Single-trait (SAM) and mutti-trait (IMAM) animal model were compared using the data of 90-day (M90) and 305-days (M205) milk yield of 985 of Hoistein-Friesian cows daughters of 104 sires and 985 dams in Egypt. Data included 985 first lactation record& Total number was 5642 fcr all lactations. Animal model in both single- and multi-trait contained season. year of calving, classes of age at calving and days open as fixed effects and animal and residual as random effects_ The variablity in predicted breeding value. PBV (i.e., range from maximum — minmum) was large for IvIAM in first lactation, however, the reverse trend was found in all lactations (i.e,, ranges of PBV in SAM was larger than the estimates from IMAM). Using MAM decreased the standard error of prediction (SEP) and consequently the accuracy (r-ri) increased . Closeness between rpm and rs of both SAM and MAM prove that any model may be effective in the evaluation of sires, darns and cows. Using records of all lactation reduced SEP in both SAM and MANI procedures than those of first lactation only, lnorasing accuracy with alliactations was markedly pronounced when compared with the first lactation, increasing information from all lactations has a direct effect toward increasing the accuracy (ra) of the all lactation than using only first lactation. Disclosness between correlations (rpm & rs) of PBV and ranks in first and all lactations, indicate that the sires, dams and cows were reranked when using first lactation and all lactation records. Part-lactation yields (M90) in both first and all lactation records proved to be a good parameter in estimating sire genetic values without complications and would also afford an opportunity for a faster return for sires. Reduction in sires, dams and cows SEP by using M90 compared with M305 using either SAM or MAM provided a considerable potential for rapid genetic progress through sire selection. (i.e. there is a considerable potential for improving milk production through selection of bull or bull-dam's of Holstein population).
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