Morehead State University
The Use of Real-time Ultrasound and Predictive Software to Estimate Carcass Yield and Quality of Fed Cattle
Institution
Morehead State University
Faculty Advisor/ Mentor
Benjamin C. Williamson; Rebecca S. Miculinch
Abstract
Use of real-time ultrasound as a means of predicting endpoints of fed-cattle has shown variable results. Sixty-four crossbred steers and heifers (276 ± 42 kg) were grouped based on similar endpoints that would result in maximum carcass value. Body measurements of rib fat (RF), percent intramuscular fat (IMF), and longissimus muscle depth (LMD) were recorded using realtime ultrasound one week prior to transport to a commercial feedyard in Iowa; predicted carcass composition was estimated (Cattle Performance Enhancement Co., Stratford, TX). Cattle were harvested when visually appraised to have 1 cm of RF. Carcass parameters were recorded for hot carcass weight (HCW), yield grade (YG), and quality grade (QG). Pearson square correlations were used to determine the relationship between predicted carcass measurements, carcass grades, HCW, and performance parameters. Predicted HCW correlated (P < 0.05) with actual HCW and final BW (r = 0.30 and 0.29, respectively). Yield grade correlated (P < 0.01) with predicted RF (r = 0.33) and tended (P < 0.06) to be correlated with the probability of grading prime (r = 0.24). Predicted final BW correlated (P < 0.01) with HCW (r = 0.31) and final BW (r = 0.30): HCW and final BW tended (P < 0.10) to be inversely correlated with predicted IMF (r = -0.22 and -0.23, respectively). Ultrasound IMF correlated (P < 0.05) with YG (r = 0.25). Predicted carcass composition correlated with carcass grid values, actual HCW, and final BW. Carcass predictive software may be an effective tool in uniformly marketing cattle.
The Use of Real-time Ultrasound and Predictive Software to Estimate Carcass Yield and Quality of Fed Cattle
Use of real-time ultrasound as a means of predicting endpoints of fed-cattle has shown variable results. Sixty-four crossbred steers and heifers (276 ± 42 kg) were grouped based on similar endpoints that would result in maximum carcass value. Body measurements of rib fat (RF), percent intramuscular fat (IMF), and longissimus muscle depth (LMD) were recorded using realtime ultrasound one week prior to transport to a commercial feedyard in Iowa; predicted carcass composition was estimated (Cattle Performance Enhancement Co., Stratford, TX). Cattle were harvested when visually appraised to have 1 cm of RF. Carcass parameters were recorded for hot carcass weight (HCW), yield grade (YG), and quality grade (QG). Pearson square correlations were used to determine the relationship between predicted carcass measurements, carcass grades, HCW, and performance parameters. Predicted HCW correlated (P < 0.05) with actual HCW and final BW (r = 0.30 and 0.29, respectively). Yield grade correlated (P < 0.01) with predicted RF (r = 0.33) and tended (P < 0.06) to be correlated with the probability of grading prime (r = 0.24). Predicted final BW correlated (P < 0.01) with HCW (r = 0.31) and final BW (r = 0.30): HCW and final BW tended (P < 0.10) to be inversely correlated with predicted IMF (r = -0.22 and -0.23, respectively). Ultrasound IMF correlated (P < 0.05) with YG (r = 0.25). Predicted carcass composition correlated with carcass grid values, actual HCW, and final BW. Carcass predictive software may be an effective tool in uniformly marketing cattle.