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Related Experiment Video

Updated: Nov 28, 2025

Species Determination and Quantitation in Mixtures Using MRM Mass Spectrometry of Peptides Applied to Meat Authentication
09:26

Species Determination and Quantitation in Mixtures Using MRM Mass Spectrometry of Peptides Applied to Meat Authentication

Published on: September 20, 2016

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A quantitative method for detecting meat contamination based on specific polypeptides.

Chaoyan Feng1, Daokun Xu2, Zhen Liu2

  • 1Key Laboratory of Meat Processing and Quality Control, MOE; Key Laboratory of Meat Processing, MARA; Jiangsu Collaborative Innovation Center of Meat Production and Processing, Quality and Safety Control; College of Food Science and Technology, Nanjing Agricultural University, 210095, Nanjing, China.

Animal Bioscience
|December 1, 2020
PubMed
Summary
This summary is machine-generated.

A new method accurately quantifies meat contamination using specific polypeptides. This technique reliably detects adulteration in various meat products down to 1% levels.

Keywords:
Meat ContaminationNano-LC-MS/MSSpecific Peptide

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Area of Science:

  • Food Science
  • Analytical Chemistry
  • Biochemistry

Background:

  • Meat adulteration poses a significant challenge to food safety and authenticity.
  • Accurate quantitative detection methods are crucial for regulatory compliance and consumer protection.
  • Existing methods may lack specificity or sensitivity for complex meat matrices.

Purpose of the Study:

  • To develop and validate a quantitative detection method for meat contamination.
  • To utilize specific polypeptides as biomarkers for accurate quantification.
  • To establish a reliable analytical approach for commercial meat sample analysis.

Main Methods:

  • Screening of thermally stable peptides with optimal responses using high-resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS).
  • Establishment of standard curves for selected specific polypeptides via triple quadrupole mass spectrometry.
  • Quantitative detection of adulteration in commercial meat samples based on established standard curves.

Main Results:

  • Identification of fifteen thermally stable peptides exhibiting robust responses.
  • Stable detection of specific peptides in both raw and processed meat products.
  • Achieved a detection limit as low as 1% with a strong linear correlation to muscle composition.

Conclusions:

  • The developed method provides effective quantitative analysis for commercial meat samples.
  • This approach offers a sensitive and specific tool for detecting meat adulteration.
  • The method demonstrates high reliability for ensuring meat product authenticity.