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Journal article
Quantification of hardware effects of an on-line Dual Energy X-ray Absorptiometry scanner when predicting lamb carcass composition
Meat science, Vol.212, 109452
2024
PMID: 38368712
Abstract
An on-line Dual Energy X-ray Absorptiometry (DXA) scanner's tissue composition prediction precision and accuracy was tested across the entire height of the unit's detector, and the hardware was assessed for robustness by measuring X-ray photon intensity throughout production days. There was good precision when predicting the tissue composition of 5 different lamb fat and lean muscle mixtures across 3 different thicknesses (R2 = 0.93 to 0.98, RMSE = 3.18% to 5.83%), however was less precise at the greatest thickness of 200 mm (R2 = 0.59, RMSE = 11.4%). There was no significant difference in the prediction of tissue composition at 8 of the 9 detector positions, however the position at the perpendicular of the X-ray photon beam was significantly different, with a fat prediction error of −4%, although no lamb carcass is detected in this position during normal production. A significant upwards drift in X-ray photon intensity was found over the course of production, especially immediately after restarting the DXA scanner following a period of inactivity. This upwards drift may affect tissue composition predictions over the span of a production day if uncorrected.
Details
- Title
- Quantification of hardware effects of an on-line Dual Energy X-ray Absorptiometry scanner when predicting lamb carcass composition
- Authors/Creators
- Stephen Louis Connaughton - Murdoch UniversityAndrew Williams - Murdoch UniversityFiona Anderson - Murdoch University, Centre for Animal Production and HealthKhama R. Kelman - Murdoch University, Centre for Animal Production and HealthJarno Peterse - Murdoch UniversityGraham Edwin Gardner - Murdoch University, Centre for Animal Production and Health
- Publication Details
- Meat science, Vol.212, 109452
- Publisher
- Elsevier Ltd
- Identifiers
- 991005638669907891
- Copyright
- © 2024 The Authors.
- Murdoch Affiliation
- Murdoch University
- Language
- English
- Resource Type
- Journal article
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- Web Of Science research areas
- Food Science & Technology
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- Agricultural Sciences