Estimation of Genetic Trend for Milk, Fat and Protein Traits in 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. Based on obtained results, RRM with SPL6 (6,6), SPC6 (6,6) and LEG (3,5) for milk yield, SPL6 (6,6), SPQ6 (6,6), LEG (3,5) for fat yield and 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 (0.10, 0.05 and 0.09 for milk, fat and protein yields, respectively). The genetic trend of milk yields was showed an increasing during the 10 past years, which indicated Iranian Holstein dairy cattle population genetically was improved for milk yields.