TY - JOUR
T1 - Authentication of Argentinean extra-virgin olive oils using three-way fluorescence and two-way near-infrared data fused with multi-block DD-SIMCA
AU - Lozano, Valeria A.
AU - Jiménez Carvelo, Ana M.
AU - Olivieri, Alejandro C.
AU - Kucheryavskiy, Sergey V.
AU - Rodionova, Oxana Ye
AU - Pomerantsev, Alexey L.
N1 - Publisher Copyright:
© 2024 Elsevier Ltd
PY - 2025/1/15
Y1 - 2025/1/15
N2 - 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 < EEFM < NIR + EEFM. This finding confirms the effectiveness of multi-block data fusion, which cumulatively improves the model performance.
AB - 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 < EEFM < NIR + EEFM. This finding confirms the effectiveness of multi-block data fusion, which cumulatively improves the model performance.
KW - Adulteration
KW - Data fusion
KW - Extra virgin olive oil
KW - Matrix fluorescence data
KW - Near infrared spectroscopy
KW - One-class SIMCA
UR - http://www.scopus.com/inward/record.url?scp=85203068221&partnerID=8YFLogxK
U2 - 10.1016/j.foodchem.2024.141127
DO - 10.1016/j.foodchem.2024.141127
M3 - Journal article
AN - SCOPUS:85203068221
SN - 0308-8146
VL - 463
JO - Food Chemistry
JF - Food Chemistry
M1 - 141127
ER -