Research Article

Non-additive genetic effects on weights and performance of a Brazilian Bos taurus x Bos indicus beef composite

Published: October 28, 2008
Genet. Mol. Res. 7 (4) : 1156-1163 DOI: 10.4238/vol7-4gmr501

Abstract

The aim of the present study was to evaluate the heterosis effects on weaning weight at 205 days (WW, n = 146,464), yearling weight at 390 days (YW, n = 69,315) and weight gain from weaning to yearling (WG, n = 59,307) in composite beef cattle. The fixed models were: RM, which included contemporary groups, class of age of dam, outcrossing percentages for direct and maternal effects, and additive direct and maternal (AM) breed effects; R, RM model, minus AM breed effects, and H, RM model, minus additive breed effects. The estimates for W205 were in general positive (P 0.01). The R and H models resulted in similar estimates, but they were very different from the ones estimated by the RM model. For W390, the R and H models resulted in general positive estimates (P 0.05). For WG, the RM model resulted in
general significant heterosis effects (P 0.05). It can be concluded that the RM model seems to supply estimates of better quality (P 0.01).

The aim of the present study was to evaluate the heterosis effects on weaning weight at 205 days (WW, n = 146,464), yearling weight at 390 days (YW, n = 69,315) and weight gain from weaning to yearling (WG, n = 59,307) in composite beef cattle. The fixed models were: RM, which included contemporary groups, class of age of dam, outcrossing percentages for direct and maternal effects, and additive direct and maternal (AM) breed effects; R, RM model, minus AM breed effects, and H, RM model, minus additive breed effects. The estimates for W205 were in general positive (P 0.01). The R and H models resulted in similar estimates, but they were very different from the ones estimated by the RM model. For W390, the R and H models resulted in general positive estimates (P 0.05). For WG, the RM model resulted in
general significant heterosis effects (P 0.05). It can be concluded that the RM model seems to supply estimates of better quality (P 0.01).