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<p>Developing traits that indirectly capture different stages of an animal’s reproductive life may support more effective selection for herd reproductive efficiency. This study aimed to estimate phenotypic and genetic parameters for lifetime offspring count (LOC) and age at first kidding (AFK) in Brazilian Saanen goats and to assess the goodness-of-fit of Gaussian, Poisson, and ordinal Bayesian mixed models for LOC. Data were obtained from 4,574 Saanen goats in the Capragene<sup>®</sup> dairy goat breeding program, with a pedigree of 5,829 animals born between 1989 and 2020. Bi-trait Bayesian analyses were conducted using three model combinations: Normal × Normal (NN), Normal × Poisson (NP), and Normal × Ordinal (NO). The average AFK was 2.03 ± 1.07 years, and mean LOC was 2.93 ± 2.31. Overall, the models converged successfully based on the Geweke diagnostic and visual inspection. Heritability estimates for LOC ranged from 0.03 to 0.17 depending on the assumed distribution, while AFK showed a heritability of 0.04. Models assuming non-normal distributions for LOC increased heritability estimates for this trait. The Poisson model provided the best fit, with the highest heritability, the lowest deviance information criterion, and the smallest mean squared error. Model choice could affect selection decisions, as different distributions led to variation in the animals ranked as top candidates. AFK showed no significant genetic correlation with LOC, limiting its value as an early selection criterion for lifetime reproductive performance.</p>

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Comparison of generalized Bayesian models for the genetic evaluation of lifetime offspring count and age at first kidding in Brazilian dairy goats

  • 期刊论文

  • 发表日期：

    2026年3月17日

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  • Alan Lopes de Aguiar,
  • Raimundo Nonato Braga Lobo,
  • Rebeka Magalhaes da Costa,
  • Anderson Antonio Carvalho Alves

摘要

Developing traits that indirectly capture different stages of an animal’s reproductive life may support more effective selection for herd reproductive efficiency. This study aimed to estimate phenotypic and genetic parameters for lifetime offspring count (LOC) and age at first kidding (AFK) in Brazilian Saanen goats and to assess the goodness-of-fit of Gaussian, Poisson, and ordinal Bayesian mixed models for LOC. Data were obtained from 4,574 Saanen goats in the Capragene® dairy goat breeding program, with a pedigree of 5,829 animals born between 1989 and 2020. Bi-trait Bayesian analyses were conducted using three model combinations: Normal × Normal (NN), Normal × Poisson (NP), and Normal × Ordinal (NO). The average AFK was 2.03 ± 1.07 years, and mean LOC was 2.93 ± 2.31. Overall, the models converged successfully based on the Geweke diagnostic and visual inspection. Heritability estimates for LOC ranged from 0.03 to 0.17 depending on the assumed distribution, while AFK showed a heritability of 0.04. Models assuming non-normal distributions for LOC increased heritability estimates for this trait. The Poisson model provided the best fit, with the highest heritability, the lowest deviance information criterion, and the smallest mean squared error. Model choice could affect selection decisions, as different distributions led to variation in the animals ranked as top candidates. AFK showed no significant genetic correlation with LOC, limiting its value as an early selection criterion for lifetime reproductive performance.