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Assessing the varietal origin of extra-virgin olive oil using liquid chromatography fingerprints of phenolic compound, data fusion and chemometrics.
Food Chem. 2017 Jan 15; 215:245-55.FC

Abstract

High Performance Liquid Chromatography (HPLC) with diode array (DAD) and fluorescence (FLD) detection was used to acquire the fingerprints of the phenolic fraction of monovarietal extra-virgin olive oils (extra-VOOs) collected over three consecutive crop seasons (2011/2012-2013/2014). The chromatographic fingerprints of 140 extra-VOO samples processed from olive fruits of seven olive varieties, were recorded and statistically treated for varietal authentication purposes. First, DAD and FLD chromatographic-fingerprint datasets were separately processed and, subsequently, were joined using "Low-level" and "Mid-Level" data fusion methods. After the preliminary examination by principal component analysis (PCA), three supervised pattern recognition techniques, Partial Least Squares Discriminant Analysis (PLS-DA), Soft Independent Modeling of Class Analogies (SIMCA) and K-Nearest Neighbors (k-NN) were applied to the four chromatographic-fingerprinting matrices. The classification models built were very sensitive and selective, showing considerably good recognition and prediction abilities. The combination "chromatographic dataset+chemometric technique" allowing the most accurate classification for each monovarietal extra-VOO was highlighted.

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Publisher Full Text (DOI)

Authors+Show Affiliations

Bajoub A
Department of Analytical Chemistry, Faculty of Sciences, University of Granada, Ave. Fuentenueva s/n, 18071 Granada, Spain.
Medina-Rodríguez S
Department of Analytical Chemistry, Faculty of Sciences, University of Granada, Ave. Fuentenueva s/n, 18071 Granada, Spain.
Gómez-Romero M
Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, SW7 2AZ London, United Kingdom.
Ajal el A
Provincial Department of Agriculture of Azilal, PO Box 13, 22000 Azilal, Morocco.
Bagur-González MG
Department of Analytical Chemistry, Faculty of Sciences, University of Granada, Ave. Fuentenueva s/n, 18071 Granada, Spain.
Fernández-Gutiérrez A
Department of Analytical Chemistry, Faculty of Sciences, University of Granada, Ave. Fuentenueva s/n, 18071 Granada, Spain.
Carrasco-Pancorbo A
Department of Analytical Chemistry, Faculty of Sciences, University of Granada, Ave. Fuentenueva s/n, 18071 Granada, Spain. Electronic address: alegriac@ugr.es.

MeSH

Chromatography, High Pressure LiquidCluster AnalysisDiscriminant AnalysisOlive OilPhenolsPrincipal Component Analysis

Pub Type(s)

Journal Article

Language

eng

PubMed ID

27542473

Citation

Bajoub, Aadil, et al. "Assessing the Varietal Origin of Extra-virgin Olive Oil Using Liquid Chromatography Fingerprints of Phenolic Compound, Data Fusion and Chemometrics." Food Chemistry, vol. 215, 2017, pp. 245-55.
Bajoub A, Medina-Rodríguez S, Gómez-Romero M, et al. Assessing the varietal origin of extra-virgin olive oil using liquid chromatography fingerprints of phenolic compound, data fusion and chemometrics. Food Chem. 2017;215:245-55.
Bajoub, A., Medina-Rodríguez, S., Gómez-Romero, M., Ajal, e. l. . A., Bagur-González, M. G., Fernández-Gutiérrez, A., & Carrasco-Pancorbo, A. (2017). Assessing the varietal origin of extra-virgin olive oil using liquid chromatography fingerprints of phenolic compound, data fusion and chemometrics. Food Chemistry, 215, 245-55. https://doi.org/10.1016/j.foodchem.2016.07.140
Bajoub A, et al. Assessing the Varietal Origin of Extra-virgin Olive Oil Using Liquid Chromatography Fingerprints of Phenolic Compound, Data Fusion and Chemometrics. Food Chem. 2017 Jan 15;215:245-55. PubMed PMID: 27542473.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Assessing the varietal origin of extra-virgin olive oil using liquid chromatography fingerprints of phenolic compound, data fusion and chemometrics. AU - Bajoub,Aadil, AU - Medina-Rodríguez,Santiago, AU - Gómez-Romero,María, AU - Ajal,El Amine, AU - Bagur-González,María Gracia, AU - Fernández-Gutiérrez,Alberto, AU - Carrasco-Pancorbo,Alegría, Y1 - 2016/07/27/ PY - 2016/01/19/received PY - 2016/06/30/revised PY - 2016/07/25/accepted PY - 2016/8/21/entrez PY - 2016/8/21/pubmed PY - 2016/12/31/medline KW - Chemometrics KW - Data fusion KW - High performance liquid chromatography KW - Monovarietal extra-virgin olive oils KW - Phenolic compounds fingerprints KW - Varietal origin SP - 245 EP - 55 JF - Food chemistry JO - Food Chem VL - 215 N2 - High Performance Liquid Chromatography (HPLC) with diode array (DAD) and fluorescence (FLD) detection was used to acquire the fingerprints of the phenolic fraction of monovarietal extra-virgin olive oils (extra-VOOs) collected over three consecutive crop seasons (2011/2012-2013/2014). The chromatographic fingerprints of 140 extra-VOO samples processed from olive fruits of seven olive varieties, were recorded and statistically treated for varietal authentication purposes. First, DAD and FLD chromatographic-fingerprint datasets were separately processed and, subsequently, were joined using "Low-level" and "Mid-Level" data fusion methods. After the preliminary examination by principal component analysis (PCA), three supervised pattern recognition techniques, Partial Least Squares Discriminant Analysis (PLS-DA), Soft Independent Modeling of Class Analogies (SIMCA) and K-Nearest Neighbors (k-NN) were applied to the four chromatographic-fingerprinting matrices. The classification models built were very sensitive and selective, showing considerably good recognition and prediction abilities. The combination "chromatographic dataset+chemometric technique" allowing the most accurate classification for each monovarietal extra-VOO was highlighted. SN - 1873-7072 UR - https://www.unboundmedicine.com/medline/citation/27542473/Assessing_the_varietal_origin_of_extra_virgin_olive_oil_using_liquid_chromatography_fingerprints_of_phenolic_compound_data_fusion_and_chemometrics_ DB - PRIME DP - Unbound Medicine ER -
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