2 hidden layer neurons showed excellent prediction ability (R2 = 0.999, MSE &lt; 10−6) and was therefore used as an objective function by GA for optimization. The optimized results revealed that higher milk production is achievable at lower investment if the age at first calving is 768 days with a body weight of ∼281 kg. The information generated by this investigation will aid in ensuring food security in terms of higher milk production while making the dairy business more sustainable and profitable for the farmers.

Diversifikasi Olahan Susu Sapi Segar Menjadi Produk Kefir untuk Minuman Probiotik dan Masker Wajah di Kelurahan Plalangan Gunungpati Semarang

Plalangan Village is one of the villages that produce fresh cow's milk in the administrative area of Gunungpati District, Semarang City, Central Java Province. The average daily activity of residents of Terwidi Village RT02 RW04, Plalangan Village, Gunungpati District, Semarang City in particular is raising cattle. The number of cattle breeders is 40 people who are members of the Ngudi Rahayu Terwidi Dairy Cattle Group (KTSP). The current number of cows is 75 heads, much lower than 5 years ago. The decline in the number of cows is due to the fact that they think that a dairy business that only relies on dairy products does not provide a steady income. Even though there is a lot of potential that can be developed from the dairy cattle business, including the diversification of dairy products. Kefir is a heterofermentative fermented product that has a taste, color and texture that resembles yogurt and has a distinctive aroma like tape. Kefir products circulating in the community today are not only consumed as probiotic drinks but can also be used as cosmetic products, such as masks. The main program will be carried out by the Community Service (PKM) team by empowering dairy cattle businesses through diversification of fresh cow's milk products to become high-value products, namely kefir which can be used as probiotic drinks and face masks.

A Review on a Milk Quality Detection and Analysis

The milk is the important nutrition for mortal being. The good quality milk should be free from the pollutants. Milk is substantially vended by original merchandisers as well as by super requests. still, in original areas to increase the volume of milk certain pollutants are added which may affect the nutritive quality of milk. Milk contamination is a social problem. The problem of contamination is faced by both Indian and foreign countries. Application of thinned milk causes severe health problems and a great concern to the food assiduity. The Country milk directors and consumers facing problem to find the quality of milk, accept the show of price and consumption. So, it's necessary to insure the quality of milk by measuring the vital parameters present in the milk and the pollutants that are added to the milk. Then we're measuring the different parameters of milk similar as pH, turbidity, conductivity, odor, temperature using detectors. Also, with the help of IOT( Internet of effects) process the milk assiduity should be suitable to shoot the real time reading information of milk to the government so that it helps to overcome the illegal effects similar as milk quality during the product of milk packet. This proposed system is enforced using At mega328 microcontroller. All the detectors arecombined to form compact and flexible system which dissect and classify the quality of milk into different grades and eventually affair displayed on TV screen. Problem faced in small journals and by the individualities can be averted by detecting the quality of milk, and help from causing the dangerous conditions by detecting the contamination of milk. husbandry is an important part of India and the dairy business is an overall benefit to India's business or frugality. Farmers force milk to dairy products and admit payments grounded on the chastity of the milk. As it's known, the world is moving presto now that people with further luxurious cultures are responding to trends and requirements. thus, there's a need to ameliorate the agrarian life of India. In milk, colorful factors are calculated, similar as fat, pH, and the asked rate of fat mass. The system calculates these parameters and the microcontroller reads the data and sends to android phone. The Blynk app installed on the phone can be used to perform billing computations and calculate the diurnal payments. This technology offers a clever mobile operation that help in determining the quantum of fat in milk. Both Arduino boards and microcontrollers may use the detector. The fashion for relating fat in milk samples is veritably affordable. The sector offers fair rates to growers and gives governments with real- time dairy value andproportions through the Internet of effects(IoT) procedure.

Operational Efficiency through Disruptive Innovation in Dairy Business: Evidence from an Emerging Economy

Operational Efficiency through Disruptive Innovation in Dairy Business: Evidence from an Emerging Economy

Entrepreneurial behaviour of dairy farmers under Dairy Business School model

Entrepreneurship has become the need of the hour with good potential to improve livelihood and generate employment. Most of the small and marginal farmers are dependent on dairy farming and there is a need to enhance the income of the farmers as per government priority to double their income. Hence entrepreneurship development in production, processing, and marketing is essential. So with the aim to inculcate entrepreneurial behaviour among dairy farmers, the Dairy Business School (DBS) was set up on an experimental basis at NDRI, Karnal a premier institute working on Dairy. The present study was conducted in 12 villages in six adjoining districts of NDRI, Karnal. An action research design was used with a sample size of 180 farmers during 2021-22. The data were collected through a pre-tested interview schedule by holding the personal interview. The results of the study revealed that the majority (61.11 %) of the farmers had a medium level of entrepreneurial behaviour. All the thirteen components of entrepreneurial behaviour like risk taking, hope of success, persistence, feedback usage, self confidence, knowledgeability, persuasability, manageability, innovativeness, achievement motivation, decision making ability, cosmopoliteness and profit orientation were at a medium level among dairy farmers. Knowledgeability was ranked first which contributed most to the entrepreneurial behavior of farmers while decision making ability at last.