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Title: 2006 BRAHMAN SIRE SUMMARY FOR CARCASS TRAITS

Author
item FRANKE, D. - LOUISIANA STATE UNIV.
item Riley, David
item PASCHAL, J. - TEXAS AG. EXP. STATION
item Chase, Chadwick - Chad

Submitted to: Brahman Journal
Publication Type: Trade Journal
Publication Acceptance Date: 5/12/2006
Publication Date: 6/12/2006
Citation: Franke, D.E., Riley, D.G., Paschal, J.C., Chase, C.C. 2006. 2006 brahman sire summary for carcass traits. Brahman Journal. 35(10):24,40.

Interpretive Summary: Progeny records from 230 Brahman sires, which included 1,719 Brahman carcasses from Louisiana, Texas, and Florida were used in conjunction with a pedigree file that included 7,365 individuals to produce an updated sire summary of Expected Progeny Differences (EPD) for beef carcass and palatability traits in the Brahman breed. Single-trait animal models were used to predict breeding values for six traits: 12th rib fat thickness, hot carcass weight, ribeye area, marbling score, percent retail yield, and Warner-Bratzler shear force (mechanical assessment of tenderness of meat after two weeks of aging; higher values indicate tougher meat). Accuracies and standard errors of prediction were used to generate possible change values (PCV) for EPD, which provide a straightforward method for bracketing a prospective sire’s true transmitting ability for one of the evaluated traits with a 68% confidence interval (EPD +/– PCV). All data were adjusted for contemporary slaughter group (year-sex-slaughter group) and to an average age of animal at slaughter. The range from low to high sire EPD for each trait in these data are similar to ranges for carcass trait EPD in other breeds. Trait leaders for each trait consisted of the 20 bulls (having at least five progeny with records) with the highest EPD for hot carcass weight, ribeye area, marbling score, and percent retail yield; and those with the lowest EPD for 12th rib fat thickness and Warner-Bratzler shear force. Brahman cattle have a reputation for poor carcass quality and beef palatability, and these results permit differentiation and selection of sires to improve these traits and therefore the marketability of straightbred and crossbred Brahman calves.

Technical Abstract: Carcass and beef palatability data was collected from 1,719 calves of 230 Brahman sires. Single trait mixed models were used to predict breeding values, and subsequent Expected Progeny Differences (EPD) for six traits: 12th rib fat thickness, hot carcass weight, ribeye area, marbling score, percent retail yield, and Warner-Bratzler shear force. All data were adjusted for contemporary slaughter group (year x sex x slaughter group) and to an average age of animal at slaughter. The animal effect was included as the only random effect, and the numerator relationship matrix included in the equations contained 7,365 individuals. Estimates of heritability produced from this data for 12th rib fat thickness, hot carcass weight, ribeye area, marbling score, percent retail yield, and Warner-Bratzler shear force were 0.44 +/– 0.08, 0.78 +/– 0.09, 0.66 +/– 0.08, 0.41 +/– 0.09, 0.51 +/– 0.11, and 0.16 +/– 0.05, respectively. The range from low to high sire EPD for each trait in these data wee similar to ranges for carcass trait EPD in other breeds. Trait leaders were identified for each trait and consisted of the 20 sires (having at least five progeny with records) with the highest EPD for hot carcass weight, ribeye area, marbling score, and percent retail yield; and those with the lowest EPD for 12th rib fat thickness and Warner-Bratzler shear force. These results are updated EPD calculated and published for the third time for beef traits in the Brahman breed. Results will facilitate improvement programs using selection by providing a convenient and well-understood method for producers. Results are especially important as Brahman cattle have the reputation for poor performance in these traits, and improvement could influence prices paid to producers for straightbred and crossbred calves and for beef from these calves. None of the EPD generated should be used for extreme single-trait selection, because it is not known how other traits would respond to such selection.