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Journal articles on the topic 'Dairy farming'

Author: Grafiati

Published: 4 June 2021

Last updated: 29 July 2024

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1

Vaghamashi, G., G. P. Sabapara, D. D. Garg, H. H. Savsani, M. R. Chavda, A. Chavda, N. K. Ribadiya, V. K. Karangiya, and R. B. Makwana. "Precision Dairy Farming: The New Era in Dairy Farming." International Journal of Current Microbiology and Applied Sciences 11, no. 5 (May 10, 2022): 20–28. http://dx.doi.org/10.20546/ijcmas.2022.1105.004.

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India has world’s largest livestock population and 1st rank in milk production with 187 million tons in 2018-19. Dairy farming is the single largest contributors to Indian GDP with 5.1 % in 2018-19 and annual growth rate in Livestock sector is 4.6%. Indian dairy production is characterized as a low input/low output system. In general, milk productivity of dairy animals is very low in comparison to global standards. The lower milk yield is mainly due to low genetic potential, lack of nutritional feeds and inadequate veterinary services. So, with suitable and scientific approach production efficiency can raise. In this context, Precision dairy farming (PDF) aims to improve individual animal performance, well being and socio-economic status of dairy farmer. Today, traditional dairy farming becomes organized commercial business with technological specializations in every part of the process. Thus, farmers are shifting towards adopting modern dairy farming practices for increase their production. PDF is the use of information and technology based farm management system to record physiological, behavioral and production parameters of individual animals to improve management strategies, profitability and production performance. There are so many important precision dairy farming technologies available globally, which are routinely useful for large and commercial dairy farm. In this direction, the authors have also highlighted the status of adoption in Indian scenario, benefits, challenges and limitations of precision dairy farming technologies. Many developing countries including India are in initial stage in these advance technology, but there are tremendous opportunities for betterment of animal and upliftment of animal husbandry profession.

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2

Sirdeshpande, Mitali, Sofiya Shikalgar, Vijeta Vipin, and V. K. Bairagi. "Dairy Farming System." International Journal of Computer Sciences and Engineering 7, no. 5 (May 31, 2019): 631–35. http://dx.doi.org/10.26438/ijcse/v7i5.631635.

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3

Measures, Mark. "Organic dairy farming." International Journal of Dairy Technology 44, no. 2 (May 1991): 54–56. http://dx.doi.org/10.1111/j.1471-0307.1991.tb00635.x.

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4

Tutkun, Muhittin. "PRECISION DAIRY FARMING." Journal of Agricultural, Food and Environmental Sciences 77, no. 1 (2023): 12–19. http://dx.doi.org/10.55302/jafes23771012t.

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5

Bobade, MD, VN Khune, Sharad Mishra, Ashutosh Dubey, Aayush Yadav, Anupam Soni, Sudheer Bhagat, Subhrajit Das, and Kundan Krishnan. "New age dairy farming: Precision dairy farming (PDF): A review." International Journal of Chemical Studies 8, no. 1 (January 1, 2020): 1041–46. http://dx.doi.org/10.22271/chemi.2020.v8.i1n.8386.

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6

Deshevykh, A. A., O. I. Skobel, V. I. Glazko, and G. Y. Kosovsky. "PROFITABILITY IN DAIRY FARMING." Russian Journal of Agricultural and Socio-Economic Sciences 54, no. 6 (June 25, 2016): 39–51. http://dx.doi.org/10.18551/rjoas.2016-06.06.

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7

Amey, Gene. "Dairy Farming in Europe." British Food Journal 89, no. 5 (May 1987): 106–7. http://dx.doi.org/10.1108/eb011795.

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8

Kaur, Dr Rupender, and Dr Rajendra Rathore. "Knowledge of Women Regarding Dairy Farming Practices." International Journal of Scientific Research 3, no. 1 (June 1, 2012): 197–98. http://dx.doi.org/10.15373/22778179/jan2014/63.

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9

Radun, Viktor, Dragan Dokić, and Vesna Gantner. "Implementing artificial intelligence as a part of precision dairy farming for enabling sustainable dairy farming." Ekonomika poljoprivrede 68, no. 4 (2021): 869–80. http://dx.doi.org/10.5937/ekopolj2104869r.

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The purpose of this paper is to consider implementation of Artificial Intelligence as a part of Precision Dairy Farming, as a way of processing, analyzing and managing Big data, in order to enable sustainable dairy cattle farm. Increasing the volume of livestock production in the future and measuring the level of environmental impact becomes one of the most pressing concerns. The aim is to evaluate the impact of animal's production level on the ammonium pollution from dairy cattle farm using precision dairy farming technologies. The results indicate significant variability in estimated ammonium pollution from dairy cattle farms due to the animal's production indicating positive correlation between daily milk production and ammonium pollution. The test day records, as Artificial Intelligence application in precision dairy farming could be used both for assessing the ammonium pollution from farms and timely prevention and correction of inadequate management towards sustainable dairy production systems.

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10

Shanthi Kuchibhatla, Muskan Banu, Shaista Taskeen, Shama begum, Samreen Sultana, and Geethanjali Karli. "Dairy Farming – a Case Study." International Research Journal on Advanced Engineering and Management (IRJAEM) 2, no. 01 (January 31, 2024): 16–19. http://dx.doi.org/10.47392/irjaem.2024.0004.i1.

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Dairy farming is an important discipline of agriculture aimed for production of milk and dairy products. India, being a predominantly agrarian economy, has about, 70% of its population living in villages, where Dairy farming play a crucial rule in the socio-economic life. India is not only one of the top producers of milk in the world, but also the largest consumer of milk and milk products in the world. Dairy sector is instrumental in bringing, socio-economic transformation in India. There exists a great need to enlighten and make the society aware of various opportunities and challenges in the dairy farming. In this context, we have visited SAARA DIARY FARM - situated at Nampally, Hyderabad to observe and understand the daily operations of a functioning dairy farm. The farm houses a total of 40 Cows yielding 3 quintal of milk per day. After the distribution of milk, the remaining was used to prepare dairy products like curd, cheese, butter, ghee etc. The visit to a dairy farm provided us with firsthand experience of dairy farming operations, caring for cows, milking processing and the milk processing. This experience has contributed to personal and professional development and enlightened us with potential career opportunities in the agricultural sector. However, the low productivity per animal and availability and affordability of the quality feed and fodder remains to be the major challenges. In these circumstances, Government should take initiative to promote the dairy farming as major industry to meet the global demand.

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11

Rossing, W., P. H. Hogewerf, A. H. Ipema, C. C. Ketelaar-De Lauwere, and C. J. A. M. De Koning. "Robotic milking in dairy farming." Netherlands Journal of Agricultural Science 45, no. 1 (July 1, 1997): 15–31. http://dx.doi.org/10.18174/njas.v45i1.523.

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The role of engineering research in the development of robotic milking systems and the integration of robotic milking in dairy farms are reviewed. The milking stall, robot arm, teat sensing system, milking equipment and udder cleaning devices of commercial automatic milking systems (AMS) available in the Netherlands at the end of 1996 are described. The importance of the attractiveness of the milking stall, lay-out of the barn and the introduction of a cow routing with special gates in the barn is highlighted. Increasing the milking frequency from 2 to 3 times/day results in a higher yield of approximately 1000 kg milk/lactation. It is concluded that automatic milking will decrease the physical and mental load on the farmer, but it should be considered that the farmer is working with complicated equipment.

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12

Malla, Yam. "Dairy Farming in Mountain Areas." Mountain Research and Development 27, no. 3 (August 1, 2007): 291. http://dx.doi.org/10.1659/mrd.mm018.

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13

Swai, Emmanuel S., and Esron D. Karimuribo. "Smallholder Dairy Farming in Tanzania." Outlook on Agriculture 40, no. 1 (March 2011): 21–27. http://dx.doi.org/10.5367/oa.2011.0034.

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14

Watanabe, Motoi. "Dairy Farming in New Zealand." Journal of Rural Problems 23, no. 1 (1987): 46–53. http://dx.doi.org/10.7310/arfe1965.23.46.

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15

Jovanovic, Miomir, Bogdan Bulatovic, and Aleksandra Despotovic. "Dairy farming: Integration into Europe." Biotehnologija u stocarstvu 21, no. 1-2 (2005): 123–32. http://dx.doi.org/10.2298/bah0502123j.

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Because of the increasing trend in globalization in dairy farming resulting in joining and taking over some companies with the aim of rationalization of production and realizing greater market participation, it seems quite real to expect such a trend to appear in our country as well. After the process of privatization had been realized a significant part of Montenegrin economy fell into the hands of private owners. In such conditions it can be expected that efficiency and competitiveness of some producers of milk and dairy products in the Republic of Montenegro will be increased, since in previous period this industry was characterized by insufficient exploitation of already existing capacities for milk processing while the quality of milk was considerably under the standards prescribed by the European Union. Depending on the dynamics of entering Montenegro into international economy the national dairy industry must be ready to face the challenge which will certainly be imposed on it. The object of this paper was to try to find the answers to the two questions. First where we are now and where we will be in the next five years in order to improve the competitive potential of domestic dairy farming.

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16

Rosati, A., and A. Aumaitre. "Organic dairy farming in Europe." Livestock Production Science 90, no. 1 (October 2004): 41–51. http://dx.doi.org/10.1016/j.livprodsci.2004.07.005.

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17

Hsu, Vernon N., Guoming Lai, and Guitian Liang. "Agricultural Partnership for Dairy Farming." Production and Operations Management 28, no. 12 (February 11, 2019): 3042–59. http://dx.doi.org/10.1111/poms.12992.

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18

Glover, Jane. "The Logic of Dairy Farming." International Journal of Rural Management 11, no. 2 (October 2015): 130–55. http://dx.doi.org/10.1177/0973005215600844.

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19

Weir, Ann. "Dairy Farming in New Zealand." New Zealand Journal of Geography 108, no. 1 (May 15, 2008): 32. http://dx.doi.org/10.1111/j.0028-8292.1999.tb00402.x.

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20

Зубарева, Ю. В. "Financial management in dairy farming." Экономика и предпринимательство, no. 8(133) (November 16, 2021): 1290–96. http://dx.doi.org/10.34925/eip.2021.133.8.253.

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Оптимальное ресурсное обеспечение факторов производства для максимального использования производственного потенциала, с целью получения оптимальных производственных результатов, обеспечивающих максимальные финансовые результаты, является целью финансового менеджмента. Методы финансового менеджмента сфокусированы на действии, показывая, какие возможны альтернативные варианты действий, а также дают возможность принимать решения с высокой степенью рациональности. Optimal resource provision of production factors for the maximum use of production potential, in order to obtain optimal production results, ensuring maximum financial results, is the goal of financial management. Financial management methods are focused on action, showing what alternative options are possible, and also make it possible to make decisions with a high degree of rationality.

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21

Péter Boldizsár. "Precision dairy farming in the practice – DeLaval „Smart Farming”." Acta Agraria Debreceniensis, no. 49 (November 13, 2012): 119–22. http://dx.doi.org/10.34101/actaagrar/49/2508.

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22

Norton, T., and D. Berckmans. "Developing precision livestock farming tools for precision dairy farming." Animal Frontiers 7, no. 1 (January 1, 2017): 18–23. http://dx.doi.org/10.2527/af.2017.0104.

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23

Ma, Yilin. "A study on the influencing factors of dairy farming returns in China based on regression analysis." Journal of Education, Humanities and Social Sciences 30 (April 19, 2024): 204–11. http://dx.doi.org/10.54097/an5hmq60.

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Since the reform and opening up, China's dairy industry has continued to improve, as reflected in the significant increase in the scale, standardization, and modernization of dairy farming. At the same time, dairy companies are experiencing a steady acceleration of production changes and technological innovation, and the consumption of dairy products is gradually growing, making milk popular as a necessary food for daily life. As the starting point of the whole dairy industry chain, dairy farming is the fundamental link in the development of this industry. Therefore, analyzing the profitability of dairy farming in China and studying the factors influencing the profitability of farming is essential to ensure the sustainable, efficient, and high-quality development of China's dairy industry. Based on the data released by the National Compendium of Costs and Benefits of Agricultural Products, this study uses regression analysis with the help of the theory of costs and benefits to study the influencing factors of the benefits and puts forward constructive suggestions for different modes of dairy farming to reduce costs and increase benefits.

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24

Singh, Singh, S. P, Ghosh Ghosh, S. S, Lakhani Lakhani, G. P, Jain Jain, et al. "Organic Dairy Farming: A Novel Approach in Dairy Sector." International Journal of Livestock Research 4, no. 6 (2014): 10. http://dx.doi.org/10.5455/ijlr.20140904091322.

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25

KUMAR, SANJEEV, SANJEEV RANJAN, SURYAMANI KUMAR, and SANJAY KUMAR. "Empowering women dairy farmers through scientific dairy farming practices." Indian Journal of Animal Sciences 88, no. 10 (October 22, 2018): 1203–6. http://dx.doi.org/10.56093/ijans.v88i10.84170.

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The study was carried out in 6 villages of operational area of KVK, Nalanda, about the knowledge levels of the women dairy farmers with respect to the different component of Scientific Dairy Farming Practices (SDFP). Fifteen farmers from each village constituting the sample size of 90 farmers were included in the survey. The responses of the farmers were collected and statistically analyzed. The study revealed that majority of farmers had medium knowledge on different components of SDFP. But, very few farmers had high knowledge about the SDFP, which showed that different dairy development agencies working in Nalanda district were not providing adequate knowledge to the farmers. The knowledge index of different aspect of SDFP, viz. breeding, feeding, health care and management were 42, 37.84, 39.75 and 41.73%, respectively, and overall knowledge index of SDFP was 39.63, which indicated poor knowledge level of farmers in the study area. Therefore, the KVK, Nalanda should make proper action plan in which more training programmes could be organized on SDFP especially for women dairy farmers to empower them in dairying.

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26

RU, Bangar, Lad AS, Kadam RP, and Mahajan SK. "Training needs of dairy farm women about dairy farming." Pharma Innovation 12, no. 1 (January 1, 2023): 201–5. http://dx.doi.org/10.22271/tpi.2023.v12.i1c.17857.

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27

Muhammad, Ali Mauludin, and Puspita Sari Viani. "Dialectics of Dairy Farming Enterprises and Dairy Farmer Community in Pangalengan West Java." E3S Web of Conferences 73 (2018): 11010. http://dx.doi.org/10.1051/e3sconf/20187311010.

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Dairy farming business in Pangalengan has been established since Dutch colonial goverment set in and it continues until today. The business encountered such dynamics, in which aligned with political changes took place in Indonesia. Situated in Southern West Java, Pangalengan has been an icon of dairy farming in that it is major occupation of Pangalengan inhabitants. Capital owners were atracted to invest there, make capitalism penetration occured during some periods and developed quite well. Koperasi Peternak Bandung Selatan / Dairy Farmer Cooperative of South Bandung (KPBS) which is famous for its pro-community development then emerged and established along with the massive development of dairy farming in that town which later gave big contribution to development process. One of them is the establishment of a new private dairy farming plant in Pangalengan. Dillematic situation then occured. There were pro and contra against the existence of that private enterprise amongst the Pangalengan citizens. One group thought that the enterprise would generate the development process in Pangalengan, while others considered that it would create a clash with the community dairy farmers who have existed long before the independence of Republic of Indonesia. This paper will discuss dialectics of Private Dairy Farming Enterprise and dairy farmers community in Pangalengan. Both perspectives of private dairy farming enterprise and dairy farmers community will be the study in this paper. Positive and negative aspects are constructed in the arena or dialectics of dairy farming development.

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28

Akbar, Muhammad Osama, Muhammad Saad Shahbaz khan, Muhammad Jamshaid Ali, Azfar Hussain, Ghazia Qaiser, Maruf Pasha, Urooj Pasha, Malik Saad Missen, and Nadeem Akhtar. "IoT for Development of Smart Dairy Farming." Journal of Food Quality 2020 (March 23, 2020): 1–8. http://dx.doi.org/10.1155/2020/4242805.

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Internet of things (IoT) and data-driven techniques are creating greater opportunities for smart dairy farming. The demand for milk is continuously increasing due to increasing population of the world. The consumption of the dairy products is more in developed countries as compared to developing countries. To meet this increased demand for milk products, better technological techniques for improving milk yield are required. It is expected that the use of IoT and different AI techniques can assist a farmer to overcome different traditional farming challenges and increase the milk production. In this research, the authors address different challenges that a dairy farmer has to face in daily life. Brief introduction of smart dairy farming (SDF) is presented with respect to the innovation in production and the processes of smart dairy farming. This review focuses on different aspects of smart dairy farming, and finally a state-of-the-art framework that can assist the farmers to increase the milk yield by using different latest technologies has been proposed. These technological methods can decrease the factors negatively affecting milk production and increase those positively affecting production with minimal resources.

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29

Eqbal, Md Shahid, Manish Kumar Singh, and Nazam Khan. "Information Needs as Perceived by Tribal Dairy Farmers of Chotanagpur Region in Dairy Farming Practices." Indian Journal of Applied Research 3, no. 6 (October 1, 2011): 506–7. http://dx.doi.org/10.15373/2249555x/june2013/168.

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30

Liu, Chenyang, Lihang Cui, and Cuixia Li. "Impact of Environmental Regulation on the Green Total Factor Productivity of Dairy Farming: Evidence from China." Sustainability 14, no. 12 (June 14, 2022): 7274. http://dx.doi.org/10.3390/su14127274.

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Environmental regulation is essential to promote green and sustainable development in dairy farming. Nevertheless, limited studies have focused on the impact of environmental regulation on the green total factor productivity (GTFP) of dairy farming. This study measures the GTFP of dairy farming in 27 provinces in China during 2009–2020 using the Slack Based Measure (SBM) model and the Malmquist–Luenberger (ML) productivity index. In addition, random effects and threshold regression models are used to measure the impact of environmental regulations on the GTFP of dairy farming. The results demonstrate the fluctuating growth of the GTFP of dairy farming and that technical efficiency is the primary driver of the GTFP growth. The annual growth rate of GTFP is the highest in large-scale dairy farming (3.27%), followed by medium-scale dairy farming (2.73%) and small-scale dairy farming (1.98%). Furthermore, environmental regulation positively affects the GTFP and has a threshold effect on the GTFP, with the urban–rural income gap as the threshold variable in medium-scale dairy farming and small-scale dairy farming. The impact on the GTFP can be significantly negative if the urban–rural income gap crosses the threshold value. Overall, this study provides some policy recommendations for attaining green and sustainable dairy farming development in China.

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31

Pandey, Saurabh, K. Ponnusamy, and Hemlata Saini. "A TEST TO MEASURE KNOWLEDGE OF DAIRY FRAMERS ABOUT IMPROVED DAIRY FARMING PRACTICES." Gujarat Journal of Extension Education 36, no. 2 (December 25, 2023): 120–25. http://dx.doi.org/10.56572/gjoee.2023.36.2.0022.

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Dairy farming is practised mainly by resource poor farmers who have limited access to knowledge, skill, training and credit. Extension interventions would help these farmers to access knowledge and technologies that can enhance their standard of living. This would facilitate them to obtain good economic returns. The major objective of study was to evaluate dairy farmers’ knowledge about improved dairy farming practices. The knowledge test of resource poor dairy farmers on four major areas of dairy farming (breeding, feeding, healthcare and management practices) was conducted. A tentative list of 35 items was drafted keeping in view the application of statement suited to the area of study. After getting jury opinion on the items of test, Item difficulty index, Discrimination index and items of validity were worked out. Finally, 28 statements were selected in the final format to measure knowledge about improved dairy farming practices. The reliability coefficient (rtt=0.77) obtained indicated that the internal consistency of the knowledge test developed for the study was very high.

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32

Rud, Ekaterina N., Elena V. Kuzminova, Marina P. Semenenko, Andrey A. Abramov, and Nikolay A. Rud. "Heat stress problem in dairy farming." Veterinaria Kubani, no. 3 (July 27, 2020): 10–11. http://dx.doi.org/10.33861/2071-8020-2020-3-10-11.

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In the context of the industrial survival of animal husbandry, taking into account the climatic characteristics of Krasnodar region, climate is considered as a heat stress, the result of an imbalance between the intake of heat from the environment and its release by the body. To assess the risks of occurrence and severity of heat stress in cattle, it is necessary to take into account not only the ambient temperature, but also humidity indicators. The temperature and humidity index provides for these two variables and allows us to assess the need for cooling of animals. The article provides information on the possibilities of occurrence and impact of heat stress due to the temperature-humidity state of the environment. Analysis of the reporting data of the Veterinary Department of Krasnodar region and the number of industries in Krasnodar region and cattle sampling rates from 2017 to 2019 demonstrates an increase in the number of abortions and youth losses during the third quarter when the temperature of the environment reaches its maximum. With this in mind, to increase the adaptability of animals under prolonged heat stress, it is necessary to regularly monitor the environmental parameters (use of thermometers and hygrometers to assess the temperature and humidity index), as well as plan protective measures (adapted feeding technology, specialized additives, good bulky feed), which will help to minimize the negative impact of hyperthermia on the economy of livestock production.

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33

Klingström, Tomas, Karl-Johan Petersson, Natalie Von der Lehr, Hans Persson, and Dirk-Jan De Koning. "Precision dairy farming – A Phenomenal opportunity." EMBnet.journal 26, A (July 8, 2021): e966. http://dx.doi.org/10.14806/ej.26.a.966.

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34

Innes, Ev, and Casey Walsh. "Musculoskeletal disorders in Australian dairy farming." Work 36, no. 2 (2010): 141–55. http://dx.doi.org/10.3233/wor-2010-1016.

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35

Ahonen, E., J. M. Venäläinen, U. Könönen, and T. KlenK. "The physical strain of dairy farming." Ergonomics 33, no. 12 (December 1990): 1549–55. http://dx.doi.org/10.1080/00140139008925353.

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36

Roche, John. "Foreword to ‘Resilient Dairy Farming Systems’." Animal Production Science 55, no. 7 (2015): iii. http://dx.doi.org/10.1071/anv55n7_fo.

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37

O’ Mahony, Niall, Sean Campbell, Anderson Carvalho, Lenka Krpalkova, Daniel Riordan, and Joseph Walsh. "3D Vision for Precision Dairy Farming." IFAC-PapersOnLine 52, no. 30 (2019): 312–17. http://dx.doi.org/10.1016/j.ifacol.2019.12.555.

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38

Hailu, Getu, and B. James Deaton. "Agglomeration Effects in Ontario's Dairy Farming." American Journal of Agricultural Economics 98, no. 4 (June 13, 2016): 1055–73. http://dx.doi.org/10.1093/ajae/aaw041.

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39

Slozhenkina, Marina I., Ivan F. Gorlov, Gilyan V. Fedotova, and Natali I. Mosolova. "Neural Network Forecasting in Dairy Farming." International Journal of Trade and Global Markets 1, no. 1 (2023): 1. http://dx.doi.org/10.1504/ijtgm.2023.10054741.

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40

Gazim, Zilda Cristiani, André Felipe Berto De Almada, Mariane De Almeida Machado, Selma Alves Rodrigues, João Pedro Terra Prado Borges, Gabriela Catuzo Canônico Silva, Daniela Dib Gonçalves, and Ranulfo Piau Junior. "Probiotics and prebiotics in dairy farming." Concilium 23, no. 14 (July 13, 2023): 222–34. http://dx.doi.org/10.53660/clm-1662-23j52.

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The search for natural products that favor productive performance in animal feed has been gaining strength with probiotics, prebiotics and symbiotics that constitute an alternative for mastitis control. The action of these products is in the competition with unwanted microorganisms, stimulating the beneficial microbiota, in addition to favoring a greater development in the intestinal villi, which can provide a better absorption of nutrients. These compounds are an alternative to treatment with antibiotics that have caused the emergence of resistant microorganisms, in addition to causing sensory changes in milk and its derivatives. Through this study, it was possible to verify the importance of this class of substance for dairy farming and for unique health in general.

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Fedotova, Gilyan V., Ivan F. Gorlov, Marina I. Slozhenkina, and Natali I. Mosolova. "Neural network forecasting in dairy farming." International Journal of Trade and Global Markets 18, no. 2/3 (2023): 207–16. http://dx.doi.org/10.1504/ijtgm.2023.135608.

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42

Martiin, Carin. "From farmer to dairy farmer: Swedish dairy farming from the late 1920s to 1990." Historia Agraria. Revista de agricultura e historia rural 73 (November 15, 2017): 7–34. http://dx.doi.org/10.26882/histagrar.073e04m.

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Swedish dairy farming became increasingly commercialized up until the mid-twentieth century, when nine out of ten farmers supplied milk to dairy plants. They adopted the view that milk sales were the path to progress for agriculture and the countryside in times of urbanization. Dairy farming was obviously embedded in functions that went beyond food production, which complicated the situation when the surplus of dairy farmers led to overproduction. At the same time, domestic demand became saturated and the international butter market proved more challenging than expected. This article focuses on collective outcomes of farmers’ actions in terms of commercialization, intensification, specialization and geographic concentration from the late 1920s to 1990. The timeframe includes an expansive phase until the late 1940s, which was followed by decades of declining demand for milk and a more restrictive political policy toward agricultural surpluses. It is argued that the vision of dairy farming as a safe way to make a living in agriculture underestimated the potential for increased production and limited demand. Contrary to initial hopes of using milk as a way to save the countryside, increasingly intensive and specialized dairy farming served to drive many out of farming.

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43

Khurana, Priya, and Arpita Sharma Kandpal. "Relationship between socio economic profiles of dairy farmers with extent of adoption of improved dairy farming practices in Kumaon division of Uttarakhand." International Journal of Agricultural and Applied Sciences 4, no. 1 (June 30, 2023): 50–52. http://dx.doi.org/10.52804/ijaas2023.419.

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Livestock sector contributes 4.11 per cent GDP. According to United States Department Agriculture 2018, 80 million households were engaged in dairy farming and majority of them are small scale, marginal farmers. The dairy farming has been considered as a potential means of employment and socio-economic development for people in rural areas. Uttarakhand trails behind from highest milk producing states due to less growth rate in milk production focused should be given to the improved dairy farming to increase milk production and development of dairy industry. The present study was conducted in Kumaon division of Uttarakhand state to find out the relationship between socio economic profile of dairy farmers with their extent of adoption of improved dairy farming practices. Udham Singh Nagar district was selected as for the study. Total 100 respondents from these villages were selected. It was resulted that respondents with higher education, higher land holdings, higher dairy farming experience, higher annual income, higher milk production higher social participation, higher risk preference and higher economic motivation tends to have more extent of adoption of improved dairy farming practices as they are found to have a significant and positive relationship with extent of adoption of dairy farming practices.

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R. Sk., Mahammad Shafi, N. B. Chauhan, and Vinaya Kumar H. M. "Qualities responsible to shape the family dairy farming skillfulness amongst the sons of practising dairy farmers." Gujarat Journal of Extension Education 34, no. 1 (December 25, 2022): 30–33. http://dx.doi.org/10.56572/gjoee.2022.34.1.0006.

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The professionals of the scientific dairy farming have a strong observation that until and unless practical ability or skilfulness to execute modern methods and operations of animal husbandry, just possession of theoretical information about the package of practices of dairy farming is not enough to get the expected return for newcomers to manage family dairy farming as an occupation. Considering this, the current research was carried out on a random sample of 200 young sons in-between the age of 18 to 35 of practising dairy farmers of Anand and Kheda districts of Gujarat. The study examined the qualities responsible to shape the family dairy farming skilfulness amongst the sons of practising dairy farmers as the new generation to handle the dairy farming occupation. The research clearly states that the majority (91.00 per cent) of the dairy farmers’ sons had a high to a very high level of skilfulness to handle animal husbandry related operations. The results of the correlation coefficients indicate that skilfulness to handle animal husbandry operations and activities was observed superior amongst those sons who had relatively older age above 25 years, married matrimonial status, the bigger size of family landholding and maintained the bigger size of the herd by their parents, to some extent low educated fathers as well as encouraging mindset towards farming as an occupation.

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Yasmin, Sarah, and Yukio Ikemoto. "Profile of Women Dairy Farmers in Two Villages of Mymensingh District." Asian Social Science 16, no. 7 (June 29, 2020): 118. http://dx.doi.org/10.5539/ass.v16n7p118.

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Dairy farming assumes most important role in providing income generating opportunities particularly for rural women in Bangladesh. To access the socio-economic status of dairy farmers, this study was carried out in selected areas of Mymensingh district. Total sample size was 50 and sample data were obtained from V1 (modern dairy farming), V1 (traditional dairy farming) and V2 (traditional dairy farming) through direct interviews using questionnaires. Simple statistical methods such as frequency, percentage and mean were used to analyze the sample data. V1 (M) women use modern technology of dairy farming and V2 (T) is traditional village. Financial conditions of selected farmers were investigated in study areas. It was found that households in V1 (M) had more household income and well status than others and that V1 (M) woman were more educated and older with longer experience in dairy farming. Relatively wealthy households and educated/experienced women tend to adopt modern dairy farming.

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Ninama, K. S., Hemlata Saini, and R. A. Gamit. "Willingness to adopt dairy farming among young women." Gujarat Journal of Extension Education 34, no. 1 (December 25, 2022): 143–47. http://dx.doi.org/10.56572/gjoee.2022.34.1.0029.

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The research study was conducted among randomly selected 120 young woman members of dairy farmers of Anand district to measure their willingness to adopt dairy farm. The Anand district carries eight talukas, out of which five were selected on the basis of highest milk production for making a composition of 120 young woman members of dairy farming. The result indicated that half (50.83 per cent) of the young woman members had a high level of willingness to adopt dairy farming followed by 35.83 per cent with a medium level of willingness and 10.00 per cent with a low level of willingness. Only 3.34 per cent of the respondents had a very high level of willingness to adopt dairy farming. Independent variables Land holding, herd size, extension contact, economic motivation, achievement motivation, self-confidence, scientific orientation, innovativeness, attitude towards dairy as an occupation and knowledge of dairy farming had positive and highly significant correlation with their willingness to adopt dairy farming.

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Subić, Jonel, Lana Nastić, and Svetlana Roljević-Nikolić. "Economic effects of investment in dairy farming." Western Balkan Journal of Agricultural Economics and Rural Development 2, no. 2 (2020): 135–46. http://dx.doi.org/10.5937/wbjae2002135s.

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Dairy farming is the most significant part of cattle raising. During the previous several years the volume of milk production has been maintained at a stable level, while there came to fall in number of dairy cows and number of farms engaged in dairy farming. Although the farms that own just a few heads of dairy cows usually step out the milk production, there are still a small number of farms specialized in dairy farming. The main paper objective is to present the economic effects of investment in the construction and equipping of dairy farm adequate for raising of 12 dairy cows. Economic analysis was based on the use of static and dynamic methods for investment assessment. Besides, there is also conducted the analysis of investment under the risk conditions (use of the break-even analysis). According to gained results (e.g. Internal rate of return, 11.98%, positive value of the Net present value, Payback period shorter than 5 years) the investment implementation is economically justified.

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Utami, Hari Dwi, MB Hariyono, Umi Wisaptiningsih, Hary Nugroho, and Nur Cholis. "The impact of education and experience on profit of smallholder dairy farming at Batu City of Malang Raya, Indonesia." E3S Web of Conferences 335 (2022): 00051. http://dx.doi.org/10.1051/e3sconf/202233500051.

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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.

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Cheng, Lijun, C. Jing, T. H. Duan, and F. Z. Li. "ResNet-based dairy daily behavior recognition." EAI Endorsed Transactions on Internet of Things 9, no. 2 (July 31, 2023): e5. http://dx.doi.org/10.4108/eetiot.v9i2.2901.

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With the rapid development of China ’s dairy farming industry, it becomes difficult to breed and manage the increasing number of dairy cows. The smart agricultural enabled by edging techniques such as smart sensor, IoT, machine learning, etc. shows great potential to improve the scientific breeding and management of dairy cows. Using machine learning assisted computer vision to identify and classify the behavior of dairy cows can quickly determine the health status of dairy cows and improve management efficiency. However, there are still some challenges need to be addressed in the current behavior recognition of dairy cows. Due to the more complex background of dairy farms, the increase in the number of cows makes the mutual shading problem of dairy cows serious, which leads to the low efficiency of dairy cow behavior recognition. To address this challenge, this paper collected and labeled four types of 1,660 dairy daily behavior datasets and proposed a residual neural network (ResNet)-based dairy daily behavior recognition model. Experiments show that the proposed method is far superior to the baseline method in accuracy performance, and it provides inspiration for the behavior recognition of cows.

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Velthof, G. L., and O. Oenema. "Nitrous oxide emission from dairy farming systems in the Netherlands." Netherlands Journal of Agricultural Science 45, no. 3 (October 1, 1997): 347–60. http://dx.doi.org/10.18174/njas.v45i3.510.

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A large part of the nitrogen (N) input in dairy farming systems in the Netherlands is lost from the system via N leaching and volatilization of gaseous N compounds, including the greenhouse gas nitrous oxide (N2O). The aim of the present study was to quantify N2O emission from dairy farming systems in the Netherlands, using a whole-farm approach. A total of 14 N2O sources was identified and emission factors were derived for each of these using the literature. Figures are presented for the amounts of N2O produced/kg herbage N produced (ranging from 4 to 89 g N2O-N kg-1 herbage N), depending on soil type and grassland management. Using Monte Carlo simulations, variations in mean total N2O emissions from the different sources were calculated for 3 model dairy farming systems differing in nutrient management. These different farming systems were chosen to assess the effect of improved nutrient management on total N2O emission. The total direct annual N2O emissions ranged from 15.4 +or-9.4 kg N2O-N/ha for the average dairy farming system in the 1980s to 5.3 +or-2.6 kg N2O-N/ha for a prototype of an economically feasible farming system with acceptable nutrient emissions. Leaching-derived, grazing-derived and fertilizer-derived N2O emissions were the major N2O sources on dairy farming systems. The total direct N2O emissions accounted for 3.2 to 4.6% of the N surplus on the dairy farming systems, suggesting that only a small amount of N was lost as N2O. Total N2O emissions from dairy farming systems in the Netherlands were 13.7+or-5.1 Gg N/year, which is about 35% of the estimated total N2O emission in the Netherlands. It is concluded that improvement of nutrient management of dairy farming systems will significantly decrease the N2O emissions from these systems, and thus the total N2O emission in the Netherlands.

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