Visualization-Based Rapid Screening and Quantitative Analysis of Target Peptides for Meat Authentication

Amidst growing demand for meat products, concerns regarding their authenticity and safety have intensified, primarily due to potential fraudulent substitutions of cheaper meats, which are not accurately labeled. This study presents a novel strategy for the rapid screening and validation of target peptides for accurate quantitative analysis using high-resolution mass spectrometry (HRMS) coupled with multivariate statistical analysis. By integrating hierarchical clustering analysis (HCA) with parallel reaction monitoring (PRM), five species-specific peptides were validated as reliable biomarkers for pork quantification. These peptides demonstrated accurate quantification in simulated meat products with known accurate contents, achieving recoveries of 78-128%, with RSD less than 12%. This methodology markedly enhances screening efficiency by excluding 80% of non-quantitative peptides, providing a robust solution for meat authenticity verification.

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Publication Details

Journal
Foods
Published
2025-08-29
DOI
https://doi.org/10.3390/foods14173048
Citations
1
Primary Topic
Identification and Quantification in Food
Type
article
Field-Weighted Citation Impact
0.81

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Visualization-Based Rapid Screening and Quantitative Analysis of Target Peptides for Meat Authentication

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article en
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Abstract

Amidst growing demand for meat products, concerns regarding their authenticity and safety have intensified, primarily due to potential fraudulent substitutions of cheaper meats, which are not accurately labeled. This study presents a novel strategy for the rapid screening and validation of target peptides for accurate quantitative analysis using high-resolution mass spectrometry (HRMS) coupled with multivariate statistical analysis. By integrating hierarchical clustering analysis (HCA) with parallel reaction monitoring (PRM), five species-specific peptides were validated as reliable biomarkers for pork quantification. These peptides demonstrated accurate quantification in simulated meat products with known accurate contents, achieving recoveries of 78-128%, with RSD less than 12%. This methodology markedly enhances screening efficiency by excluding 80% of non-quantitative peptides, providing a robust solution for meat authenticity verification.

FoodsVol. 14(17)
Shanghai Customs College (CN), China Meat Research Centre (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 24%
Identification and Quantification in Food
0.81
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