Retail Beef Yield Lead-In Project – Year 1 Data Collection

Summary

Dressing percentage and saleable meat yield are key economic drivers for the Australian beef industry. The estimate breeding value (EBV) for retail beef yield (RBY%) is the selection criteria that underpins these profit drivers. The RBY% EBV is estimated almost exclusively from correlations with liveweight and live animal scanned eye muscle area (EMA) and fat depths due to limited recording of abattoir carcase data and actual RBY% phenotypes. Since the original correlations were calculated in 2001, selection has led to large genetic increases in liveweight and EMA, and smaller changes in fat traits, while RBY% has remained relatively stagnant. It is possible that these genetic changes have impacted the correlations between these traits.

The Angus Australia and MLA co-funded Angus Sire Benchmarking Project (ASBP) provides a unique opportunity to collect quality RBY% data. The animals in this project have Angus Australia registered sires with close genetic links to current industry populations, have extensive phenotypic records collected from birth to slaughter, and are genotyped as part of that project. This project was conducted as a lead-in to a larger project, and to ensure the opportunity was not lost to collect retail beef yield and related data on available animals from the Angus Sire Benchmarking Project.

Retail bone out data was collected on 154 ASBP Cohort 5 (2015 born) steers from the NSW DPI Glen Innes and Trangie research cow herds in April 2017 at John Dee, Warwick abattoir. Following commercial AUS-MEAT carcase preparation, carcases were weighed and hot P8 fat depth recorded. Carcases were tagged and chilled overnight, and Meat Standards Australia (MSA) carcase grading data collected by registered MSA graders on the right hand sides the following morning prior to bone out. A standard set of AUS-MEAT boneless primals and standard trim of 10mm fat were selected for bone out of the right sides.

This small group of steers displayed substantial variation in weight, fatness and RBY%. Correlations between fat measures and RBY% were negative, and correlations between EMA and muscle score were positive. Correlations between RBY% and IMF% scan data were negative but low, and the correlations between RBY% and carcase measures of marbling or IMF% measured in the lab were very low. The correlation between RBY% and MSA Index was also very low. Regressions using animal liveweight, live ultrasound scan data and live assessment of muscle score accounted for 19.9% to 30.4% of the variation in actual RBY% at slaughter. The regression using carcase weight, carcase fat and EMA measurements, and the live muscle score at feedlot entry accounted for 25.2% of the variation in RBY%.

Overall, ultrasound scan measures of fatness in the live steers and carcase measures of fatness had negative relationships with RBY%, while live and carcase measures of EMA and muscle score had positive relationships. These relationships are logical and in keeping with previously reported results and the RBY% correlations used in BREEPLAN.

While the dataset is too small to use to assess genetic parameters, this is likely to be feasible once the number of records increases towards 1,000 in the large project. This small data set will be a valuable addition to BREEDPLAN, and will be included in the mid-December Angus BREEDPLAN analysis.

Collecting RBY% data on these steers provided a useful preparatory step in the planning towards conducting RBY% data collection on 1000 animals.