MALDI-TOF-MS integrated workflow for food authenticity investigations: An untargeted protein-based approach for rapid detection of PDO feta cheese adulteration

[Display omitted] •Cheese authenticity protein-based investigation via MALDI-TOF-MS.•Automated data treatment workflow for cheese origin discrimination.•Fast high throughput analytical method applicable in routine analysis.•Reliable detection of feta cheese adulteration down to 1% cow milk.•Discrimi...

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Bibliographic Details
Published in:Food chemistry 2022-02, Vol.370, p.131057-131057, Article 131057
Main Authors: Kritikou, Anastasia S., Aalizadeh, Reza, Damalas, Dimitrios E., Barla, Ioanna V., Baessmann, Carsten, Thomaidis, Nikolaos S.
Format: Article
Language:English
Subjects:
Adulteration
Chemometrics
Feta cheese
MALDI-TOF-MS
PDO dairy product
Proteins
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Summary:[Display omitted] •Cheese authenticity protein-based investigation via MALDI-TOF-MS.•Automated data treatment workflow for cheese origin discrimination.•Fast high throughput analytical method applicable in routine analysis.•Reliable detection of feta cheese adulteration down to 1% cow milk.•Discrimination of feta cheese from similar white cheese ripened in brine. Advances in Matrix-assisted Laser Desorption/Ionization -Time-Of-Flight Mass Spectrometry (MALDI-TOF-MS) have led to its supremacy for complex assessment of food authenticity studies, like dairy products fraud, holding promise for the discovery of potential authenticity (bio)markers. In this study, an integrated untargeted protein-based workflow in combination with advanced chemometrics is presented, to address authenticity challenges in PDO feta cheese which is legally manufactured by the mixture of sheep/goat milk. Potential markers attributed to specific animal origin were found from protein profiles acquired for authentic feta and white cheeses (prepared from cow milk), belonging to 4 kDa–18.5 kDa mass area. Rapid detection of feta cheese adulteration from cow milk was also achieved down to 1% adulteration level. The discriminative models showed high predictive ability for feta cheese authenticity (Q2 = 0.920, RMSEE = 0.053) and its adulteration (Q2 = 0.835, RMSEE = 0.121), introducing a reliable approach in routine analysis. The methodology was successfully applied in detection of cow milk in sheep yoghurt.
ISSN:0308-8146
1873-7072
DOI:10.1016/j.foodchem.2021.131057