A Protein-Based Approach for Greek Yogurt Authentication via an HRMS Technique (MALDI-TOF MS) and Milk Powder
Evangelia Krystalli1,2, Nikolaos Thomaidis1, Anastasia S Kritikou1
1Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece.
A new method using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) can detect as little as 1% cow milk powder in yogurt. This technique also classifies yogurt by animal origin, type, and milk processing.
Area of Science:
- Food Science and Technology
- Analytical Chemistry
- Biochemistry
Background:
- Greek-style yogurt's popularity is rising due to its nutritional benefits and texture.
- Increased demand makes yogurt susceptible to adulteration, particularly with cow milk powder.
- Accurate detection methods are crucial for ensuring product authenticity and quality.
Purpose of the Study:
- To develop a rapid and reliable method for detecting cow milk powder adulteration in yogurt.
- To establish a protein-based workflow for identifying adulteration at low concentrations.
- To simultaneously classify yogurt based on milk origin, processing type, and thermal treatment.
Main Methods:
- Utilized matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to analyze intact protein profiles.
- Developed an integrated protein-based workflow for sample preparation and analysis.
- Applied chemometric tools, including principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), for data interpretation.
Main Results:
- Successfully detected as little as 1% cow milk powder adulteration in cow and goat milk yogurt.
- Identified distinct protein markers for classifying yogurt by animal origin (cow, ewe, goat).
- Revealed markers for differentiating yogurt types (traditional vs. strained) and milk thermal treatments.
Conclusions:
- The developed MALDI-TOF MS methodology offers a fast, reliable, and sensitive approach for yogurt adulteration detection.
- This technique enables simultaneous classification of yogurt based on multiple intrinsic characteristics.
- The findings provide a valuable tool for quality control and authentication in the dairy industry.
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