HPTLC-PCA Complementary to HRMS-PCA in the Case Study of <i>Arbutus unedo</i> Antioxidant Phenolic Profiling

A comparison between High-Performance Thin-Layer Chromatography (HPTLC) analysis and Liquid Chromatography High Resolution Mass Spectrometry (LC&#8722;HRMS), coupled with Principal Component Analysis (PCA) was carried out by performing a combined metabolomics study to discriminate <i>Arbut...

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Bibliographic Details
Main Authors: Mariateresa Maldini, Gilda D’Urso, Giordana Pagliuca, Giacomo Luigi Petretto, Marzia Foddai, Francesca Romana Gallo, Giuseppina Multari, Donatella Caruso, Paola Montoro, Giorgio Pintore
Format: Article
Language:English
Published: MDPI AG 2019-07-01
Series:Foods
Subjects:
PCA
Online Access:https://www.mdpi.com/2304-8158/8/8/294
Description
Summary:A comparison between High-Performance Thin-Layer Chromatography (HPTLC) analysis and Liquid Chromatography High Resolution Mass Spectrometry (LC&#8722;HRMS), coupled with Principal Component Analysis (PCA) was carried out by performing a combined metabolomics study to discriminate <i>Arbutus unedo</i> (<i>A. unedo</i>) plants. For a rapid digital record of <i>A. unedo</i> extracts (leaves, yellow fruit, and red fruit collected in La Maddalena and Sassari, Sardinia), HPTLC was used. Data were then analysed by PCA with the results of the ability of this technique to discriminate samples. Similarly, extracts were acquired by non-targeted LC&#8722;HRMS followed by unsupervised PCA, and then by LC&#8722;HRMS (MS) to identify secondary metabolites involved in the differentiation of the samples. As a result, we demonstrated that HPTLC may be applied as a simple and reliable untargeted approach to rapidly discriminate extracts based on tissues and/or geographical origins, while LC&#8722;HRMS could be used to identify which metabolites are able to discriminate samples.
ISSN:2304-8158