Assessment of the sustainability of multipliers as the core of the region's agroeconomic system

This article examines the role of multipliers – subsectors of agriculture, as the core of the agroeconomic system of any region, using the example of the Ural Federal Okrug, and also evaluates their sustainability based on materials from 2010-2015. Three basic subsectors are analyzed as multipliers: grain production, dairy farming and poultry farming. As a result of the author's calculations using the appropriate methods, a conclusion was drawn about the dependence of the basic industries on each other, as well as on the market model in a particular territory.

The impact of education and experience on profit of smallholder dairy farming at Batu City of Malang Raya, Indonesia

The research was conducted at Batu, City, Malang Raya of Indonesia. Study addressed to examine the farmer characteristics, dairy farming income, and the factors influencing on profit. The case study applied multistage sampling method to select 34 representative farmers which divided into three strata namely, stratum-1 (rearing <4 Animal Units), stratum-2 (owning 4-8 AU), and stratum-3 (controlling >8 AU). Primary data collection used survey method with structured questionnaire, whereas secondary data were available in related institutions and sources. Data analysis implemented descriptive and multiple regression technique. Results confirmed that farmers has experienced about 6-10 years in raising dairy farming and they has secondary school education. The profitable dairy farming was smallholder dairy farming that rearing more than 8 AU with daily income per Animal Unit of IDR 64,554 and structured with IDR 11,131 of revenue and IDR 47,577 of production cost. Farmer’s experience was positively explaining the smallholder dairy profit, and the high school education attainment was more likely to increase venture’s income. The farm return has positive and strong relationships with the more number of dairy cattle owned.

Factors Affecting Machinations at Dairy Farms : An Appraisal from Economic Perspective

This study was undertaken to get a comprehensive idea about the favourable and unfavourable factors for adoption of dairy automation/ machinations as perceived by dairy farmers, and study the economic impact of semi-automatic milking machine for small, medium and large dairy unit using the analysis of total cost and monetary benefits. The study was carried out in north Indian states, 30 commercial dairy farmers were selected constituting a total of 150 respondents practicing commercial dairy farming under survey method of investigation. Results revealed that time saving in dairy farm operations, drudgery reduction, and maintenance of hygiene and quality of milk and milk products were perceived as top three favourable factors for adoption of dairy automation or machination. The high initial investment required for dairy automation, no extra milk price for hygiene and quality products through the adoption of dairy automation in the market, and high cost of equipment and less subsidy provided by the government were perceived as top three favourable factors for adoption of dairy automation or machination. The study indicated that adoption score of the respondents were not significantly correlated with age. It implies that age, education, family size land holding and experiences of dairy farming does not affect the adoption of dairy automation technologies. The additional monetary benefits apart from this economic benefit’s other benefits such as clean and hygiene milk, health care and management in economic terms were calculated about 43800, 39,600, and 64,000 per year for small, medium, and large dairy unit, respectively

Over 20 Years of Machine Learning Applications on Dairy Farms: A Comprehensive Mapping Study

Machine learning applications are becoming more ubiquitous in dairy farming decision support applications in areas such as feeding, animal husbandry, healthcare, animal behavior, milking and resource management. Thus, the objective of this mapping study was to collate and assess studies published in journals and conference proceedings between 1999 and 2021, which applied machine learning algorithms to dairy farming-related problems to identify trends in the geographical origins of data, as well as the algorithms, features and evaluation metrics and methods used. This mapping study was carried out in line with PRISMA guidelines, with six pre-defined research questions (RQ) and a broad and unbiased search strategy that explored five databases. In total, 129 publications passed the pre-defined selection criteria, from which relevant data required to answer each RQ were extracted and analyzed. This study found that Europe (43% of studies) produced the largest number of publications (RQ1), while the largest number of articles were published in the Computers and Electronics in Agriculture journal (21%) (RQ2). The largest number of studies addressed problems related to the physiology and health of dairy cows (32%) (RQ3), while the most frequently employed feature data were derived from sensors (48%) (RQ4). The largest number of studies employed tree-based algorithms (54%) (RQ5), while RMSE (56%) (regression) and accuracy (77%) (classification) were the most frequently employed metrics used, and hold-out cross-validation (39%) was the most frequently employed evaluation method (RQ6). Since 2018, there has been more than a sevenfold increase in the number of studies that focused on the physiology and health of dairy cows, compared to almost a threefold increase in the overall number of publications, suggesting an increased focus on this subdomain. In addition, a fivefold increase in the number of publications that employed neural network algorithms was identified since 2018, in comparison to a threefold increase in the use of both tree-based algorithms and statistical regression algorithms, suggesting an increasing utilization of neural network-based algorithms.

Dairy Farming Innovations for Productivity Enhancement

Dairy farming innovations’ implementation at every farmer’s farm is the present day need; during the era of scarce natural resources coupled with population explosion, putting obvious pressure for more food production. Milk, produced from every single farm at micro level, is contributing to global economy at macro level. Dairy sector is facing the challenge of low animal productivity due to ineffective and poor farm management. This provides a big window for different innovations application to enhance animal productivity in developing nations where majority dairy farms are small scale and managed on traditional practices. Farm innovations are the novel practices/products/techniques suitable for particular area, physiological stage of animals and economically viable option to enhance the animals’ per diem yield. Despite the prevalence of innovations, the scenario for its applicability is very dismal, majority of them are yet to reach masses at root level. Farmers’ demographic, social and economic characteristics including adoption behavior, act as major impeding factors affecting impact of innovations. In this chapter, information on low cost and user friendly dairy farming innovations suitable for all kinds of farms, maintained under rural conditions existing in different tropical countries have been detailed for enhancing the animal productivity and henceforth farmers’ socio-economic welfare.

Smallholder Dairy Farmers' Livelihoods: Opportunities and Challenges in Metta Robi Woreda, West Shewa Zone, Oromia Regional State, Ethiopia

In today's world, small-scale dairy farming has become commonplace. Farmers in Ethiopia, particularly in rural areas, have used it to supplement their income and ensure food security. This study aimed to assess the opportunities and challenges for the livelihoods of smallholder dairy farmers in Metta Robi woreda. A mixed research method was applied, with descriptive and cross-sectional research designs. A total of 372 SDFs (households) who performed dairy farming in the research area were selected using a systematic sampling technique. In addition, three kebeles in Metta Robi woreda were randomly picked from a total of 23 kebeles. The questionnaire was used to obtain quantitative data, while in-depth interviews, key informant interviews, and personal observation were employed to collect qualitative data. The quantitative data were analyzed using descriptive and inferential statistics, which were performed using SPSS Version 21. On the other hand, the qualitative data were transcribed and analyzed thematically. The findings showed that households in the study area engaged in a variety of livelihood activities. For more than half of the sampled households, on-farm activities are their primary source of income. The data also revealed that the study area's opportunities included appropriate environmental conditions, availability of land and water, market and road, social networks, access to information, crop residue availability, and credit service. However, land-use change, market fluctuations and inaccessibility, a lack of labor and sufficient competence, a lack of infrastructure, livestock diseases, and a scarcity of feed and water were mentioned as issues that affected SDFs' livelihoods. It was suggested that the government pay special attention to the challenges that affect SDFs' livelihoods in general and the study area in particular.

INFLUENCE OF DIFFERENT AGES HEIFERS LIVE WEIGHT ON THE LIFELONG COWS PRODUCTIVITY

One of the problems of modern dairy farming is the short period of productive use of cows. This is observed not only in Ukraine, but also in most countries of the world with developed dairy farming. The consequence of a short period of productive use is a decrease in lifelong productivity of cows. The aim of this paper was to study the possibility of influencing the duration of use and lifelong yield of cows by selecting heifers for live weight during their rearing. The study analyzed the lifelong productivity of 1071 cows of the Ukrainian black-spotted dairy breed, starting from their breeding and before leaving the herd. Animals were divided into five groups by living weight at the age of 3, 6, 12 and 15 months using a standard deviation (σ) from the mean value. The number of calving, the duration of productive life, lifelong yield and yield for higher lactation, as well as the average period between calving were determined within the groups. It was found that yield for higher lactation are associated with the weight of heifers during the beginning of pubertal development and the onset of sexual maturity. Animals that had a live weight of + 0.5…1.5 σ at the age of 6 months and more than +1.5 σ at the age of 12 months from the average live weight in the herd were characterized by the highest milk yield. The group of signs of lifelong productivity (number of calving, duration of productive use and lifelong yield) was positively affected by live weight of heifers aged 3, 6, 12 and 15 months, which exceeded the average live weight in the herd by 0.5…1.5 σ. Cows included in these groups outperformed other groups by 0.2…1.4 calving. During the period of use, these cows received 11…32% more milk than the herd average. The research expands the understanding of the influence of heifer breeding on the formation of lifelong productivity of cows and can be used to select livestock and adjust plans for dairy cattle breeding.