PSIV-26 Late-Breaking: Evaluation of a genome-based sorting system for feeder cattle.

Abstract

This study evaluated the use of molecular breeding values (MBVs) for carcass traits to sort steers into quality grid and lean meat yield groups. A training set of 2300 animals with genotypes and phenotypes was used to predict MBVs for lean meat yield (LMY) and marbling score (MBS) for 299 Angus, 181 Charolais and 638 Kinsella composite steers using the genomic best linear unbiased prediction method. Steers were placed into MBV-Quality, MBV-Lean, MBV-Marbling and MBV-Other groups on the basis of predicted MBV for LMY and MBS being jointly greater or less than the mean MBV values for both traits. Carcass phenotypes of the steers were then collected and evaluated for consistency with the assigned group using descriptive statistics. Also, the accuracy of genomic predictions was assessed as the additive genetic correlation from a bivariate animal model that fits the observed carcass phenotype and the predicted MBV. The number of steers that met the expected carcass outcome was counted to produce actual percentages for each MBV group. Results showed that on average, MBV-Quality and MBV-Marbling groups had heavier carcasses, greater backfat and more marbling across the three populations while MBV-Lean had leaner carcasses. For most traits, the coefficient of variation suggested less variability and uniform carcass in the MBV-Marbling followed by MBV-Lean and MBV-Quality groups. Greater than 70% of the steers in the MBV-Quality, MBV-Lean and MBV-Marbling groups reached the desired carcass outcome of 70:70 Quality Grid and Y1-lean meat yield in Angus and Charolais but not for Kinsella composite. The accuracy of genomic prediction showed that the MBVs could predict from 60 to 80% of the observed carcass trait values. Thus, genomic profiles can potentially help to streamline the feedlot-finishing process and improve the quality and consistency of beef carcasses.