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Food Res Int


Title:A metabolic fingerprinting approach based on selected ion flow tube mass spectrometry (SIFT-MS) and chemometrics: A reliable tool for Mediterranean origin-labeled olive oils authentication
Author(s):Bajoub A; Medina-Rodriguez S; Ajal EA; Cuadros-Rodriguez L; Monasterio RP; Vercammen J; Fernandez-Gutierrez A; Carrasco-Pancorbo A;
Address:"Department of Analytical Chemistry, Faculty of Sciences, University of Granada, Ave. Fuentenueva s/n, 18071 Granada, Spain. Provincial Department of Agriculture of Azilal, PO Box 13, 22000 Azilal, Morocco. Instituto de Biologia Agricola de Mendoza (IBAM), CONICET, Alt. Brown 500, Chacras de Coria, Mendoza, Argentina. Interscience, Avenue J.E. Lenoir 2, 1348 Louvain-la-Neuve, Belgium. Department of Analytical Chemistry, Faculty of Sciences, University of Granada, Ave. Fuentenueva s/n, 18071 Granada, Spain. Electronic address: alegriac@ugr.es"
Journal Title:Food Res Int
Year:2018
Volume:20171214
Issue:
Page Number:233 - 242
DOI: 10.1016/j.foodres.2017.12.027
ISSN/ISBN:1873-7145 (Electronic) 0963-9969 (Linking)
Abstract:"Selected Ion flow tube mass spectrometry (SIFT-MS) in combination with chemometrics was used to authenticate the geographical origin of Mediterranean virgin olive oils (VOOs) produced under geographical origin labels. In particular, 130 oil samples from six different Mediterranean regions (Kalamata (Greece); Toscana (Italy); Meknes and Tyout (Morocco); and Priego de Cordoba and Baena (Spain)) were considered. The headspace volatile fingerprints were measured by SIFT-MS in full scan with H(3)O(+), NO(+) and O(2)(+) as precursor ions and the results were subjected to chemometric treatments. Principal Component Analysis (PCA) was used for preliminary multivariate data analysis and Partial Least Squares-Discriminant Analysis (PLS-DA) was applied to build different models (considering the three reagent ions) to classify samples according to the country of origin and regions (within the same country). The multi-class PLS-DA models showed very good performance in terms of fitting accuracy (98.90-100%) and prediction accuracy (96.70-100% accuracy for cross validation and 97.30-100% accuracy for external validation (test set)). Considering the two-class PLS-DA models, the one for the Spanish samples showed 100% sensitivity, specificity and accuracy in calibration, cross validation and external validation; the model for Moroccan oils also showed very satisfactory results (with perfect scores for almost every parameter in all the cases)"
Keywords:Discriminant Analysis Food Contamination/*analysis Greece Italy Mass Spectrometry/*methods Mediterranean Region Morocco Olive Oil/*chemistry/*classification Reproducibility of Results Sensitivity and Specificity Spain Volatile Organic Compounds/*analysis;
Notes:"MedlineBajoub, Aadil Medina-Rodriguez, Santiago Ajal, El Amine Cuadros-Rodriguez, Luis Monasterio, Romina Paula Vercammen, Joeri Fernandez-Gutierrez, Alberto Carrasco-Pancorbo, Alegria eng Canada 2018/03/28 Food Res Int. 2018 Apr; 106:233-242. doi: 10.1016/j.foodres.2017.12.027. Epub 2017 Dec 14"

 
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