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HPTLC-PCA Complementary to HRMS-PCA in the Case Study of Arbutus unedo 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 Arbutus unedo (A. unedo)...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6723518/ https://www.ncbi.nlm.nih.gov/pubmed/31357632 http://dx.doi.org/10.3390/foods8080294 |
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author | Maldini, Mariateresa D’Urso, Gilda Pagliuca, Giordana Petretto, Giacomo Luigi Foddai, Marzia Gallo, Francesca Romana Multari, Giuseppina Caruso, Donatella Montoro, Paola Pintore, Giorgio |
author_facet | Maldini, Mariateresa D’Urso, Gilda Pagliuca, Giordana Petretto, Giacomo Luigi Foddai, Marzia Gallo, Francesca Romana Multari, Giuseppina Caruso, Donatella Montoro, Paola Pintore, Giorgio |
author_sort | Maldini, Mariateresa |
collection | PubMed |
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 Arbutus unedo (A. unedo) plants. For a rapid digital record of A. unedo 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. |
format | Online Article Text |
id | pubmed-6723518 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-67235182019-09-10 HPTLC-PCA Complementary to HRMS-PCA in the Case Study of Arbutus unedo Antioxidant Phenolic Profiling Maldini, Mariateresa D’Urso, Gilda Pagliuca, Giordana Petretto, Giacomo Luigi Foddai, Marzia Gallo, Francesca Romana Multari, Giuseppina Caruso, Donatella Montoro, Paola Pintore, Giorgio Foods Article 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 Arbutus unedo (A. unedo) plants. For a rapid digital record of A. unedo 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. MDPI 2019-07-27 /pmc/articles/PMC6723518/ /pubmed/31357632 http://dx.doi.org/10.3390/foods8080294 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Maldini, Mariateresa D’Urso, Gilda Pagliuca, Giordana Petretto, Giacomo Luigi Foddai, Marzia Gallo, Francesca Romana Multari, Giuseppina Caruso, Donatella Montoro, Paola Pintore, Giorgio HPTLC-PCA Complementary to HRMS-PCA in the Case Study of Arbutus unedo Antioxidant Phenolic Profiling |
title | HPTLC-PCA Complementary to HRMS-PCA in the Case Study of Arbutus unedo Antioxidant Phenolic Profiling |
title_full | HPTLC-PCA Complementary to HRMS-PCA in the Case Study of Arbutus unedo Antioxidant Phenolic Profiling |
title_fullStr | HPTLC-PCA Complementary to HRMS-PCA in the Case Study of Arbutus unedo Antioxidant Phenolic Profiling |
title_full_unstemmed | HPTLC-PCA Complementary to HRMS-PCA in the Case Study of Arbutus unedo Antioxidant Phenolic Profiling |
title_short | HPTLC-PCA Complementary to HRMS-PCA in the Case Study of Arbutus unedo Antioxidant Phenolic Profiling |
title_sort | hptlc-pca complementary to hrms-pca in the case study of arbutus unedo antioxidant phenolic profiling |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6723518/ https://www.ncbi.nlm.nih.gov/pubmed/31357632 http://dx.doi.org/10.3390/foods8080294 |
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