| Literature DB >> 30008338 |
G E Gardner1, S Starling2, J Charnley3, J Hocking-Edwards4, J Peterse5, A Williams5.
Abstract
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 R2 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%.Entities:
Keywords: Accuracy; Automation; Computed tomography; Genetics; Precision
Mesh:
Year: 2018 PMID: 30008338 DOI: 10.1016/j.meatsci.2018.06.020
Source DB: PubMed Journal: Meat Sci ISSN: 0309-1740 Impact factor: 5.209