Logo image
Fast non-destructive measurement of intramuscular fat in Australian beef and lamb using nuclear magnetic resonance (NMR) technologies
Journal article   Peer reviewed

Fast non-destructive measurement of intramuscular fat in Australian beef and lamb using nuclear magnetic resonance (NMR) technologies

Evan R. McCarney, Peter McGilchrist, Sarah M. Stewart and Robin Dykstra
Meat science, Vol.220, 109706
2025

Abstract

Food magnetic resonance Intramuscular fat Low field NMR Marbling Unilateral NMR
Nuclear magnetic resonance (NMR) is an excellent technique for non-destructive analysis of meat because it has high accuracy, a linear response, and insignificant drift over time, which removes the need for recalibration. Furthermore, single-side NMR devices have open geometries that enable measurements of subsections of larger samples without taking sub-samples. Here we demonstrated long-term reproducibility in a benchtop device and the utility of a single-sided NMR device. We validated long-term reproducibility of NMR measurements of lamb intramuscular fat (IMF%) in a commercial processor boning room years after the original model was created. It was hypothesised that the NMR IMF% model would retain precision and accuracy on independent validation. The root mean squared (RMS) error of prediction of lamb IMF was 0.79 %. The R2 between reference measurements, predicted IMF% was 0.74, the slope of the chemical IMF% vs NMR predictions was 0.989, and the bias was 0.53 % IMF%. In the second example, we showed that IMF% measurements of high value beef striploins could be measured off a commercial processing belt and returned without damaging the product. It was hypothesised that a commercial prototype single-sided NMR system would predict IMF% in beef M. longissimus thoracis et lumborum. Here the RMS error of the correlation was 1.58 % IMF% and R2 was 0.97. The long-term stability, high accuracy, and nondestructive nature make unilateral NMR devices ideal for applications in the red meat industry where IMF% contributes to product value.

Details

Metrics

InCites Highlights

These are selected metrics from InCites Benchmarking & Analytics tool, related to this output

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
Logo image