Search

Heifer pregnancy (HPG) and Stayability (STAY) are female reproductive traits that have EPD reported by the Red Angus Association of America. Challenges arise when making genetic predictions for these traits. Specifically, HPG and STAY phenotypes can only be collected on females retained in the breeding herd and have low heritability estimates. Additionally, STAY is measured late in an animal's life. The objective of this research was to investigate the genetic relationships between HPG or STAY and 13 other traits, which included measurements of growth, carcass, ultrasound, and scrotal circumference. For STAY relationships between mature weight (MW), body condition score (BCS), teat score (TS), and udder suspension score (US) were also evaluated. Data from 142,146 and 164,235 animals were used in the analyses for HPG and STAY, respectively. Genetic relationships were investigated using a series of 2 trait animal models and a REML procedure. In all analyses, the appropriate contemporary groups were included as a fixed effect, and direct genetic as a random effect. Additional fixed effects included as follows: sex for weight, carcass and ultrasound traits, age of dam for weight traits, and age of measurement for ultrasound, carcass, BCS, udder traits, and MW. Maternal genetic effects for preweaning gain (Pre-WG), weaning weight (WW), and yearling weight (YW) were also modeled. Permanent environmental effects of the dam were modeled for the traits Pre-WG and WW. Permanent environment of the individual for the traits MW, BCS, TS, and US was also included. Heritability estimates were 0.12 ± 0.01 and 0.10 ± 0.01 for HPG and STAY, respectively. Heritability estimates for direct genetic effects of production traits were moderate to high in magnitude, maternal heritability estimates were low, and permanent environmental effects accounted for 0.00 to 0.18 of the total variation. The strongest genetic correlations were those among Pre-WGD (0.24 ± 0.08), WWD (0.18 ± 0.08), YWD (0.20 ± 0.07), ultrasound rib eye area direct (0.16 ± 0.08), and ultrasound backfat direct (0.14 ± 0.08) and HPG. The highest genetic correlations were between STAY and WWM (0.54 ± 0.05), YWM (0.36 ± 0.07), backfat (0.53 ± 0.20), marbling score (0.40 ± 0.20), UREA (0.19 ± 0.07), ultrasound backfat (0.37 ± 0.07), TS (0.30 ± 0.11), and US (0.23 ± 0.11). Relationships between HPG or STAY and other traits were minimal. These results suggest that genetic relationships exist between HPG or STAY and other more densely recorded traits.

The Beef Improvement Federation recommends residual feed intake (RFI) be calculated from 70-d tests preceded by a 21-d adjustment period. Individual animal feed intake and gain measurements are expensive and time consuming, which limits the number of animals available for national genetic evaluation of feed intake. If a shorter test period of comparable accuracy could be used, the cost would decrease and more animals could be tested annually. The objective of this study was to determine if data from shortened tests is equally as predictive of average daily DMI (ADMI) and RFI values from 70-d tests. Feed intake and weight measures were collected after weaning from Bos taurus bulls, steers, and heifers (n = 612) during four 70-d performance tests. For each individual, ADMI and RFI were calculated. Residual feed intake was calculated by regressing ADMI on metabolic midweight (MMWT) and ADG with the effect of breed included where appropriate. Based on four 70-d intake tests, ADMI, RFI, ADG, and MMWT were evaluated using shortened test lengths in a post hoc analysis where shortened test lengths were imposed on the full-period tests. The ADMI, RFI, ADG, and MMWT values from the full 70-d test were regressed on ADMI, RFI, ADG, and MMWT values resulting from the constructed shorter data subsets. The 8 subsets ranged from 14 to 56 d in length. The fixed effects of test, breed, animal's origin, and sex were included in each comparison for ADMI, ADG, and MMWT. Estimates for regression coefficients of ADMI values from a full test on various subsets ranged from 0.63 to 1.02. Likewise, estimated coefficients obtained from the regression of full test RFI, ADG, and MMWT values on subsets ranged from 0.50 to 1.00, 0.09 to 0.85, and 0.48 to 1.02, respectively. We conclude that ADMI values from a 42-d test ( < 0.0001) and RFI values from a 56-d test (P < 0.0001) adequately predict ADMI and RFI when compared to a 70-d test. These results suggest that testing periods of 42 d for determining ADMI and 56 d for RFI could ultimately reduce testing costs and result in collection of data on a larger number of animals per year, in turn resulting in more data for genetic evaluation.

Maintenance energy requirements of cattle can be predicted from published equations utilizing metabolic BW and milk production potential. Metabolic BW is a function of BW at a constant fat percentage or BCS. Pedigree and performance records can be used in random regression models to predict genetic merit for metabolic BW and milk production potentials. The purpose of this study was to present a methodology for predicting mature cow maintenance energy EPD using mature cow BW and BCS and accounting for prior selection of replacement females at weaning and yearling ages. Variance components were obtained for direct and maternal effects on weaning weight, direct effects on postweaning BW gain, and direct coefficients for random regression on mature weights (MW) adjusted for BCS. These BW were transformed into metabolic BW by taking BW to the power of 0.75, variance components were estimated for metabolic BW, and were then used to predict breeding values from which cow maintenance energy EPD could be derived. Data used in this analysis were obtained from the Red Angus Association of America and limited to herds with MW and corresponding BCS observations. The data set included 52,338 BW records on 21,103 individuals. Weaning and yearling contemporaries to those with MW observations, but with no MW records themselves, were included to account for selection occurring before maturity. Heritability estimates for weaning weight direct, weaning weight maternal, and postweaning BW gain were 0.18 +/- 0.02, 0.16 +/- 0.02, and 0.18 +/- 0.02, respectively. Mature BW observed at 2, 3, 4, 5, and 6 yr of age had heritability estimates of 0.45 +/- 0.03, 0.44 +/- 0.03, 0.49 +/- 0.03, 0.66 +/- 0.04, and 0.62 +/- 0.05, respectively. Correlations between weaning weight direct and MW ranged from 0.65 +/- 0.07 to 0.82 +/- 0.04, and correlations between MW at different ages ranged from 0.95 +/- 0.03 to 0.99 +/- 0.01. The genetic correlations between postweaning BW gain and MW ranged from 0.48 +/- 0.06 to 0.59 +/- 0.06. The 15-yr genetic increase in metabolic BW was 3.6 kg(0.75), greater than the value of 0.23 kg(0.75) obtained from the same data ignoring weaning and yearling contemporaries with unobserved MW, the approach currently used in the derivation of cow maintenance EPD published by the Red Angus Association of America.

In good environments, cow intake is sufficient for their own growth and for milk production to support their calf. In poor environments, cows lose BW or may reduce milk supply to maintain themselves. Heritability for direct genetic and maternal components of weaning weight as well as the correlations between these components might be expected to vary according to these circumstances. The purpose of this study was to estimate heritability and genetic correlations for the direct genetic and maternal components of weaning weight classified in 2 environments according to maternal BW gain and to identify whether a single heritability estimate is appropriate for the differing environments experienced by cows from year to year. Data used in this analysis was obtained from the Red Angus Association of America and consisted of 96,064 cow BW observations and 27,534 calf weaning weight observations. A dam's change in BW from one year to the next was used to classify each calf's weaning weight into 1 of 2 environmental groups, those being good or poor. Best linear unbiased estimates of the change in cow BW with age were obtained from analysis of cow BW using a repeatability model. If the phenotypic change in cow BW exceeded this average BW change, the calf's weaning weight associated with the end of this time frame was classified as having been observed in a good environment. If not, the calf's corresponding weaning weight was classified as having occurred in a poorer than average environment. Heritability estimates of 0.24 +/- 0.03, 0.24 +/- 0.03, 0.13 +/- 0.02, and 0.14 +/- 0.02 were obtained for weaning weight good direct, poor direct, good maternal, and poor maternal, respectively. Correlations between direct genetic and maternal weaning weight components in the good and poor environments were -0.47 +/- 0.08 and -0.20 +/- 0.09, respectively. These variance components are not sufficiently distinct to warrant accounting for dam nutritional environment in national cattle evaluation.