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 ( ) plants. For a rapid...

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Bibliographic Details
Published in:Foods 2019-07, Vol.8 (8), p.294
Main Authors: Maldini, Mariateresa, D'Urso, Gilda, Pagliuca, Giordana, Petretto, Giacomo Luigi, Foddai, Marzia, Gallo, Francesca Romana, Multari, Giuseppina, Caruso, Donatella, Montoro, Paola, Pintore, Giorgio
Format: Article
Language:English
Subjects:
antioxidant activities
antioxidants
Arbutus unedo
case studies
fruits
HPTLC
LC–HRMS
leaves
mass spectrometry
metabolomics
PCA
principal component analysis
provenance
Sardinia
secondary metabolites
thin layer chromatography
tissues
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Summary: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 ( ) plants. For a rapid digital record of 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.
ISSN:2304-8158
2304-8158
DOI:10.3390/foods8080294