Using Principal Components of the Additive Genetic Random Regression Coefficients Matrix to Modify Lactation Curve of Holstein Dairy Cattle in Iran



The objective of this study was to investigate the effect of principal components (PC) of the regression coefficients (co)variance matrix on the lactation curve, and on the formation of selection index to modify the curve, based on these PC’s, and as well to estimate additive genetic and phenotypic variances and heritability of the constructed selection index. Lactation period of 301 d (5-305) was partitioned into 10 equal stages, such that the values of weighted coefficients (unrestricted selection index) were considered the same value as of the lactation stage. In contrast, the value of weighted coefficients (restricted selection index) which were calculated based on the genetic gain in each stage of lactation. The results showed that the first PC had an impact on milk production and the second PC was associated with persistency. The third PC increased (decreased) milk production in early and late (middle) lactation and the fourth PC decreased (increased) milk production in early (late) as well as middle of second (first) part of lactation curve. Because of more emphasis on persistency and decreasing genetic gain in early lactation in compared with , the value of weighted coefficients first (third) and second (fourth) PC were decreased (increased). Because of decreasing the variance of additive genetic in due to negative genetic covariance between the stages of lactation, the heritability of (0.08) decreased in comparison with (0.33) which lead to decline genetic gain.