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Updated: Mar 10, 2026

Species Determination and Quantitation in Mixtures Using MRM Mass Spectrometry of Peptides Applied to Meat Authentication
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Beef quality grading using rapid evaporative ionization mass spectrometry (REIMS).

Yafang Cui1, Lynda S Perkins2, Jingjing Liu3

  • 1INRAE, Clermont Auvergne University, VetAgro Sup, UMRH, Theix, 63122 Saint-Genès-Champanelle, France.

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|March 9, 2026
PubMed
Summary

Rapid evaporative ionization mass spectrometry (REIMS) accurately differentiates beef muscles and predicts carcass traits. This technique shows promise for real-time meat quality assessment, distinguishing muscle types and influencing quality factors.

Keywords:
Carcass gradingMetabolic fingerprintingREIMSSensory qualityUntrained consumers

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Area of Science:

  • Food Science
  • Analytical Chemistry
  • Biochemistry

Background:

  • Traditional beef quality assessment methods are often time-consuming and subjective.
  • Rapid evaporative ionization mass spectrometry (REIMS) offers potential for real-time, objective analysis of biological tissues.
  • Understanding muscle-specific metabolite profiles is crucial for predicting beef quality and carcass traits.

Purpose of the Study:

  • To evaluate the efficacy of REIMS for real-time metabolite analysis of beef muscles.
  • To develop predictive models for carcass traits and sensory quality using REIMS data.
  • To investigate the muscle-specific metabolic differences influencing beef quality.

Main Methods:

  • REIMS was used to analyze two distinct beef muscles (rump and striploin) from Limousine cows.
  • Orthogonal partial to latent structures-discriminant analysis (OPLS-DA) was employed to build classification and prediction models.
  • Models were developed using carcass traits, laboratory measurements, and sensory data, with variables dichotomized by median values.

Main Results:

  • REIMS achieved 100% accuracy in distinguishing rump from striploin muscles.
  • Strong associations were found between REIMS data and transport distance, carcass traits, and laboratory measurements (R²Y = 0.86-0.94).
  • Rump muscle models showed moderate predictive accuracy for sensory traits (63.3%-73.3%), while striploin models were less successful (<60%).

Conclusions:

  • REIMS is a rapid and effective tool for muscle-specific metabolite profiling in beef.
  • The technique shows potential for improving carcass grading and predicting beef sensory quality, particularly in binary classification scenarios.
  • Metabolic differences identified by REIMS correlate with distinct muscle characteristics and quality attributes.