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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...

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Autores principales: Difonzo, Graziana, Crescenzi, Maria Assunta, Piacente, Sonia, Altamura, Giuseppe, Caponio, Francesco, Montoro, Paola
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
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.
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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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