title: Coupling of image analysis and tenderness classification to simultaneously evaluate carcass cutability, longissimus area, subprimal cut weights, and tenderness of beef.
abstract: The present experiment was conducted to determine whether image analysis of the 12th-rib cross-section used for tenderness classification could accurately predict carcass cutability, longissimus area, and subprimal cut weights. The right side of crossbred steer and heifer carcasses (n=66) was fabricated, and the yield of totally trimmed retail product was determined. Following procedures that we have described for tenderness classification, a 2.54-cm-thick steak was removed from the 12th-rib region of the left side of each carcass, and image analysis was conducted using off-the-shelf technology. Image analysis accounted for more of the variation in retail product yield (RPYD; 89 vs 77%) and retail product weight (95 vs 90%) than did calculated yield grade. Also, image analysis accurately predicted longissimus area (R2=.88). For most subprimals, the combination of image analysis-predicted RPYD and hot carcass weight (HCW) accounted for more of the variation in subprimal weight than did the combination of calculated yield grade and HCW. Whereas HCW, by itself, accounted for only 30 to 34% of the variation in weights of round cuts, the combination of image analysis-predicted RPYD and HCW accounted for 78 to 82% of the variation in weights of round cuts. Hot carcass weight, the combination of calculated yield grade and HCW, and the combination of image analysis-predicted RPYD and HCW accounted for 54, 83, and 91% of the variation in the weight of 80% lean trimmings. Thus, image analysis could be used by the beef industry to more accurately predict individual subprimal weights. In turn, that information and appropriate price extensions could be used to more accurately estimate carcass value. Thus, image analysis could be used by the beef industry in combination with tenderness classification to accurately characterize beef carcasses for cutability and tenderness. These tools should help facilitate the development of value-based marketing systems.
authors.affiliation: Roman L. Hruska U.S. Meat Animal Research Center, ARS, USDA, Clay Center, NE 68933-0166, USA. shackelford@email.marc.usda.gov
authors.forename: S D
authors.initials: SD
authors.lastname: Shackelford
authors.forename: T L
authors.initials: TL
authors.lastname: Wheeler
authors.forename: M
authors.initials: M
authors.lastname: Koohmaraie
mesh_terms: D000273:Adipose Tissue / Q000033:anatomy & histology; D000818:Animals; D002417:Cattle; D005260:Female; D007091:Image Processing, Computer-Assisted; D008297:Male; D008460:Meat / Q000592:standards*; D018482:Muscle, Skeletal / Q000033:anatomy & histology; D012044:Regression Analysis