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HPLC Fingerprints for the Characterization of Walnuts and the Detection of Fraudulent Incidents
A high-pressure liquid chromatographic method coupled to diode array detector (HPLC-DAD) was developed for the determination of phenolic compounds that could be used as markers in authentication studies of walnuts belonging to the Chandler variety, originating from Bulgaria, Greece, and France. An u...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8468111/ https://www.ncbi.nlm.nih.gov/pubmed/34574256 http://dx.doi.org/10.3390/foods10092145 |
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author | Kalogiouri, Natasa P. Samanidou, Victoria F. |
author_facet | Kalogiouri, Natasa P. Samanidou, Victoria F. |
author_sort | Kalogiouri, Natasa P. |
collection | PubMed |
description | A high-pressure liquid chromatographic method coupled to diode array detector (HPLC-DAD) was developed for the determination of phenolic compounds that could be used as markers in authentication studies of walnuts belonging to the Chandler variety, originating from Bulgaria, Greece, and France. An ultrasound-assisted extraction (UAE) protocol applied in the extraction of phenolic compounds was optimized. The method was validated and the relative standard deviations (RSD%) of the within-day, and between-day assays was lower than 6.3 and 11.1, respectively, showing adequate precision, and good accuracy ranging from 86.4 (sinapic acid) to 98.4% (caffeic acid) for within-day assay, and from 90.1 (gallocatechin gallate) to 100.6% (gallic acid) for between-day assay. Eighteen phenolic compounds were determined belonging to the classes of phenolic acids and flavonoids. The quantification results were further processed with chemometrics, and a robust partial least square–discriminant analysis (PLS-DA) model was developed for the classification of the samples according to their geographical origin, proposing markers that could be used for the control of walnuts authenticity and the detection of fraudulent incidents. |
format | Online Article Text |
id | pubmed-8468111 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-84681112021-09-27 HPLC Fingerprints for the Characterization of Walnuts and the Detection of Fraudulent Incidents Kalogiouri, Natasa P. Samanidou, Victoria F. Foods Article A high-pressure liquid chromatographic method coupled to diode array detector (HPLC-DAD) was developed for the determination of phenolic compounds that could be used as markers in authentication studies of walnuts belonging to the Chandler variety, originating from Bulgaria, Greece, and France. An ultrasound-assisted extraction (UAE) protocol applied in the extraction of phenolic compounds was optimized. The method was validated and the relative standard deviations (RSD%) of the within-day, and between-day assays was lower than 6.3 and 11.1, respectively, showing adequate precision, and good accuracy ranging from 86.4 (sinapic acid) to 98.4% (caffeic acid) for within-day assay, and from 90.1 (gallocatechin gallate) to 100.6% (gallic acid) for between-day assay. Eighteen phenolic compounds were determined belonging to the classes of phenolic acids and flavonoids. The quantification results were further processed with chemometrics, and a robust partial least square–discriminant analysis (PLS-DA) model was developed for the classification of the samples according to their geographical origin, proposing markers that could be used for the control of walnuts authenticity and the detection of fraudulent incidents. MDPI 2021-09-10 /pmc/articles/PMC8468111/ /pubmed/34574256 http://dx.doi.org/10.3390/foods10092145 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Kalogiouri, Natasa P. Samanidou, Victoria F. HPLC Fingerprints for the Characterization of Walnuts and the Detection of Fraudulent Incidents |
title | HPLC Fingerprints for the Characterization of Walnuts and the Detection of Fraudulent Incidents |
title_full | HPLC Fingerprints for the Characterization of Walnuts and the Detection of Fraudulent Incidents |
title_fullStr | HPLC Fingerprints for the Characterization of Walnuts and the Detection of Fraudulent Incidents |
title_full_unstemmed | HPLC Fingerprints for the Characterization of Walnuts and the Detection of Fraudulent Incidents |
title_short | HPLC Fingerprints for the Characterization of Walnuts and the Detection of Fraudulent Incidents |
title_sort | hplc fingerprints for the characterization of walnuts and the detection of fraudulent incidents |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8468111/ https://www.ncbi.nlm.nih.gov/pubmed/34574256 http://dx.doi.org/10.3390/foods10092145 |
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