Factors that influence the test day milk yield and composition

• Autor(a) principal: Silva, F.G.
• Data de Publicação: 2013
• Outros Autores: Brito, L.F., Torres, R.A., Ribeiro Júnior, J.I., Oliveira, H.R., Caetano, G.C., Rodrigues, M.T.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: LOCUS Repositório Institucional da UFV
• Texto Completo: http://dx.doi.org/10.4238/2013.13.5; http://www.locus.ufv.br/handle/123456789/12899
• topic: Genetic grouping; Season-year; Type of kidding

The objective of this research was to study the factors that influence the test day milk yield (TDMY) and percentages of protein, fat, lactose, and total dry extract obtained on test day. We evaluated 110,732 weekly milk production records from 1496 goats and 19,271 monthly milk constituent records from 1245 Alpine and Saanen goats, which were collected from 1997 to 2010 in the goat sector at Universidade Federal de Viçosa. To ensure greater record reliability, only lactation data with kidding order between 1 to 6, type of kidding data including 0 to 3 kids, milk control years after 1997, and genetic groupings other than types 7 or 9 were considered, due to the relative lack of information recorded for some classes of these factors. Data in which the reported milk days were less than 7 or greater than 315 were also eliminated. Goats aged greater than 300 days at calving and those aged less than 6 years at control were considered in this study. Milk production was higher in the dry season in comparison to the rainy season. Genetic grouping did not influence all traits in both breedings. The TDMY tended to increase along with increasing age of the goats at kidding, while the opposite trend was observed relative to kidding order. Factors that significantly influenced all of the studied traits varied, and the factors that significantly influenced each trait were altered between the relationship of Alpine and Saanen breeds. Thus, the analysis of factors that influence traits to be evaluated in the herd under study is critical for defining the best evaluation model.