Prediction of the Hind-Leg Muscles Weight of Yearling Dairy-Beef Steers Using Carcass Weight, Wither Height and Ultrasound Carcass Measurements

Abstract

Simple Summary: Carcass 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.Abstract: 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 R 2 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.

Optimization of Profit for Pasture-Based Beef Cattle and Sheep Farming Using Linear Programming: Young Beef Cattle Production in New Zealand

“…There is no carcass classification and grading system for young beef cattle in New Zealand [26] and the current study processed them as one class [25] at manufacturing beef price (NZ$4.50) [50]. A premium price of NZ$5.00 per kg carcass by targeting different markets was simulated [24].…”

“…Previous studies have examined the growth performance and carcass quality of young steers slaughtered at the ages of 8, 10 and 12 months [24][25][26] and the growth and carcass performance of young steers vs bulls slaughtered at 11 months of age from dairy-origin cattle in New Zealand [44]. Young steers and bulls were shown to have the same growth rate and carcass weight [44].…”

“…The concept of young beef production in a New Zealand setting would utilize dairyorigin cattle slaughtered less than 14 months of age [24][25][26]. It would potentially allow a greater number of cattle to be managed in grazing systems for beef production and provide a faster rotation of animals from birth to slaughter [27,28].…”

Objective carcass measurement technologies: Latest developments and future trends

“…Even though this technology is very advanced in pigs (suitable on-line due to wet skin after the scalding process ensuring good acoustic contact), the same technology cannot be implemented on beef or sheep carcass due to air pockets following de-hiding which would impede proper access of the sound energy (Allen, 2009). Addis et al (2020) tried to predict hind-leg muscles weight of yearling dairy-beef steers with ultrasound measurements of EMA obtaining low percentage of variability explained (39.9%). Therefore, it is likely that applications on sheep and beef will only be useful on live animals, while it is a successful pig carcass grading technology.…”