Variability structure and heritability of the high fertility cycle of Holstein cattle in the Novosibirsk Region
Автор: Shishkin M.A., Kamaldinov E.V., Palchikov P.N.
Журнал: Вестник Красноярского государственного аграрного университета @vestnik-kgau
Рубрика: Зоотехния и ветеринария
Статья в выпуске: 10, 2025 года.
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The aim of the study is to evaluate the structure of variability and heritability of the high fertility cycle in Holstein cows in industrial complexes of the Novosibirsk Region. The objectives of the study include: searching for a mathematical distribution corresponding to the empirical distribution of the service period; dividing cows into groups based on the presence or absence of a high fertility cycle; assessing the role of genetic, paratypic factors and heritability in maintaining high fertility. Research was based on the data of the IAS SELEX for four large livestock enterprises of the region for the period from 2001 to 2022. The final sample after cleaning consisted of 43,051 lactation records from 18,632 cows. The quantitative feature "service period" was transformed into a binary one (presence/absence of a high fertility cycle with a threshold of 130 days) and analyzed using a generalized mixed binomial model. The empirical distribution of the service period corresponds to the Poisson law (p = 0.12), characterizing the onset of pregnancy as a random event. Fifty-three percent of lactations correspond to a high-fertility cycle (a service period of 21–130 days). Significant negative effects on the probability of maintaining this cycle were demonstrated by the age of first fertile insemination (a 3 % decrease in chances for each additional month) and milk yield at 305 days (a 17 % decrease per 1,000 kg). The heritability coefficient for this trait was 0.154, confirming its low genetic determinacy. The largest proportion of variability (τ2 = 0.28) is explained by the random ef-fect of farm of origin, indicating the dominant role of paratypic factors.
Service period, high-fertility cycle, heritability, variability, binomial model, distribution fitting
Короткий адрес: https://sciup.org/140312646
IDR: 140312646 | УДК: 631.234.1.082.4 | DOI: 10.36718/1819-4036-2025-10-158-167