Challenges in Applying Multimodal Imaging Technologies to Quantify In Vivo Glycogen and Intramuscular Fat in Livestock

Tharcilla I. R. C. Alvarenga; Peter McGilchrist; Marianne D. Keller; David W. Pethick

doi:10.3390/foods14050784

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Challenges in Applying Multimodal Imaging Technologies to Quantify In Vivo Glycogen and Intramuscular Fat in Livestock

Journal article

Open access

Peer reviewed

Challenges in Applying Multimodal Imaging Technologies to Quantify In Vivo Glycogen and Intramuscular Fat in Livestock

Tharcilla I. R. C. Alvarenga, Peter McGilchrist, Marianne D. Keller and David W. Pethick

Foods, Vol.14(5), 784

2025

DOI: https://doi.org/10.3390/foods14050784

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Abstract

glycogen concentration

intramuscular fat

live animal

muscle hydration

ultrasound frequency

Predicting meat quality, especially dark, firm and dry meat, as well as muscle fat prior to slaughter, presents a challenge in practice. Medical as well as high-frequency ultrasound applications can be utilized to predict body composition and meat quality aspects. Ultrasounds are non-invasive, rapid-to-operate in vivo and show high correlations to the animal production traits being estimated. Farm animal ultrasounds are used to predict intramuscular fat content in the beef cattle industry. Challenges are identified in applying ultrasound technology to detect glycogen content in farm animals due to a wide range of fat, muscle and water composition. Other technologies and methods are reported in this literature review to overcome issues in the practicability and accuracy of ultrasound technology when estimating muscle glycogen levels in cattle. The discussion of other tools such as hyperspectral imaging, microwave sensor technology and digital infrared thermal imaging were addressed because of their superior accuracy in estimating moisture and fat components.

Details

Title: Challenges in Applying Multimodal Imaging Technologies to Quantify In Vivo Glycogen and Intramuscular Fat in Livestock
Authors/Creators: Tharcilla I. R. C. Alvarenga
Peter McGilchrist - University of New England
Marianne D. Keller - The University of Sydney
David W. Pethick - Murdoch University
Publication Details: Foods, Vol.14(5), 784
Publisher: MDPI; BASEL
Number of pages: 13
Grant note: Australian Meat Processor Corporation: 2017-1040
This research was funded by Australian Meat Processor Corporation Ltd.-AMPC (2017-1040).
Identifiers: 991005748444607891
Murdoch Affiliation: Food Futures Institute
Language: English
Resource Type: Journal article

UN Sustainable Development Goals (SDGs)

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Collaboration types: Domestic 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