Abstract

Video images of ham cross-sections were recorded from 71 pork carcasses (ranging in weight from 72 to 119kg). Three sets of prediction equations were developed to estimate pork carcass lean and fat composition from video image analysis (VIA) of ham cross-sectional area measurements, 10th rib back fat depth (TENFAT) and hot carcass weight (HCKg). Carcass data of dissected lean and fat in the four primal cuts (ham, loin, Boston button and picnic shoulder) were used as dependent variables in establishing regression equations. The first set of equations combined VIA ham measurements and total ham weight (HTKg). Regression models containing the single variable HTKg times ham percentage lean area (Vol. 1) or HTKg times ham percentage fat area (Vol. 2) accounted for 88% and 68% of the variation in total carcass lean weight (CLKg) and total carcass fat weight (CFKg) from the right side of each carcass, respectively. The second set of equations combined VIA ham measurements and TENFAT (cm). Multiple regression models involving TENFAT, Vol. 1, and Vol. 2 accounted for 91% and 90% of the variation in CLKg and CFKg. The third set of equations used VIA ham measurements, TENFAT and HCKg. Carcass lean weight was best predicted by HCKg, TENFAT, and ham lean area (HLA) (R(2)=.92). Carcass fat weight was best predicted by HCKg, TENFAT, and Vol. 2 (R(2)=.91). Overall correlations showed a high association between Vol. 1 and CLKg (r=.94, P<.0001) and Vol. 2 and CFKg (r=.83, P<.0001). Ham lean area was related to CLKg (r=.74, P<.0001) and ham fat area to CFKg (r=.81, P<.0001). The results of this study indicated video image analysis of ham cross-section slices combined with backfat depth at the 10th rib can be used for accurate estimation of total carcass lean or fat composition.

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