Quantification of hardware effects of an on-line Dual Energy X-ray Absorptiometry scanner when predicting lamb carcass composition

Stephen Louis Connaughton; Andrew Williams; Fiona Anderson; Khama R. Kelman; Jarno Peterse; Graham Edwin Gardner

doi:10.1016/j.meatsci.2024.109452

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Quantification of hardware effects of an on-line Dual Energy X-ray Absorptiometry scanner when predicting lamb carcass composition

Journal article

Open access

Peer reviewed

Quantification of hardware effects of an on-line Dual Energy X-ray Absorptiometry scanner when predicting lamb carcass composition

Stephen Louis Connaughton, Andrew Williams, Fiona Anderson, Khama R. Kelman, Jarno Peterse and Graham Edwin Gardner

Meat science, Vol.212, 109452

2024

DOI: https://doi.org/10.1016/j.meatsci.2024.109452

PMID: 38368712

Appears in Open Access via Read & Publish Agreements

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Abstract

Composition

Continuous X-ray

DXA

Hardware

Lamb

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 University
Andrew Williams - Murdoch University
Fiona Anderson - Murdoch University, Centre for Animal Production and Health
Khama R. Kelman - Murdoch University, Centre for Animal Production and Health
Jarno Peterse - Murdoch University
Graham Edwin Gardner - Murdoch University, Centre for Animal Production and Health
Publication Details: Meat science, Vol.212, 109452
Publisher: Elsevier Ltd
Identifiers: 991005638669907891
Murdoch Affiliation: Murdoch University
Language: English
Resource Type: Journal article

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Citation topics: 1 Clinical & Life Sciences; 1.44 Nutrition & Dietetics; 1.44.330 Geriatric Nutrition
Web Of Science research areas: Food Science & Technology
ESI research areas: Agricultural Sciences