ABSTRACT
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.
