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−HRMS), coupled with Principal Component Analysis (PCA) was carried out by performing a combined metabolomics study to discriminate <i>Arbut...
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2019-07-01
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author | Mariateresa Maldini Gilda D’Urso Giordana Pagliuca Giacomo Luigi Petretto Marzia Foddai Francesca Romana Gallo Giuseppina Multari Donatella Caruso Paola Montoro Giorgio Pintore |
author_facet | Mariateresa Maldini Gilda D’Urso Giordana Pagliuca Giacomo Luigi Petretto Marzia Foddai Francesca Romana Gallo Giuseppina Multari Donatella Caruso Paola Montoro Giorgio Pintore |
author_sort | Mariateresa Maldini |
collection | DOAJ |
description | A comparison between High-Performance Thin-Layer Chromatography (HPTLC) analysis and Liquid Chromatography High Resolution Mass Spectrometry (LC−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−HRMS followed by unsupervised PCA, and then by LC−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−HRMS could be used to identify which metabolites are able to discriminate samples. |
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institution | Directory Open Access Journal |
issn | 2304-8158 |
language | English |
last_indexed | 2024-04-12T06:00:28Z |
publishDate | 2019-07-01 |
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series | Foods |
spelling | doaj.art-7f4da618399542a4bff5356f7dc9c95a2022-12-22T03:45:03ZengMDPI AGFoods2304-81582019-07-018829410.3390/foods8080294foods8080294HPTLC-PCA Complementary to HRMS-PCA in the Case Study of <i>Arbutus unedo</i> Antioxidant Phenolic ProfilingMariateresa Maldini0Gilda D’Urso1Giordana Pagliuca2Giacomo Luigi Petretto3Marzia Foddai4Francesca Romana Gallo5Giuseppina Multari6Donatella Caruso7Paola Montoro8Giorgio Pintore9Department of Chemistry and Pharmacy, University of Sassari, Via F. Muroni, 23/b, 07100 Sassari, ItalyDepartment of Pharmacy, University of Salerno, Via Giovanni Paolo II, 84084 Fisciano (SA), ItalyNational Center for Drug Research and Evaluation, Viale Regina Elena, 299, 00161 Roma, ItalyDepartment of Chemistry and Pharmacy, University of Sassari, Via F. Muroni, 23/b, 07100 Sassari, ItalyDepartment of Chemistry and Pharmacy, University of Sassari, Via F. Muroni, 23/b, 07100 Sassari, ItalyNational Center for Drug Research and Evaluation, Viale Regina Elena, 299, 00161 Roma, ItalyNational Center for Drug Research and Evaluation, Viale Regina Elena, 299, 00161 Roma, ItalyDepartment of Pharmacological and Biomolecular Sciences, Università degli Studi di Milano, Via Balzaretti, 9, 20133 Milan, ItalyDepartment of Pharmacy, University of Salerno, Via Giovanni Paolo II, 84084 Fisciano (SA), ItalyDepartment of Chemistry and Pharmacy, University of Sassari, Via F. Muroni, 23/b, 07100 Sassari, ItalyA comparison between High-Performance Thin-Layer Chromatography (HPTLC) analysis and Liquid Chromatography High Resolution Mass Spectrometry (LC−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−HRMS followed by unsupervised PCA, and then by LC−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−HRMS could be used to identify which metabolites are able to discriminate samples.https://www.mdpi.com/2304-8158/8/8/294HPTLCLC–HRMSPCAmetabolomicsArbutus unedoantioxidant activities |
spellingShingle | Mariateresa Maldini Gilda D’Urso Giordana Pagliuca Giacomo Luigi Petretto Marzia Foddai Francesca Romana Gallo Giuseppina Multari Donatella Caruso Paola Montoro Giorgio Pintore HPTLC-PCA Complementary to HRMS-PCA in the Case Study of <i>Arbutus unedo</i> Antioxidant Phenolic Profiling Foods HPTLC LC–HRMS PCA metabolomics Arbutus unedo antioxidant activities |
title | HPTLC-PCA Complementary to HRMS-PCA in the Case Study of <i>Arbutus unedo</i> Antioxidant Phenolic Profiling |
title_full | HPTLC-PCA Complementary to HRMS-PCA in the Case Study of <i>Arbutus unedo</i> Antioxidant Phenolic Profiling |
title_fullStr | HPTLC-PCA Complementary to HRMS-PCA in the Case Study of <i>Arbutus unedo</i> Antioxidant Phenolic Profiling |
title_full_unstemmed | HPTLC-PCA Complementary to HRMS-PCA in the Case Study of <i>Arbutus unedo</i> Antioxidant Phenolic Profiling |
title_short | HPTLC-PCA Complementary to HRMS-PCA in the Case Study of <i>Arbutus unedo</i> Antioxidant Phenolic Profiling |
title_sort | hptlc pca complementary to hrms pca in the case study of i arbutus unedo i antioxidant phenolic profiling |
topic | HPTLC LC–HRMS PCA metabolomics Arbutus unedo antioxidant activities |
url | https://www.mdpi.com/2304-8158/8/8/294 |
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