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Sixty left sides of pig carcasses were scanned by spiral computed tomography (CT) to measure lean meat weight and percentage. The carcasses were fully dissected and scanned to develop a calibration protocol. Different image analyses were performed on the basis of anatomically defined scans, direct volumetric estimation, body- and grey-scale ranges and using Partial Least Squares (PLS) regression of data provided by CT. The R2 values of the calibrations for lean meat weight were 0.874, 0.976, 0.983 and 0.992, respectively, depending on the method applied. The PLS proved to be the best approach with a calibration RSD of 232 g. When changing from lean meat weight to percentage, the statistical goodness drops-to a very small extent (R2 = 0.988, RSD = 0.56). According to the results, the CT method can be recommended as a reference for determining the lean meat content of pig carcasses.

This study was conducted to assess the ability of the VCS2001 (E+V, Oranienburg, Germany) video image analysis system to predict pork carcass composition. Pork carcasses (n = 278) were selected from a commercial packing plant to differ in weight, Fat-O-Meater (FOM) predicted percentage lean, and gender. Carcasses were imaged three times with the VCS2001, chilled overnight, and then sequentially fabricated into boneless subprimals. The VCS2001 accurately predicted the weight of total saleable product (R2 = 0.88, root mean square error [RMSE] = 1.84) and fat-corrected lean (R2 = 0.92, RMSE = 1.66), but autocorrelation existed between dependent and independent variables. The VCS2001 was acceptably accurate and precise in predicting weights of bone-in ham (R2 = 0.83, RMSE = 0.80), bone-in loin (R2 = 0.74, RMSE = 1.17), loin lean (R2 = 0.77, RMSE = 0.82), belly (R2 = 0.78, RMSE = 0.94), sparerib (R2 = 0.55, RMSE = 0.28), and boneless shoulder (R2 = 0.73, RMSE = 0.79). Weights were more accurately predicted than yields (as a percentage of hot carcass weight) of total saleable product (R2 = 0.47, RMSE = 1.97) or total fat-corrected lean (R2 = 0.44, RMSE = 1.89) using VCS2002, and it did not accurately predict percentages of bone-in ham (R2 = 0.45, RMSE = 1.13), ham lean (R2 = 0.32, RMSE = 1.46), bone-in loin (R2 = 0.29, RMSE = 1.36), loin lean (R2 = 0.56, RMSE = 0.90), belly (R2 = 0.43, RMSE = 1.08), sparerib (R2 = 0.08, RMSE = 0.32), or boneless shoulder (R2 = 0.30, RMSE = 0.88). New prediction models and equations were developed using VCS2001 output variables plus hot carcass weight to predict weight of total saleable product (R2 = 0.89, RMSE = 1.72) and fat-corrected lean (R2 = 0.93, RMSE = 1.55) with very minimal increases in accuracy and precision over that achieved using E+V-programmed models and equations. Use of new prediction models and equations marginally improved accuracy and precision of estimations of total saleable product yield (R2 = 0.56, RMSE = 1.81) and fat-corrected lean yield (R2 = 0.57, RMSE = 1.67) over that achieved using E+V-programmed models and equations. The VCS2001 was not able to predict pork carcass composition more accurately than existing technology; therefore, further development is needed to assure commercial viability of this instrument.