Literature DB >> 31108805

Discrimination of extra-virgin-olive oils from different cultivars and geographical origins by untargeted metabolomics.

Silvia Ghisoni1, Luigi Lucini2, Federica Angilletta1, Gabriele Rocchetti3, Daniela Farinelli4, Sergio Tombesi5, Marco Trevisan1.   

Abstract

In this preliminary study, ultra-high-pressure liquid chromatography (UHPLC) coupled to quadrupole-time-of-flight mass spectrometry (QTOF) metabolomics followed by multivariate statistics was applied to discriminate nine extra-virgin olive oil (EVOO) cultivars according to their phenolic and sterolic fingerprints. The same approach was then used to discriminate EVOO samples from different geographical origins, namely six blends representative of the main growing regions in Italy (i.e., Sicily, Puglia, Umbria, Liguria, Lombardy and Tuscany). This approach allowed to putatively identify >1000 compounds, considering both polyphenols and sterols. The unsupervised hierarchical cluster analysis (HCA) and the orthogonal projections to latent structures discriminant analysis (OPLS-DA) discriminated EVOO samples according to both cultivar and geographical origin. In particular, flavonoids (i.e., anthocyanins and flavonols), hydroxycinnamic acids and cholesterol derivatives were found to be the most representative classes of compounds discriminating EVOO samples according to the two parameters (cultivar or geographical origin) selected. However, the following Venn analysis allowed to point out the discriminant markers being exclusive for cultivar or origin discrimination. In this regard, only the 9.6% of phenolics and 13.6% of sterols were in common, thus indicating that several of these discriminant compounds were exclusive of a single condition. Indeed, considering that most of the commercial EVOOs are blended, the contribution of both the cultivars used and the geographical origin must be taken into account.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Extra-Virgin Olive Oil; Food metabolomics; Polyphenols; Sterols; Traceability

Year:  2018        PMID: 31108805     DOI: 10.1016/j.foodres.2018.12.052

Source DB:  PubMed          Journal:  Food Res Int        ISSN: 0963-9969            Impact factor:   6.475


  10 in total

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Journal:  Plants (Basel)       Date:  2022-07-12

Review 2.  Extra Virgin Olive Oil: Lesson from Nutrigenomics.

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Journal:  Nutrients       Date:  2019-09-04       Impact factor: 5.717

3.  1H-NMR Profiling Shows as Specific Constituents Strongly Affect the International EVOO Blends Characteristics: The Case of the Italian Oil.

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Journal:  Molecules       Date:  2021-04-13       Impact factor: 4.411

4.  Chemometric Discrimination of the Geographical Origin of Three Greek Cultivars of Olive Oils by Stable Isotope Ratio Analysis.

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Journal:  Foods       Date:  2021-02-04

Review 5.  Geographical Origin Assessment of Extra Virgin Olive Oil via NMR and MS Combined with Chemometrics as Analytical Approaches.

Authors:  Francesca Calò; Chiara Roberta Girelli; Selina C Wang; Francesco Paolo Fanizzi
Journal:  Foods       Date:  2022-01-01

6.  Comparative Metabolomics Study of Chaenomeles speciosa (Sweet) Nakai from Different Geographical Regions.

Authors:  Yubo Ma; Jihan Li; Jingling Li; Li Yang; Guanle Wu; Shiyao Liu
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8.  Metabolomic Study to Evaluate the Transformations of Extra-Virgin Olive Oil's Antioxidant Phytochemicals During In Vitro Gastrointestinal Digestion.

Authors:  Gabriele Rocchetti; Biancamaria Senizza; Gianluca Giuberti; Domenico Montesano; Marco Trevisan; Luigi Lucini
Journal:  Antioxidants (Basel)       Date:  2020-04-06

9.  Olive Oil Quality and Authenticity Assessment Aspects Employing FIA-MRMS and LC-Orbitrap MS Metabolomic Approaches.

Authors:  Theodora Nikou; Matthias Witt; Panagiotis Stathopoulos; Aiko Barsch; Maria Halabalaki
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Review 10.  Metabolomics as a marketing tool for geographical indication products: a literature review.

Authors:  Alvaro Luis Lamas Cassago; Mateus Manfrin Artêncio; Janaina de Moura Engracia Giraldi; Fernando Batista Da Costa
Journal:  Eur Food Res Technol       Date:  2021-06-15       Impact factor: 2.998

  10 in total

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