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Assessment of breeding and genetic parameters of milk productivity indicators of zebu cows-a prominent type of black-and-white breed

https://doi.org/10.32634/0869-8155-2024-385-8-101-106

Abstract

The article presents the results of an evaluation of the breeding and genetic parameters of milk productivity and breeding qualities of zeboid-type black-and-white cows. The level of coefficient of variability, interrelation and coefficient of heritability of indicators of dairy productivity of cows for the first, third and highest lactation in the herd of the Experimental station “Snegiri” — a branch of the Federal State Budgetary Institution of Science “N.V. Tsitsin Main Botanical Garden of the Russian Academy of Sciences” (Istra district, Moscow region) has been established. Currently, the herd at the experimental station consists of hybrid cattle created by crossbreeding black-and-white cattle with various zeboid subspecies (New Zealand, Indian, Azerbaijani, and Cuban), as well as with purebred Holstein-Friesians. As a result of extensive breeding work involving distant hybridization, unique animals have been developed that exhibit increased disease resistance, significant adaptive potential, and are undemanding in terms of feed and housing conditions under intensive milk production technology. Generally, the milk from zeboidtype black-and-white cattle is characterized by a comparatively higher concentration of nutrients — fats, proteins, milk sugar, and essential amino acids. The high nutritional value of the milk, combined with the enhanced adaptive abilities, characterizes the zeboid-type black-and-white cattle as potentially valuable animals, making breeding work with them justifiably highly relevant. The evaluation of breeding and genetic parameters will help uncover the potential for milk productivity, determine the directions for breeding work, and adjust selection methods to further enhance production and improve the breeding qualities of this type of dairy cattle.

About the Authors

T. V. Lepekhina
Moscow State Academy of Veterinary Medicine and Biotechnology — MVA named after K.I. Skryabin
Russian Federation

Tatyana Viktorovna Lepekhina, Associate Professor, Candidate of Biological Sciences

23 Academic Skryabin Str., Moscow, 109472



S. S. Yurochka
Federal Scientific Agroengineering Center VIM
Russian Federation

Sergey Sergeevich Yurochka, Senior Researcher, Candidate of Technical Sciences

5 1st Institutsky Аve., Moscow, 109428



F. E. Vladimirov
Federal Scientific Agroengineering Center VIM
Russian Federation

Fedor Evgenievich Vladimirov, Research Associate

5 1st Institutsky Аve., Moscow, 109428



M. D. Boyko
Moscow State Academy of Veterinary Medicine and Biotechnology — MVA named after K.I. Skryabin
Russian Federation

Maria Dmitrievna Boykо, Undergraduate Student

23 Academic Skryabin Str., Moscow, 109472



O. I. Solovyova
Russian State Agrarian University — Moscow Timiryazev Agricultural Academy
Russian Federation

Olga Ignatievna Solovyova, Professor, Doctor of Agricultural Sciences

49 Timiryazevskaya Str., Moscow, 127434



References

1. Boyko M.D., Mkrtchyan G.V., Kozlov Yu.N. Variability of milk productivity traits in cows of Leningrad and German breeding. Symbol of science. 2021; 4: 40–42 (in Russian). https://elibrary.ru/svuvaa

2. Boyko M.D., Mkrtchyan G.V. Correlation between economically useful traits in cows of German and Leningrad breeding. Innovation science. 2021; 5: 66–69 (in Russian). https://elibrary.ru/oxpfqn

3. Zagorodnev Yu.P., Elizarova I.B. Breeding and genetic parameters of dairy cattle productivity depending from line accessories. Nauka i оbrazovanie. 2022; 5(1): 100 (in Russian). https://elibrary.ru/fqhlor

4. Sheveleva O.M., Svyazhenina M.A., Chasovshchikova M.A. Breeding and genetic parameters of selection of cows for dairy productivity in the improvement of the herd of cattle. Vestnik Kurganskoy GSKhA. 2023; 1: 60–68 (in Russian). https://elibrary.ru/rbxubb

5. Krovikova A.N., Lepekhina T.V., Bakai F.R. Evaluation of the productive qualities of cows of different origin in the herd of Zelenogradskoye JSC Moscow region. Bulletin of Michurinsk State Agrarian University. 2023; 1: 100–104 (in Russian). https://elibrary.ru/bjzibw

6. Bianchi M.C. et al. Diffusion of precision livestock farming technologies in dairy cattle farms. Animal. 2022; 16(11): 100650. https://doi.org/10.1016/j.animal.2022.100650

7. Upelniek V.P., Zavgorodny S.V., Makhnova E.N., Senator S.A. The history of the origin and prospects for the spread of the zebu-type Black-and-White cattle (review). Achievements of science and technology in agribusiness. 2020; 34(12): 66–72 (in Russian). https://doi.org/10.24411/0235-2451-2020-11211

8. Lepekhina T.V., Yurochka S.S., Khakimov A.R., Pavkin D.Yu., Vasiliev A.A. Digitalization in breeding as a tool for predicting productivity in dairy cattle breeding. Zootechniya. 2023; 12: 10–13 (in Russian). https://doi.org/10.25708/ZT.2023.59.33.004

9. Neethirajan S., Kemp B. Digital Livestock Farming. Sensing and Bio-Sensing Research. 2021; 32: 100408. https://doi.org/10.1016/j.sbsr.2021.100408

10. Chinarov V.I. Resources of Russian cattle breeding. Achievements of science and technology in agribusiness. 2020; 34(7): 80–85 (in Russian). https://doi.org/10.24411/0235-2451-2020-10714

11. Alekseeva E.A. Index construction to comprehensively assess dairy cows. Bulletin of KrasGAU. 2023; 2: 172–179 (in Russian). https://elibrary.ru/yopfvh

12. Lepekhina T.V., Bakai F.R., Papurina O.Yu. Dairy productivity of cows of different lines in the agricultural complex “Maysky Stud Farm”. Zootechniya. 2022; 6: 5–7 (in Russian). https://elibrary.ru/wlulth


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For citations:


Lepekhina T.V., Yurochka S.S., Vladimirov F.E., Boyko M.D., Solovyova O.I. Assessment of breeding and genetic parameters of milk productivity indicators of zebu cows-a prominent type of black-and-white breed. Agrarian science. 2024;1(8):101-106. (In Russ.) https://doi.org/10.32634/0869-8155-2024-385-8-101-106

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ISSN 0869-8155 (Print)
ISSN 2686-701X (Online)
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