MALDI-TOF MS Protein Profiling Combined with Multivariate Analysis for Identification and Quantitation of Beef Adulteration

    The problem of adulteration and mislabeling in meat products has raised the public concerns globally. An easy-operation, fast, and robust method that is applicable to routine inspections is urgently needed. This study showed that the MALDI-TOF MS protein profiling of four meat species (beef, chi...

Full description

Saved in:
Bibliographic Details
Published in:Food analytical methods 2023, Vol.16 (1), p.132-142
Main Authors: Pu, Keyuan, Qiu, Jiamin, Li, Jiaying, Huang, Wei, Lai, Xiaopin, Liu, Cheng, Lin, Yan, Ng, Kwan-Ming
Format: Article
Language:English
Subjects:
Analytical Chemistry
Aquatic birds
Beef
Chemistry
Chemistry and Materials Science
Chemistry/Food Science
Discriminant analysis
Food Science
Ions
Least squares method
Meat
Meat products
Microbiology
Multivariate analysis
Pork
Prediction models
Proteins
Qualitative analysis
Quantitation
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:    The problem of adulteration and mislabeling in meat products has raised the public concerns globally. An easy-operation, fast, and robust method that is applicable to routine inspections is urgently needed. This study showed that the MALDI-TOF MS protein profiling of four meat species (beef, chicken, duck, and pork) combining with partial least squares discriminant analysis (PLS-DA) discovered 57 feature peaks for their unambiguous differentiation. Among them, 36 were identified in Uniprot. Based on the linear relation between the intensities of feature peaks, the partial least squares regression was successfully applied to build the prediction models for determining the adulteration ratios of beef meat mixtures containing one of the other three species. Blind tests were applied to evaluate the method and the average prediction accuracy at 94.7% was achieved. Taking duck meat as the adulterant, the detection sensitivity of the method could be down to 5%. Moreover, the method has also been successfully applied to analyze market samples and the results were in agreement with the PCR method, showing the potential of its practical application for qualitative and quantitative analysis of adulterated beef products.
ISSN:1936-9751
1936-976X
DOI:10.1007/s12161-022-02403-2