Mathematical Models to Describe the Lactation Curves of Protein Trait of Iranian Holstein Dairy Cattle

The objective of this study was to compare the goodness of fit of lactation curve models; Wood, Wilmink, Linear Splines (SPL), Cubic Splines (SPC), Quadratic Splines (SPQ), Cobby and Le Du, Ali Schaeffer and Legendre Polynomial (LEG), in random regression model (RRM) for milk production traits of Iranian Holstein dairy cattle. For this purpose the records obtained from Test-day (TD) regarding milk (928513), fat (788577) and protein (653317) yields related to their first parity were used. These data collected from the years of 2003 to 2011 by the Karaj breeding center of Iran. The genetic parameters were estimated using REML method using WOMBAT software. To compare the model, different criterion (-2Logl, AIC, BIC,LRT) were used for protein trait. Based on obtained results, RRM with SPL5 (5,5), SPQ4 (4,4) and LEG (3,4) for protein yield, were selected as better model to describe the lactation curves. The estimated heritabilities by best models were lower in the beginning lactation than other during lactation (0.09 for protein yield). Additive genetic correlation between adjacent test days was more than between distant test days.

Keywords:

Dairy cattle , Random Regression Model , Protein Yield