Journal article
Calibration of an on-line dual energy X-ray absorptiometer for estimating carcase composition in lamb at abattoir chain-speed
Meat Science, Vol.144, pp.91-99
2018
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%.
Details
- Title
- Calibration of an on-line dual energy X-ray absorptiometer for estimating carcase composition in lamb at abattoir chain-speed
- Authors/Creators
- G.E. Gardner (Author/Creator)S. Starling (Author/Creator)J. Charnley (Author/Creator)J. Hocking-Edwards (Author/Creator)J. Petersen (Author/Creator)A. Williams (Author/Creator)
- Publication Details
- Meat Science, Vol.144, pp.91-99
- Publisher
- Elsevier BV
- Identifiers
- 991005544550407891
- Copyright
- © 2018 Published by Elsevier Ltd.
- Murdoch Affiliation
- School of Veterinary and Life Sciences
- Language
- English
- Resource Type
- Journal article
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- Collaboration types
- Domestic collaboration
- International collaboration
- Citation topics
- 3 Agriculture, Environment & Ecology
- 3.51 Dairy & Animal Sciences
- 3.51.206 Meat Quality
- Web Of Science research areas
- Food Science & Technology
- ESI research areas
- Agricultural Sciences