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Metabolomics Approach to Characterize Green Olive Leaf Extracts Classified Based on Variety and Season
The huge interest in the health-related properties of plant polyphenols to be applied in food and health-related sectors has brought about the development of sensitive analytical methods for metabolomic characterization. Olive leaves constitute a valuable waste rich in polyphenols with functional pr...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9735528/ https://www.ncbi.nlm.nih.gov/pubmed/36501360 http://dx.doi.org/10.3390/plants11233321 |
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author | Difonzo, Graziana Crescenzi, Maria Assunta Piacente, Sonia Altamura, Giuseppe Caponio, Francesco Montoro, Paola |
author_facet | Difonzo, Graziana Crescenzi, Maria Assunta Piacente, Sonia Altamura, Giuseppe Caponio, Francesco Montoro, Paola |
author_sort | Difonzo, Graziana |
collection | PubMed |
description | The huge interest in the health-related properties of plant polyphenols to be applied in food and health-related sectors has brought about the development of sensitive analytical methods for metabolomic characterization. Olive leaves constitute a valuable waste rich in polyphenols with functional properties. A (HR)LC-ESI-ORBITRAP-MS analysis with a multivariate statistical analysis approach using PCA and/or PLS-DA projection methods were applied to identify polyphenols in olive leaf extracts of five varieties from the Apulia region (Italy) in two different seasonal times. A total of 26 metabolites were identified, further finding that although metabolites are common among the different cultivars, they differ in the relative intensity of each peak and within each cultivar in the two seasonal periods taken into consideration. The results of the total phenol contents showed the highest content in November for Bambina and Cima di Mola varieties (1816 and 1788 mg/100 g, respectively), followed by Coratina, Leccino, and Cima di Melfi; a similar trend was found for the antioxidant activity and RapidOxy evaluations by reaching in Bambina values of 45 mmol TE/100 g and 85 min of induction time. |
format | Online Article Text |
id | pubmed-9735528 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-97355282022-12-11 Metabolomics Approach to Characterize Green Olive Leaf Extracts Classified Based on Variety and Season Difonzo, Graziana Crescenzi, Maria Assunta Piacente, Sonia Altamura, Giuseppe Caponio, Francesco Montoro, Paola Plants (Basel) Article The huge interest in the health-related properties of plant polyphenols to be applied in food and health-related sectors has brought about the development of sensitive analytical methods for metabolomic characterization. Olive leaves constitute a valuable waste rich in polyphenols with functional properties. A (HR)LC-ESI-ORBITRAP-MS analysis with a multivariate statistical analysis approach using PCA and/or PLS-DA projection methods were applied to identify polyphenols in olive leaf extracts of five varieties from the Apulia region (Italy) in two different seasonal times. A total of 26 metabolites were identified, further finding that although metabolites are common among the different cultivars, they differ in the relative intensity of each peak and within each cultivar in the two seasonal periods taken into consideration. The results of the total phenol contents showed the highest content in November for Bambina and Cima di Mola varieties (1816 and 1788 mg/100 g, respectively), followed by Coratina, Leccino, and Cima di Melfi; a similar trend was found for the antioxidant activity and RapidOxy evaluations by reaching in Bambina values of 45 mmol TE/100 g and 85 min of induction time. MDPI 2022-12-01 /pmc/articles/PMC9735528/ /pubmed/36501360 http://dx.doi.org/10.3390/plants11233321 Text en © 2022 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 Difonzo, Graziana Crescenzi, Maria Assunta Piacente, Sonia Altamura, Giuseppe Caponio, Francesco Montoro, Paola Metabolomics Approach to Characterize Green Olive Leaf Extracts Classified Based on Variety and Season |
title | Metabolomics Approach to Characterize Green Olive Leaf Extracts Classified Based on Variety and Season |
title_full | Metabolomics Approach to Characterize Green Olive Leaf Extracts Classified Based on Variety and Season |
title_fullStr | Metabolomics Approach to Characterize Green Olive Leaf Extracts Classified Based on Variety and Season |
title_full_unstemmed | Metabolomics Approach to Characterize Green Olive Leaf Extracts Classified Based on Variety and Season |
title_short | Metabolomics Approach to Characterize Green Olive Leaf Extracts Classified Based on Variety and Season |
title_sort | metabolomics approach to characterize green olive leaf extracts classified based on variety and season |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9735528/ https://www.ncbi.nlm.nih.gov/pubmed/36501360 http://dx.doi.org/10.3390/plants11233321 |
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