Authentication of Argentinean extra-virgin olive oils using three-way fluorescence and two-way near-infrared data fused with multi-block DD-SIMCA

A trending problem of Extra Virgin Olive Oil (EVOO) adulteration is investigated using two analytical platforms, involving: (1) Near Infrared (NIR) spectroscopy, resulting in a two-way data set, and (2) Fluorescence Excitation-Emission Matrix (EEFM) spectroscopy, producing three-way data. The relate...

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Bibliographic Details
Published in:Food chemistry 2025-01, Vol.463 (Pt 1), p.141127, Article 141127
Main Authors: Lozano, Valeria A., Jiménez Carvelo, Ana M., Olivieri, Alejandro C., Kucheryavskiy, Sergey V., Rodionova, Oxana Ye, Pomerantsev, Alexey L.
Format: Article
Language:English
Subjects:
Adulteration
Data fusion
Extra virgin olive oil
Matrix fluorescence data
Near infrared spectroscopy
One-class SIMCA
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Summary:A trending problem of Extra Virgin Olive Oil (EVOO) adulteration is investigated using two analytical platforms, involving: (1) Near Infrared (NIR) spectroscopy, resulting in a two-way data set, and (2) Fluorescence Excitation-Emission Matrix (EEFM) spectroscopy, producing three-way data. The related instruments were employed to study genuine and adulterated samples. Each data set was first separately analyzed using the Data Driven-Soft Independent Modeling of Class Analogies (DD-SIMCA) method, based on Principal Component Analysis (for the two-way NIR data) and PARallel FACtor analysis (for the three-way EEFM data). The data sets were then processed together using the multi-block fusion method, based on the concept of Cumulative Analytical Signal (CAS). A comparison of the data processing methods in terms of sensitivity, specificity and selectivity showed the following order of excellence: NIR 
ISSN:0308-8146
1873-7072
1873-7072
DOI:10.1016/j.foodchem.2024.141127