Dynamic correction of dual-energy x-ray absorptiometry images improves chain speed prediction of lamb composition in abattoirs

A prototype, on-line Dual Energy X-ray Absorptiometer (DXA) has shown high precision of the prediction of carcass composition for the purpose of improved sheep meat grading in the Australian lamb supply chain, albeit with small inaccuracies over time. These inaccuracies were present across hours, and more significantly across days, which were unacceptable for any accreditation of this device as an objective carcass measurement tool in Australia. This inaccuracy demanded the creation of a novel image-processing algorithm for the prototype DXA. This DXA was tested for repeatability of predictions of lamb carcass composition over minutes, hours, and days, using two developed image processing algorithms. There was high immediate repeatability for both algorithms when predicting lean muscle % in 40 lamb carcasses, with a maximum CV of 0.65% over five repeated scans. There was a decrease in the CV of the prediction of lean muscle % of 30 lambs scanned three times over a 48-h period from 5.93 to 1.19% when the superior algorithm was used. The inaccuracies of lean muscle % predictions were associated with increases in the unattenuated space pixel values in DXA images. Improvements of the current algorithm are required to demonstrate repeatability over time for the purpose of accreditation within the Australian sheep meat industry, and for possible expansion of this technology into international supply chains.

Dual energy X-ray absorptiometry precisely and accurately predicts lamb carcass composition at abattoir chain speed across a range of phenotypic and genotypic variables

Dual energy X-ray absorptiometry (DEXA) is an imaging modality that has been used to predict the computed tomography (CT)-determined carcass composition of multiple species, including sheep and pigs, with minimal inaccuracies, using medical grade DEXA scanners. An online DEXA scanner in an Australian abattoir has shown that a high level of precision can be achieved when predicting lamb carcass composition in real time. This study investigated the accuracy of that same online DEXA when predicting fat and lean percentages as determined by CT over a wide range of phenotypic and genotypic variables across 454 lambs over 6 kill groups and contrasted these results against the current Australian industry standard of grade-rule (GR) measurements to grade carcasses. Lamb carcasses were DEXA scanned and then CT scanned to determine CT Fat % and CT Lean %. All phenotypic traits and genotypic information, including Australian Sheep Breeding Values, were recorded for each carcass. Residuals of the DEXA predicted CT Fat % and Lean %, and the actual CT Fat % and Lean % were calculated and tested against all phenotypic and genotypic variables. Excellent overall precision was recorded when predicting CT Fat % (R2 = 0.91, RMSE = 1.19%). Small biases present for sire breed, sire type, dam breed, hot carcass weight and c-site eye muscle area could be explained by a regression paradox; however, biases among kill group (-0.73% to 1.01% for CT Fat %, -1.48% to 0.76% for CT Lean %) and the Merino sire type (0.36% for CT Fat %, -0.73% for CT Lean %) could not be explained by this effect. Over the large range of phenotypic and genotypic variation, there was excellent precision when predicting CT Fat % and CT Lean % by an online DEXA, with only minor biases, showing superiority to the existing Australian standard of GR measurements.

Repeatability and reproducibility of measurements obtained by dual-energy X-ray absorptiometry on pig carcasses

The precision of a dual-energy X-ray absorptiometry (DXA) device in terms of repeatability and reproducibility was evaluated on nine left half-carcasses from pigs with large variability in body weight and fat content. Repeatability was assessed by scanning each carcass 10 times sequentially in the same position. Reproducibility was assessed by scanning each carcass in 10 different positions. Images were analyzed with DXA software using a custom region of interest (ROI) and the standard head, trunk, arm, and leg ROI. Predicted values from the DEXA for bone mineral content (BMC), bone area, bone mineral density (BMD), total weight, soft-tissue weight, fat-tissue weight, and lean-tissue weight were considered. Repeatability was associated with the variance between measurements on the same carcass in the same position (repeatability conditions). An average variance value was obtained with all the carcasses combined, and the SD was calculated as the square root of this combined variance. The CV was the ratio between the SD of the measurements and its average value. Reproducibility was calculated for each carcass as the difference between the variance obtained under the reproducibility conditions and that obtained under the repeatability conditions. The effects of the ROI and conditions were evaluated by ANOVA and Tukey's test. Means of BMC, bone area, BMD, fat tissue, and lean tissue differed among the ROI (P < 0.05) in both the repeatability and reproducibility conditions. The CV of DXA measurements under repeatability condition obtained in the head, arm, and leg ROI was lesser than 1%. Only the repeatability errors of fat tissue differed (P < 0.05) among the ROI, with the lowest precision found for the trunk ROI. The reproducibility errors of BMC, bone area, fat tissue, and lean tissue differed (P < 0.05) among the ROI. The custom ROI had reproducibility errors greater than 2% for fat tissue and greater than 3.5% for BMC and bone area. In addition, the trunk ROI had the highest reproducibility errors for fat tissue (20.7%) and lean tissue (6.2%) when compared to the other ROI. In conclusion, repeatability and reproducibility results obtained for most of the studied ROI indicate that DXA is a valuable tool for carcass evaluation. From a methodological viewpoint and considering the variations observed in this study, the ROI should be chosen based on the item to be evaluated or on the conditions in which the DXA measurements are to be taken.

Accuracy of dual energy X-ray absorptiometry, weight, longissimus lumborum muscle depth and GR fat depth to predict half carcass composition in sheep

A Hologic QDR4500W dual energy X-ray absorptiometer (DXA) was used to measure body composition in 60 sheep half carcasses ranging from 8 to 28 kg. Half carcasses were from ewes and wethers of mixed genetics. Values determined by DXA, including total tissue mass (TTM), lean tissue mass (LTM), fat tissue mass (FTM) and bone mineral content (BMC), for the half carcass were evaluated by comparison with chemically determined composition. In the case of BMC, the relationship was with chemically determined ash content. Liveweight and chemically determined lean, fat and ash were strongly related to DXA-derived values for TTM, LTM, FTM and BMC, respectively (R2 = 0.999, 0.986, 0.989 and 0.920, respectively). However, because DXA estimates were different from chemically determined values in this sample of carcasses, they needed to be adjusted with the use of appropriate regression equations to correct the in-built algorithms. These data demonstrate the efficacy of DXA as a non-destructive method for determining the composition of the sheep half carcass.