A major activity of the INTAQT project is to conduct research to better discriminate beef composition and beef sensory quality by using up-to-date approaches and techniques. Among them, Rapid Evaporative Ionization Mass Spectrometry (REIMS) is an emerging ambient mass spectrometry technique that has demonstrated applications initially in human health for prognostic and diagnostic purpose and currently has demonstrated an increasing number of applications in the field of food science. The information generated by the REIMS platform creates a unique mass spectral “fingerprint” of the different analysed samples that can be used to assess differences between them. Fingerprints are generated largely from molecular ions that are present in lipid and phospholipid tissue within muscles.

Herein, we investigated the potential of REIMS analysis for classifying muscle composition and meat sensory quality of cattle. This study was based on 116 samples from 29 crossbred Angus × Salers, across three muscle types. Prediction models were developed combining REIMS fingerprints and meat quality traits. Varying efficacy was observed across REIMS discriminations − muscle type (71 %), marbling level (32 %), untrained consumer evaluated tenderness (36 %), flavor liking (99 %) and juiciness (99 %). Notably, REIMS demonstrated the ability to classify 116 beef samples across four different quality grades provided by untrained consumers with an overall accuracy of 37 %. Specifically, “premium” beef could be differentiated from “unsatisfactory”, “good everyday” and “better than everyday” grades with accuracies of 99 %, 84 %, and 62 %, respectively. Limited efficacy was observed however, in classifying trained panel evaluated sensory quality and fatty acid composition. Additionally, key predictive features were tentatively identified from the REIMS fingerprints primarily comprised of molecular ions present in lipids, phospholipids, and amino acids.

This work has been published in Food Chemistry, 2024, 454, pp.139645. ⟨10.1016/j.foodchem.2024.139645⟩

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