graduate student from 01.01.2022 until now
VAK Russia 5.2.3
VAK Russia 5.2.4
VAK Russia 5.2.5
VAK Russia 5.2.6
VAK Russia 5.2.7
UDC 631.151
UDC 631.151.1
The article reflects the main trends in the development of dairy cattle breeding. Dairy farms in the region were selected as the object of the study. The opportunities and threats to the further development of the industry are identified. The aim of the research is to develop a unified system for forecasting, planning, monitoring, and managing dairy farms in the region. The results of the research in this area are briefly reviewed. The Presidential Decree of the Russian Federation No. 309 of March 7, 2024, “On the National Development Goals of the Russian Federation for the Period up to 2030 and for the Outlook up to 2036,” outlines a new stage of development, including for dairy cattle breeding. To conduct more substantiated forecasting, planning, and management, the authors propose a new comprehensive system of indicators for forecasting dairy cattle breeding in the region.
dairy cattle breeding, indicators, forecasting, planning, Balanced Scorecard
1. Kuzyk B.N., Kushlin V.I., Yakovec Yu.V. Prognozirovanie, strategicheskoe plani-rovanie i nacional'noe programmirovanie // Ekonomika. 2011. 1–604 s.
2. Rutten CJ, Steeneveld W, Vernooij JCM, Huijps K, Nielen M, Hogeveen H. A prognostic model to predict the success of artificial insemination in dairy cows based on readily available data // J Dairy Sci. 99(8) 1/08/2016.67–79pp.
3. Glen J.J. operations Res/; 1987. 35 s. Mathematical Models in Farm Planning: A Survey //Operations ResearchVol. 35, No. 5 (Sep. - Oct., 1987), 641-666 pp.
4. Houben E.H. Economic optimization of decisions with respect to dairy cow helf man-agement // Netherlands: Wageningen Agric. Univ. 1995. 528 pp.
5. DeLorenzo MA, Thomas C V. Dairy Records and Models for Economic and Financial Planning // J Dairy Sci. 1.02.1996. 79(2). 33–45 pp.
6. Kompas T, Che TN. Technology choice and efficiency on Australian dairy farms. Aus-tralian Journal of Agricultural and Resource Economics //50(1) 03.2006 50(1).65–83 pp.
7. Bjorn G.H., Agnar H., Grete S. Characterizing Efficient Dairy Farms and Farmers // Farm Management. 2.10.2002. 129–42 pp.
8. Murphy MD, O’Mahony MJ, Shalloo L, French P, Upton J. Comparison of modelling techniques for milk-production forecasting // J Dairy Sci. 97(6) 1.06.2014. 33–63 pp.
9. Deshmukh S, and RPAJ of DForecasting of milk production in India with ARIMA and VAR time series models // Journal of Dairying, Foods & Home Sciences 35(1). 03.2016. 17-22 pp.
10. Sabir'yanova R.G., Shatova B.C. Proizvodstvennyy potencial molochnogo skotovodstva i faktory ego rosta // Regional'naya ekonomika: teoriya i praktika. 2008. 68-71c.
11. Lichko K.P. Prognozirovanie i planirovanie agropromyshlennogo kompleksa // Gardariki; 1999. 264 c.
12. Kaplan R., Norton D. Sbalansirovannaya sistema pokazateley. Ot strategii k dey-stviyu // ZAO «Olimp -Biznes». 2006. 320c.
13. Gáspár S, Czikkely M, Thalmeiner G. Improvement of the BSC model with KPI-tree method through a dairy farm case study // Hungarian Agricultural Engineering. (38)2020. 5–14 pp.
14. Christian Noell, Mogens Lund. The Balanced Scorecard (BSC) for Danish Farms -Vague Framework jr Functional Instrument? // Farm Managment. 2.10.2002.193–210 pp.
15. Bogataya I.N., Dmitrichenko E.D. Osobennosti primeneniya metodiki sbalansiro-vannyh pokazateley v sel'skohozyaystvennyh organizaciyah dlya upravleniya riska-mi // Uchet i Statistika. 2008.12–35c.
16. Pashkovina E.V. Model' formirovaniya sistemy sbalansirovannyh pokazateley kak instrument upravleniya biznes-processami // Biznes Obrazovanie Pravo Vest-nik Volgogradskogo instituta biznesa. 4 (45). 11.2018. 56–61 c.
17. Mazloev V.Z., Suglobov A.E.Formirovanie mnogofunkcional'nyh ob'edineniy produktovogo kompleksa: metodologiya i praktika // Ekonomika, trud, upravlenie v sel'skom hozyaystve. 2023. № 11 (105). S. 164-170.



