Abstract
Simple SummaryCarcass classification and grading systems are typically inadequate for young cattle processed for beef production. Conformation of the hindquarter region of cattle has been used to classify and grade the whole carcass from older beef cattle. This study was initiated with the objective of providing a carcass classification and grading system based on hind-leg muscles weight. Prediction equations for the indirect prediction of saleable meat yield using hind-leg muscles weight from young dairy-origin steers were developed, and could be used for their carcass classification and grading. These equations avoid the need to isolate and track boneless subprimal cuts to establish the saleable meat yield of individual animals.Prediction equations have been widely utilized for carcass classification and grading systems in older beef cattle. However, the equations are mostly relevant for common beef breeds and 18 to 24 month old animals; there are no equations suitable for yearling, dairy-origin cattle. Therefore, this study developed prediction models using 60 dairy-origin, 8 to 12 month old steers to indicate saleable meat yield from hind-legs, which would assist with carcass classification and grading. Fat depth over the rump, rib fat depth, and eye muscle area between the 12th and 13th ribs were measured using ultrasound, and wither height was recorded one week prior to slaughter. The muscles from the hind-leg were retrieved 24 h after slaughter. Prediction equations were modeled for the hind-leg muscles weight using carcass weight, wither height, eye muscle area, rump, and rib fat depths as predictors. Carcass weight explained 61.5% of the variation in hind-leg muscles weight, and eye muscle area explained 39.9% (p < 0.05). Their combination in multivariate analysis explained 63.5% of the variation in hind-leg muscles weight. The R2 of the prediction in univariate and multivariate analyses was improved when data were analyzed per age group. Additional explanatory traits for yearling steers, including body length, hearth girth, and muscle depth and dimensions measured using video image analysis scanning (VIAscan), could improve the prediction ability of saleable meat yield from yearling dairy beef steers across the slaughter age groups.
Highlights
In 2018, global beef production was estimated at 72.1 million tonnes, representing 22.5% of total meat production [1]
Beef production increasingly utilizes calves originating from the dairy industry [2,3], which is partly due to the expansion of dairy farming producing an Animals 2020, 10, 651; doi:10.3390/ani10040651
In New Zealand, 65% of the annual beef production is sourced from dairy-origin cattle [5], and the dairy industry supplies 35% to 40% of annual calves required for beef finishing [4]
Summary
In 2018, global beef production was estimated at 72.1 million tonnes (carcass weight equivalent), representing 22.5% of total meat production [1]. Beef production increasingly utilizes calves originating from the dairy industry [2,3], which is partly due to the expansion of dairy farming producing an Animals 2020, 10, 651; doi:10.3390/ani10040651 www.mdpi.com/journal/animals. In New Zealand, 65% of the annual beef production is sourced from dairy-origin cattle [5], and the dairy industry supplies 35% to 40% of annual calves required for beef finishing [4]. Calves are produced in excess of the dairy herd’s replacement requirements. These calves may go to beef finishing farms or be processed for veal or pet-food [2,5]. In New Zealand, 1.7 million calves from the dairy industry were commercially processed at 4 to 8 days of age in 2018 [5]
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