Preview

Achievements of Science and Technology in Agro-Industrial Complex

Advanced search

Evaluation of reproductive performance of Holstein bull daughters using statistical methods of survival analysis

https://doi.org/10.53859/02352451_2026_40_2_55

Abstract

The study was conducted to test a method for genetically evaluating sires based on the length of the daughters’ service period using a mixed Cox proportional hazards model. The work was performed on retrospective breeding data for 2002-2022. The sample included information on 22,087 lactations of daughters of 42 Holstein sires (at least 100 lactations per sire). The time variable was the length of the service period (days from calving to successful insemination). Observations were censored if an animal was discarded before pregnancy or if there was no pregnancy after 305 days post-calving (event rate of 0.71). The mixed Cox model included fixed effects (lactation number, year and month of calving, calving ease) and a random effect (sire). The between-group variance for the random factor was 0.0243 (p < 0.001), the 50% median service period for the sample was 138 ± 1 days. Paratypic factors had a significant impact: the median decreased from 177 days in 2012 to 126 days in 2021, and the use of obstetric assistance increased this indicator by 12 days, compared to normal calving. Based on the assessment of the chances of pregnancy, 14 bulls were classified as improving reproductive quality, 13 – as worsening. The daughters of the best sire (Fortune 12302930) had a 43% higher probability of becoming pregnant during lactation than the herd average (odds ratio = 1.43). The Spearman rank correlation coefficient between the obtained estimates and the Canadian Daughter Fertility Index (Lactanet) was p = 0.525 (p < 0.001). The use of a mixed Cox model ensures the calculation of accurate, unbiased estimates of bull breeding value based on fertility, taking into account paratypic factors. Integration of the proposed approach into the national evaluation system will improve the accuracy of animal selection based on reproductive traits.

About the Authors

M. A. Shishkin
Novosibirsk State Agrarian University
Russian Federation

M. A. Shishkin, post graduate student

ul. Dobrolyubova, 160, Novosibirsk, 630039



E. V. Kamaldinov
Novosibirsk State Agrarian University
Russian Federation

E. V. Kamaldinov, D. Sc. (Biol.), prof., head of department

ul. Dobrolyubova, 160, Novosibirsk, 630039



A. F. Petrov
Novosibirsk State Agrarian University
Russian Federation

Petrov A. F., Cand. Sc. (Biol.), head of laboratory

ul. Dobrolyubova, 160, Novosibirsk, 630039



O. V. Efremova
Irmen’ stud farm
Russian Federation

Efremova O. V., chief zootechnician breeder

s. Verch-Irmen’, Ordyinskiyi r-n, Novosibirskaya obl., 633272



References

1. Modorov MV, Tkachenko IV, Grin AA, et al. Population genetic structure of Ural black pied cattle. Russ J Genet. 2021;57(4):453-9.

2. Petrov AF, Bogdanova OV, Narozhnykh KN, et al. Clustering of countries based on dairy productivity characteristics of Holstein cattle for breeding material selection. Vet World. 2024;(5(17)):1108-18.

3. Wahinya PK, Jeyaruban GM, Swan AA, et al. Optimization of Dairy Cattle Breeding Programs with Genotype by Environment Interaction in Kenya. Agriculture [Internet]. 2022[cited 2025 Mar 6];12(8):1274. Available from: https://www.mdpi.com/2077-0472/12/8/1274. doi: 10.3390/agriculture12081274.

4. Koyama K, Takahashi T. Relationship between sire predicted transmitting ability for daughter pregnancy rate and daughter’s reproductive performance and milk production in Japanese dairy herds. J Reprod Dev. 2020;66(5):445-52.

5. Shishkin MA, Kamaldinov EV, Pal’chikov PN. [Structure of variability and heritability of the high fertility cycle of Holstein cattle in the Novosibirsk region]. Vestn KrasGAU. 2025;(10):158-67. doi: 10.36718/1819-4036-2025-10-158-167. Russian.

6. Kaplan EL, Meier P. Nonparametric estimation from incomplete observations. J Am Stat Assoc. 1958;53(282):457-81.

7. Boujenane I, Draga B. Nongenetic factors affecting reproductive performance of Holstein dairy cows. Livest Res Rural Dev [Internet]. 2021[cited 2025 Mar 6];33:1. Available from: https://www.lrrd.org/lrrd33/1/ismail3310.html

8. Riabchuk PG, Korneev DN, Lysenko MV, et al. [Architecture of the methodological constructor: resampling]. Azimut Nauch Issled Ekon Upr. 2021;10(3(36)):242-5. Russian.

9. R Core Team. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2023 [cited 2024 Oct 20]. Available from: https://www.R-project.org/

10. Functional Trait Interpretations: Technical Note. Lactanet [Internet]. 2025 [cited 2025 Mar 6]. Available from: https://lactanet.ca/en/functional-trait-interpretations/

11. Ignat’eva LP, Sermisagin AA. [Use of the BLUP animal model method for assessing the breeding value of Simmental cows]. Vestn Ul’ianovsk Gos S-kh Akad. 2021;(4(56)):188-94. Russian.

12. Firsova EV, Kartashova AP. [Results of assessing the breeding value of lines using methods of comparison with peers and BLUP on the cattle population of the Murmansk region]. Agrar Vestn Urala. 2021;(5(208)):63-70. Russian.

13. Shendakov AI. [Genetic and environmental factors in Holstein breed selection]. Biol Sel’skom Khoz. 2021;(2(31)):2-7. Russian.

14. Kovaleva GP, Sulyga NV, Lapina MN. [Breeding and genetic evaluation of Holstein dairy cattle families of the Stavropol population]. Sel’skokhoz Zhurn. 2023;1(16):61-9. Russian


Review

For citations:


Shishkin M.A., Kamaldinov E.V., Petrov A.F., Efremova O.V. Evaluation of reproductive performance of Holstein bull daughters using statistical methods of survival analysis. Achievements of Science and Technology in Agro-Industrial Complex. 2026;40(2):55–61. (In Russ.) https://doi.org/10.53859/02352451_2026_40_2_55

Views: 84

JATS XML


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 0235-2451 (Print)