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Abstract
Records on birth (BWT), weaning (WWT), and yearling (YWT) weights on F$\sb1$ progeny from 13 sire breeds, and on weaning weight (MWWT) of top-cross progeny from 13 maternal grandsire (MGS) breeds were analyzed with three models to determine the effects of ignoring the correct model for estimation of sire breed effects. The first model included only fixed effects. The second and third analyses included random effects for sires (or MGS) and sires and dams (or daughters of MGS), respectively. Ignoring variation due to these effects resulted in underestimation of standard errors associated with contrasts among sire breeds.
A model including fixed and random effects for sires (or MGS) and dams (or daughters of MGS) was used to estimate regression coefficients of progeny performance on sire EPD (BWT, WWT, YWT, and milk = MILK (MGS only)) to be used to adjust sire breed means for time trend for calculation of across-breed EPD. Regression coefficients were similar to expected values except for YWT and MILK, which were larger than expected. Breed of sire means generally increased when adjusted for sire sampling. Factors to adjust within-breed EPD to an across-breed basis (Base breed = Angus) were largest for Brahman and Simmental sires.
Records on BWT, WWT, and YWT were obtained from six locations across the USA and analyzed for comparison with the above results. Hot carcass weight (HCWT), fat thickness (FT), ribeye area (REA), kidney, pelvic and heart fat (KPH), and marbling score (MAR) also were analyzed to obtain sire breed differences. Breed differences were pooled across locations for all traits. Sire breeds used in the two data sets ranked similarly. Regression coefficients for growth traits differed significantly from the expected value (1.0), except for WWT. Across-breed EPD adjustment factors were largest for Brahman for BWT and for Gelbvieh for WWT and YWT. Progeny of Simmental sires were among the heaviest at all weights, had the largest REA and the smallest FT. Shorthorn sires produced progeny with the largest KPH and MAR.
