Phenotypic correlation and estimation of bodyweight in creole cattle

Descripción del Articulo

The aim of this study was to determine the phenotypic correlations between bodyweight (PV) and the biometric measurements of 90 Creole cattle, of both sexes and diverse ages, from the Conayca Community in Huancavelica, Peru, to define prediction equations of PV. Head width (AC), head length (LC), ch...

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Detalles Bibliográficos
Autores: Contreras P., José L., Cordero F., Alfonso, Reymundo C., Blas, Ramos A., Hebert E., Curasma C., James, Delgado C., Alfredo
Formato: artículo
Fecha de Publicación:2020
Institución:Universidad Nacional Mayor de San Marcos
Repositorio:Revistas - Universidad Nacional Mayor de San Marcos
Lenguaje:español
OAI Identifier:oai:ojs.csi.unmsm:article/17546
Enlace del recurso:https://revistasinvestigacion.unmsm.edu.pe/index.php/veterinaria/article/view/17546
Nivel de acceso:acceso abierto
Materia:body weight
native cattle
productive interrelations
biometry
peso vivo
bovinos criollos
interrelaciones productivas
biometría
Descripción
Sumario:The aim of this study was to determine the phenotypic correlations between bodyweight (PV) and the biometric measurements of 90 Creole cattle, of both sexes and diverse ages, from the Conayca Community in Huancavelica, Peru, to define prediction equations of PV. Head width (AC), head length (LC), chest width (ATO), chest height (ALT), body length (LCU), chest perimeter (PT), height at the withers (ACR), rump width (AGR), rump length (LGR), anterior fetlock perimeter (PCA), lumbar back distance (DDL), rump height (ALG), chest length (LTO), body length (LAC) and abdominal perimeter (PAB) were measured. The observations were analysed using linear models, including the effect of sex and age based on teeth growth. The biometric measurements were adjusted in a first order multiple linear regression to obtain the prediction equations of PV of the animals. Dental age was the most important source of variation in each of the characteristics, except for ALT. Sex only significantly affected PCA and ALG. High and significant phenotypic correlations (p<0.001) were detected between the PV and the measurements of PT (0.91), LC (0.79), ACR (0.77), ALG (0.78) and LAC (0.89). The PT + ACR + LAC presented the most accurate prediction equation (R2 = 1.0000), followed by the PT + LAC (R2 = 0.9775) and the PT (R2 = 0.9274). It is concluded that the PV of the Creole cattle studied can be satisfactorily predicted from the PT, or PT + LAC or PT + ACR + LAC, where dental age is the factor that most influences predictions.
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