Classification of 'Chemlali' accessions according to the geographical area using chemometric methods of phenolic profiles analysed by HPLC-ESI-TOF-MS

Amani Taamalli; David Arráez Román; Mokhtar Zarrouk; Antonio Segura-Carretero; Alberto Fernández-Gutiérrez

doi:10.1016/j.foodchem.2011.10.070

Classification of 'Chemlali' accessions according to the geographical area using chemometric methods of phenolic profiles analysed by HPLC-ESI-TOF-MS

Food Chem. 2012 May 1;132(1):561-6. doi: 10.1016/j.foodchem.2011.10.070. Epub 2011 Nov 4.

Authors

Amani Taamalli¹, David Arráez Román², Mokhtar Zarrouk³, Antonio Segura-Carretero⁴, Alberto Fernández-Gutiérrez²

Affiliations

¹ Laboratoire Caractérisation et Qualité de l'Huile d'Olive, Centre de Biotechnologie de Borj Cedria, BP 901, 2050 Hammam-Lif, Tunisia; Department of Analytical Chemistry, University of Granada, Avda. Fuentenueva s/n, 18071 Granada, Spain; Funtional Food Research and Development Centre (CIDAF), Health Science Technological Park, Avda. Del Conocimiento s/n, 18100 Granada, Spain.
² Department of Analytical Chemistry, University of Granada, Avda. Fuentenueva s/n, 18071 Granada, Spain; Funtional Food Research and Development Centre (CIDAF), Health Science Technological Park, Avda. Del Conocimiento s/n, 18100 Granada, Spain.
³ Laboratoire Caractérisation et Qualité de l'Huile d'Olive, Centre de Biotechnologie de Borj Cedria, BP 901, 2050 Hammam-Lif, Tunisia.
⁴ Department of Analytical Chemistry, University of Granada, Avda. Fuentenueva s/n, 18071 Granada, Spain; Funtional Food Research and Development Centre (CIDAF), Health Science Technological Park, Avda. Del Conocimiento s/n, 18100 Granada, Spain. Electronic address: ansegura@ugr.es.

PMID: 26434332
DOI: 10.1016/j.foodchem.2011.10.070

Abstract

The present work describes a classification method of Tunisian 'Chemlali' olive oils based on their phenolic composition and geographical area. For this purpose, the data obtained by HPLC-ESI-TOF-MS from 13 samples of extra virgin olive oils, obtained from different production area throughout the country, were used for this study focusing in 23 phenolics compounds detected. The quantitative results showed a significant variability among the analysed oil samples. Factor analysis method using principal component was applied to the data in order to reduce the number of factors which explain the variability of the selected compounds. The data matrix constructed was subjected to a canonical discriminant analysis (CDA) in order to classify the oil samples. These results showed that 100% of cross-validated original group cases were correctly classified, which proves the usefulness of the selected variables.

Keywords: Discriminant classification; Geographical area; Liquid chromatography; Mass spectrometry; Monovarietal virgin olive oil; Phenolic compounds.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Chromatography, High Pressure Liquid / methods*
Olive Oil / chemistry*
Phenols / analysis
Phenols / chemistry*
Plant Oils / chemistry*

Substances

Olive Oil
Phenols
Plant Oils