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Genetic parameters for direct and maternal genetic components of calving ease in Korean Holstein Cattle using animal models. | LitMetric

AI Article Synopsis

  • The study explored the genetic parameters influencing calving ease (CE) in Korean Holsteins using various animal models and aimed to find suitable methods for routine CE evaluation.
  • Two datasets containing first-parity CE records were analyzed with an emphasis on heritability and maternal effects, revealing different modeling structures.
  • The results indicated that models M2 and M3 were more effective in accounting for data complexities, which could enhance future genetic evaluations and selection progress for CE in this breed.

Article Abstract

Objective: We investigated genetic parameters of calving ease (CE) using several animal models in Korean Holstein and searched for suitable models for routine evaluation of CE.

Methods: Two phenotypic datasets of CE (DS5 and DS10) on first-parity Korean Holstein calves were prepared. DS5 and DS10 included at least 5 and 10 CE records per herd-year level and comprised 117,921 and 80,389 observations, respectively. The CE phenotypes ranged from 1 to 4, from a normal to extreme difficulty calving scale. The CE was defined as a trait of the calf. The BLUPF90+ software was used for (co)variances estimation through four animal models with a maternal effect (M1 to M4), where all models included effects of a fixed calf-sex, a fixed dam calving age (covariate), and one or more fixed contemporary group (CG) terms. The CG effects were different across models-a herd-year-season (M1, HYS), a herd-year and year-season (M2, HY+YS), a herd-year and season (M3, HY+S), and a herd and year-season (M4, H+YS).

Results: Direct heritability (h2) estimates of CE ranged from 0.005 to 0.234 across models and datasets. Maternal h2 values were low (0.001 to 0.090). Genetic correlations between direct and maternal effects were strongly negative to lowly positive (-0.814 to 0.078), further emphasizing its importance in CE evaluation models. These genetic parameter estimates also indicate slower future selection progress of CE in Korean Holsteins. The M1 fitted many levels with fewer observations per level deriving unreliable parameters, and the M4 did not account for confounded herd and animal structures. The M2 and M3 were deemed more realistic for implementation, and they were better able to account for data structure issues (incompleteness and confounding) than other models.

Conclusion: As the pioneering study to employ animal models in Korean Holstein CE evaluation, our findings hold significant potential for this breed's future and routine evaluation development.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11541032PMC
http://dx.doi.org/10.5713/ab.24.0281DOI Listing

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