Estimation of genetic parameters for production traits and somatic cell score in Iranian Holstein dairy cattle using random regression model

In this study test-day records of milk (kg), fat (g), and protein (g) yields, somatic cell score (SCS, cells/ML) collected by Animal Breeding Center of Iran during 2007 and 2009 were used to estimate genetic parameters using random regression model. Models with different order of Legendre polynomials were compared using Bayesian information criterion (BIC).For milk, fat yield and SCS genetic and permanent environmental effects were modeled with 3th order of Legendre polynomials and for protein yield genetic and permanent environmental effects were modeled with 4th and 3rd order of Legendre polynomials, respectively. The mean heritability for milk, fat, protein yield and SCS were 0.24, 0.12, 0.23 and 0.07, respectively. For all the traits except for SCS, the estimated heritabilities were lowest at the beginning and higher at the end of the lactation period. Around peak yield (DIM 50 to 150), heritability was lowest for all traits and then increased to the end of lactation. Phenotypic correlations were high between adjacent yields and small between yields at the extremes of the lactation curve. Negative genetic correlations were observed between tests at the beginning and at the end of lactation in this research. The present study showed clear evidence for the benefits of using a random regression TD model for management decisions.