Journal
MEAT SCIENCE
Volume 144, Issue -, Pages 91-99Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.meatsci.2018.06.020
Keywords
Computed tomography; Genetics; Automation; Precision; Accuracy
Categories
Funding
- Meat and Livestock Australia [A.MQA.0017]
- CRC for Sheep Industry Innovation (Program E2 - Quality-based sheepmeat value chains)
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This experiment assessed the ability of an on-line dual energy x-ray absorptiometer (DEXA) installed at a commercial abattoir to determine carcase composition at abattoir chain-speed. 607 lamb carcases from 7 slaughter groups were DEXA scanned and then scanned using computed tomography to determine the proportions of fat (CT fat%), lean (CT lean%), and bone (CT bone%). Data between slaughter groups were standardised relative to a synthetic phantom consisting of Nylon-6. Models were then trained within each dataset using hot carcase weight and DEXA value to predict CT composition, and then validated in the remaining datasets. Results from across-dataset validation tests demonstrated excellent precision for predicting CT fat%, with RMSE and R-2 values of 1.32 and 0.89, compared to values of 1.69 and 0.69 for CT lean%, and 0.81 and 0.68 for CT bone% which had less precision. Accuracy across datasets was also robust, with average bias values of 0.66, 0.83, and 0.51 for CT fat%, lean%, and bone%.
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