Selection and genetic parameters of the Holstein cattle population based on traits with continuous variability at the Bugry breeding farm in the Leningrad Region

The main objective of the study was to conduct a population-statistical analysis of integrated varying selection characteristics according to such parameters as: coefficients of heritability, repeatability, correlation, mean-square deviation. At the same time, the breeding parameters of dairy cows — milk yield, mass fraction of fat and protein, as well as key reproductive indicators — show variability within acceptable limits and pronounced correlations. Genomic assessment of breeding bulls is currently the main generally accepted and widely used method in world practice for determining breeding value; an innovative and effective method for increasing the efficiency of dairy cattle breeding and implementing the producer's genotype. The basis of the genomic forecast and calculation of the breeding differential is the assessment of the varying characteristics of the breed range; with its correction and refinement of new phenotypic data. The high repeatability of traits between lactation increases the predictive value of the first lactation data and justifies early selection, while a pronounced regression to the mean with low accuracy indicates insufficient breeding value of the producer. Descriptive statistics confirm the expected structure of the phenotype: milk yield for 305 days has a median of 9,820 kg with an interquartile range of 8,54910,944 kg and moderate relative dispersion (CV≈18%); the mass fractions of fat and protein are stable (3.60% [3.46–3.75] and 3.25% [3.13–3.39], respectively; CV≈6.9% and 5.5%), while the yield of components in kilograms varies more widely (fat 351.5 kg [310.1–390.1], CV≈17.8%; protein 321.8 kg [270.8–366.0], CV≈20.7%). The reproductive block is represented by a large range of variability: the median service period is 114 days [75-187] with a CV of 66.9%, and the distribution of somatic cells is expressed as follows (137×103 [77-300×103], CV≈138%). There are moderate negative associations at the junction of productivity and reproduction: earlier first insemination is associated with higher milk yield and yield of components (r≈-0.40 with milk yield; -0.47 and -0.35 with protein and fat in kilograms; with a mass fraction of protein p≈-0.48), reflecting the combined effect of biological maturity and management. The relevance of the research problem lies in the need for continuous monitoring of incoming data and correction of the genomic forecast.

1. Bugrov P.S., Ivanov N.V., Abylkasymov D., Sudarev N.P. Milk productivity and reproductive capacity of highly productive cows depending on hereditary factors. Dairy and beef cattle breeding. 2016; 8: 27–30.

2. Gerasimova A.S., Tatueva O.V., Prishchep E.A., Letunova D.V. Milk productivity of Brown Swiss cows and the results of its implementation in the Smolensk region. International Veterinary Bulletin. 2020; 4: 87–93.

3. Zhigachev A.I., Bezruchko A.V. Genetic potential of bulls used in AOZT "Kotelskoye". Proceedings of the St. Petersburg State Academy of Veterinary Medicine; 2003: 40–42.

4. Zhebrovsky L.S. Variability and heritability of protein content in cows' milk. Proceedings of the XIII International Dairy Congress. Melbourne; 1970: p. 484.

5. Kanalina N.M. Milk productivity of Tatar-type cows depending on their lineage. Scientific Notes of the Kazan State Academy of Veterinary Medicine named after N.E. Bauman. Kazan. 2013; Vol. 215: 156–160.

6. Kudrin A.G. Heritability of serum enzymes in high-yielding dairy cattle. Animal husbandry science: collected papers of the VSMAH. Vologda-Molochnoye; 2000: 44–46.

7. Svyazhenina M.A. Some selection and genetic indicators of Black-and-White cattle. Agrarian Bulletin of the Urals. 2012; 6: 46–48. Tatarina N.I., Svyazhenina M.A., Loseva N.A. Using the Productive Potential of the Holstein Breed. Agrarian Bulletin of the Urals. 2012;5(97): 58-60.

8. Ukolov P.I., Sharaskina O.G. Breeding and Biotechnics of Reproduction of Farm Animals. St. Petersburg: Quadro; 2018: 96–110.

9. Ukolov P.I., Sharaskina O.G. Veterinary Genetics. 2nd ed. St. Petersburg: Lan; 2022: 23–25.

10. Pereverzev D.B., Dunin I.M., Kozankov A.G., Meshcherov R.K., Vysotskaya V.M. Fundamentals of Increasing the Selection Effect in Breeding Kholmogory Cattle: Methodological Recommendations. Moscow: GNU VNII Breeding Research Institute; 2000:19–25.

11. Lepekhina T.V., Yurochka S.S., Khakimov A.R., et al. Digitalization in breeding as a tool for predicting productivity in dairy cattle farming. Zootechnics. 2023;12: 10–13.

12. Mishurov N.P., Kondratieva O.V., Goltiapin V.Ya., et al. Organizational foundations for constructing a multi-level information and computing system for breeding and selection work: an analytical review. Moscow: Rosinformagrotech; 2022: 224 p.

13. Isupova Yu.V., Gimazitdinova E.A., Azimova G.V., Martynova E.N. Efficiency of genomic analysis of the breeding value of Holstein sires in comparison with assessment based on the quality of offspring. Dairy and Beef Cattle Farming. 2022;1:c. 7.

14. Butler M. L., Bormann J. M., Weaber R. L., Grieger D. M., Rolf M. M. Selection for bull fertility: a review. Translational Animal Science. 2019;4(1): 423–441.