Genetic analysis of Brahman cattle growth curves using the two-stage method and joint analysis

• Autores: Conceição Meirelles, Sarah Laguna, Contreras Paco, Jose Luis, Canaza-Cayo, Ali William, Ribeiro de Lima, Renato, Rojas De La Cruz, Yhan Carlos
• Formato: artículo
• Fecha de Publicación: 2025
• Institución: Universidad Nacional Mayor de San Marcos
• Repositorio: Revistas - Universidad Nacional Mayor de San Marcos
• Lenguaje: español
• OAI Identifier: oai:revistasinvestigacion.unmsm.edu.pe:article/29053
• Enlace del recurso: https://revistasinvestigacion.unmsm.edu.pe/index.php/veterinaria/article/view/29053
• Nivel de acceso: acceso abierto
• Materia: Bayesian hierarchical model; genetic parameters; growth curves; beef cattle; modelo jerárquico bayesiano; parámetros genéticos; curvas de crecimiento; bovinos de carne

The aim of this study was to evaluate two methods for genetic analysis of the Gompertz growth curve (the two-stage method and the method based on a hierarchical Bayesian approach, referred to in this study as the conjoint analysis method). A total of 1110 body weight measurements from 185 Brahman cattle were used. The variance components of the curve parameters were estimated using the two-stage method using the restricted maximum likelihood (REML) method. For the conjoint analysis method, the Gibbs Sampling and Metropolis-Hasting algorithms were used. The heritability values estimated using the two-stage method were 0.41 ± 0.004, 0.09 ± 0.01, and 0.65 ± 0.001 for asymptotic weight (a), integration constant (b), and maturation rate (k), respectively. Estimates using the conjoint analysis method were 0.51 0.03, 0.50 0.04, and 0.52 0.04 for the asymptotic weight, integration constant, and maturation rate, respectively. Except for the parameter k, heritability estimates tended to be higher using the conjoint analysis method. The results reveal that the two-stage method presented a higher residual variance than the residual variance obtained with the conjoint analysis method, which could produce less precise estimates of the genetic parameters when using the two-stage method.