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 (Foods)
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.