Modeling experience in northern reindeer husbandry

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The objective of the study is to develop models of nomadic reindeer herding, including a description of the main technological processes, the yield of meat and antler products depending on the number of animals and production indicators. The presented studies are unique, since, firstly, much attention is currently paid to food security in the Arctic zone of the Russian Federation, and reindeer meat is an essential part of the food basket of northerners, and secondly, the development of effective models and forecasting the productivity of individual animals, as well as optimization of herd management using these technologies open up new opportunities to improve the efficiency of the reindeer herding industry. Primary material on nomadic reindeer herding farms was collected in the YamaloNenets Autonomous Okrug in 2018–2023. A total of 13 nomadic farms with a population of 14,550 reindeer were surveyed. Analytical, statistical, descriptive, expert, graphical, and mathematical methods were used in the research. As a result of the conducted research, a descriptive model of the sequence and content of household and technological operations during the calendar year was compiled, which allows to present the specifics of production operations in a nomadic reindeer herding economy and the functional requirements for members of a nomadic family and specialists. A digital model of the need of nomadic families for the number of private reindeer and the structure of a reindeer herd with different meat productivity of the livestock, as well as a simplified scheme for forecasting the yield of meat in slaughter weight and dry antlers were developed. The implementation of the above models allows to forecast the yield of commercial products in reindeer herding, to plan the optimal size and structure of a herd of domestic reindeer.

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Arctic zone of the Russian Federation, reindeer herding, venison, antlers, production modeling

Короткий адрес: https://sciup.org/140312349

IDR: 140312349   |   УДК: 636.294:636.082   |   DOI: 10.36718/1819-4036-2025-9-185-196