Best linear model to explain variability in the growth in Blanco Orejinegro cattle and effect of the serological status for bovine viral diarrhea and bovine leukosis

• Autor(a) principal: Saldarriaga-Saldarriaga, Alejandro
• Data de Publicação: 2020
• Outros Autores: González-Herrera, Luis Gabriel, Londoño-Gil, Marisol, Rincón Flórez, Juan Carlos, López-Herrera, Albeiro
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Semina. Ciências Agrárias (Online)
• Texto Completo: https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/38568
• topic: Efeitos ambientais; Modelos de crescimento; Raça crioula; Sorologia.

The cattle breed Blanco Orejinegro (BON) is an important animal genetic resource in Colombia that needs to be studied to identify its productive benefits for Colombian livestock. The aim of this work was to establish the best linear model that explains the variability for birth weight, weaning weight and yearling weight, and estimate the effect of the serological status for Bovine Viral Diarrhea (BVD) and Bovine Leukosis (BL) in BON cattle in Colombia. The information on animal weighings belonging to 14 BON cattle herds, was collected and cleansed. Using the least squares method, 12 linear models were evaluated including as fixed effects, factors such as herd, sex, weighing month, birth order, season (rainy or dry), birth year, and contemporary group (formed by the concatenation of the factors herd, sex, and birth year). The weighing age was included as a covariate for weaning and yearling weights. For the selection of a model that best describes each parameter, the criteria for choosing models, such as Akaike information criterion (AIC), Bayesian Information criterion (BIC), coefficient of determination (R2), and the sum of squares of the error (SSE), were considered. The model that included the contemporary group showed the best fit, being also the best to describe the three parameters evaluated, since, of the four criteria considered for its evaluation, AIC and SSE showed the lowest values and the highest R2. With this model, weight predictions with higher precision were able to be performed. Employing indirect ELISA screening tests of blood plasma, the serological status of each animal was estimated for BVD and BL viral infections. The serological status of these two viral infections was included in the best-fit model. There was no significant effect of the serological status on the parameters evaluated, so there are indications that animals that came in contact with the virus were not affected during growth.