Comparing nonlinear mixed models for genetic evaluation of lactation curves in dairy goats

• Ano de defesa: 2017
• Autor(a) principal: Siqueira, Otávio Henrique Gomes Barbosa Dias de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Federal de Viçosa
• Palavras-chave em Português: Caprinos; Lactação; Genética e Melhoramento dos Animais Domésticos
• Link de acesso: http://www.locus.ufv.br/handle/123456789/18794

Knowledge on lactation curve is essential to validate the genetics, nutritional and reproductive adopted management, since it allows the evaluation of animals before the end of yielding, saving resources. By comparing the shape of curves among different groups of animals (genetic group, ages, herds and other treatments of interest), it is possible to access the effectiveness of the lactations, thus providing information for selection of the more productive groups. The study of lactation curves can be more attractive by using nonlinear mixed models since it is possible to make inferences when milk collections may be irregular in time; when there is incomplete group structure; when the adjacent evaluations are more closely correlated than the others; and when the response of individuals as a function of time has increasing variance. We aimed to fit and compare fifteen nonlinear mixed models to describe lactation curve of dairy goats as well as to estimate heritability and genetic correlations for the parameters of the selected model. The dataset was provided by the Caprine sector of the Universidade Federal de Viçosa. After checking the data consistency, we used 3,856 milk yield test-day records from 535 first lactations of Saanen and Alpine goats (including crosses). In order to identify the best nonlinear mixed model, different information criteria (AIC, AICc, AICu, BIC, cAIC and AIC3) were used here. Based on these criteria, the Wood model presented the best goodness of fit, being their parameters used as phenotypic observations for genetic evaluation of lactation curves. Additionally, the Wood model was integrated to calculate the total milk yield (TMY) that was also included in the genetic analysis. For this, a multi-trait mixed model was fitted by considering as traits the TMY and the a, b and c parameters of Wood model. The heritability estimates for TMY, a, b and c were 0.31, 0.17, 0.11 and 0,08, respectively. The genetic correlation between TMY and the parameters a, b and c were, 0.28, 0.22 and 0.17. Based on these results, the trait TMY can be indicated as selection criterion in dairy goats breeding programs, however the parameters of Wood model are not recommended to this aim.