A bayesian model for the analysis of lactation curves of dairy goats

This article aims to determine the effect of certain covariates, such as season of kidding, parity, and time of kidding on the characteristics of the lactation curve of Saanen dairy goats. Characteristics investigated are peak milk yield, time of peak milk yield, total milk production, persistency, and the relationship between fat and protein in milk composition, as well as between lactation curves of the same animal in successive years. The analysis is carried out using a hierarchical Bayesian approach, together with Wood’s model, to model lactation. Posterior distributions of quantities of interest are obtained by means of the Markov chain Monte Carlo (MCMC) methods. These clearly illustrate the significant effect of especially parity, but also season and time of kidding on the characteristics of the lactation curve. Total and peak milk yield increase with increasing parity up to about the third or fourth parity, while peak yield is later for first than for later parities. The analysis also enables estimation of lactation characteristics of untested animals, prediction of future characteristics and identification of exceptional animals.