Title Comparing two metabolic profiling approaches (liquid chromatography and gas chromatography coupled to mass spectrometry) for extra-virgin olive oil phenolic compounds analysis: A botanical classification perspective
Authors Bajoub, Aadil , Pacchiarotta, Tiziana , HURTADO FERNÁNDEZ, ELENA, Olmo-Garcia, Lucia , Garcia-Villalba, Rocio , Fernandez-Gutierrez, Alberto , Mayboroda, Oleg A. , Carrasco-Pancorbo, Alegria
External publication Si
Means J. Chromatogr. A
Scope Article
Nature Científica
JCR Quartile 1
SJR Quartile 1
JCR Impact 3.98100
SJR Impact 1.46300
Publication date 08/01/2016
ISI 000368564000025
DOI 10.1016/j.chroma.2015.10.059
Abstract Over the last decades, the phenolic compounds from virgin olive oil (VOO) have become the subject of intensive research because of their biological activities and their influence on some of the most relevant attributes of this interesting matrix. Developing metabolic profiling approaches to determine them in monovarietal virgin olive oils could help to gain a deeper insight into olive oil phenolic compounds composition as well as to promote their use for botanical origin tracing purposes. To this end, two approaches were comparatively investigated (LC-ESI-TOF MS and GC-APCI-TOF MS) to evaluate their capacity to properly classify 25 olive oil samples belonging to five different varieties (Arbequina, Cornicabra, Hojiblanca, Frantoio and Picual), using the entire chromatographic phenolic profiles combined to chemometrics (principal component analysis (PCA) and partial least square-discriminant analysis (PIS-DA)). The application of PCA to LC-MS and GC-MS data showed the natural clustering of the samples, seeing that 2 varieties were dominating the models (Arbequina and Frantoio), suppressing any possible discrimination among the other cultivars. Afterwards, PLS-DA was used to build four different efficient predictive models for varietal classification of the samples under study. The varietal markers pointed out by each platform were compared. In general, with the exception of one GC-MS model, all exhibited proper quality parameters. The models constructed by using the LC-MS data demonstrated superior classification ability. (C) 2015 Elsevier B.V. All rights reserved.
Keywords Monovarietal extra-virgin olive oils; Phenolic compounds; Liquid chromatography-electrospray ionisation-time of flight mass spectrometry; Gas chromatography-atmospheric pressure chemical ionisation-ti
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