Author
Norman, H | |
Wright, Janice | |
Vanraden, Paul | |
Cole, John |
Submitted to: Journal of Dairy Science
Publication Type: Abstract Only Publication Acceptance Date: 3/5/2007 Publication Date: 7/8/2007 Citation: Norman, H.D., Wright, J.R., Van Raden, P.M., Cole, J.B. 2007. Effect of service sire and cow sire on gestation length. Journal of Dairy Science. 90(Suppl. 1):194(abstr. 230). Interpretive Summary: Technical Abstract: Recent studies have examined environmental factors affecting gestation length (GL) and derived estimates of variance components for service sire and sire of daughters in heifers and cows. These studies show that bull differences exist, thus providing the opportunity to change GL. Predictors for Holstein bulls as either service sire or sire of daughters were derived using calvings from 1999 through 2005. Effects included in the model were year, herd-year, calving month, age x parity, multiple birth x calf gender, cow’s days in milk, cow’s milk yield, dam’s and calf’s sires, and cow. All effects except sires (2) and cow were fixed. Frequencies of predictors for all bulls and those currently marketed through artificial insemination service (active AI bulls) having >=100 daughters with GL were examined. Standard deviations (SD) of bulls’ GL on heifers (parity 1) and cows (parities 2 to 5) were 1.43 and 1.32 d from service sire predictors for all bulls (323), respectively; likewise, SD of bulls GL were 0.75 and 0.78 d from predictors of sires of cows for all bulls (397). The correlation between predictors for service sire and sire of daughters from the heifer subset were 0.63 for all bulls (192) and 0.49 for active-AI bulls (58); the equivalent correlations from cows were 0.69 and 0.70 (2441 and 151 bulls). The regressions were from 0.24 to 1.43. The correlation between predictors for service sires between heifers and cows were 0.96 from all bulls (323) and 0.97 from active-AI bulls (137). Likewise, the correlation between predictors for sire of daughters between heifers and cows were 0.83 and 0.83 from all (397) and active AI bulls (67). These regressions ranged from 0.73 to 0.94. It is likely that genetic information for GL can be useful, but at present it seems that substantially more research is needed to determine the potential consequences either from selection for shorter or longer gestation lengths. |