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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MDPI AG
2022-12-01
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| Series: | Plants |
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| Online Access: | https://www.mdpi.com/2223-7747/11/23/3321 |
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| author | Graziana Difonzo Maria Assunta Crescenzi Sonia Piacente Giuseppe Altamura Francesco Caponio Paola Montoro |
| author_facet | Graziana Difonzo Maria Assunta Crescenzi Sonia Piacente Giuseppe Altamura Francesco Caponio Paola Montoro |
| author_sort | Graziana Difonzo |
| collection | DOAJ |
| 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 (<i>HR</i>)<i>LC-ESI-ORBITRAP-MS</i> 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. |
| first_indexed | 2024-03-09T17:35:19Z |
| format | Article |
| id | doaj.art-eb8d61763a85413696e5cb9e2198d1e5 |
| institution | Directory Open Access Journal |
| issn | 2223-7747 |
| language | English |
| last_indexed | 2024-03-09T17:35:19Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
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| spelling | doaj.art-eb8d61763a85413696e5cb9e2198d1e52023-11-24T11:56:00ZengMDPI AGPlants2223-77472022-12-011123332110.3390/plants11233321Metabolomics Approach to Characterize Green Olive Leaf Extracts Classified Based on Variety and SeasonGraziana Difonzo0Maria Assunta Crescenzi1Sonia Piacente2Giuseppe Altamura3Francesco Caponio4Paola Montoro5Department of Soil, Plant and Food Science, University of Bari Aldo Moro, Via Amendola, 165/a, I-70126 Bari, ItalyDipartimento di Farmacia, Università Degli Studi di Salerno, Via Giovanni Paolo II, 132, I-84084 Fisciano, ItalyDipartimento di Farmacia, Università Degli Studi di Salerno, Via Giovanni Paolo II, 132, I-84084 Fisciano, ItalyCentro di Ricerca, Sperimentazione e Formazione in Agricoltura Basile Caramia, Locorotondo, I-70010 Bari, ItalyDepartment of Soil, Plant and Food Science, University of Bari Aldo Moro, Via Amendola, 165/a, I-70126 Bari, ItalyDipartimento di Farmacia, Università Degli Studi di Salerno, Via Giovanni Paolo II, 132, I-84084 Fisciano, ItalyThe 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 (<i>HR</i>)<i>LC-ESI-ORBITRAP-MS</i> 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.https://www.mdpi.com/2223-7747/11/23/3321olive leaf extractmetabolomicsmultivariate analysispolyphenolsoxidationupcycling |
| spellingShingle | Graziana Difonzo Maria Assunta Crescenzi Sonia Piacente Giuseppe Altamura Francesco Caponio Paola Montoro Metabolomics Approach to Characterize Green Olive Leaf Extracts Classified Based on Variety and Season Plants olive leaf extract metabolomics multivariate analysis polyphenols oxidation upcycling |
| 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 | olive leaf extract metabolomics multivariate analysis polyphenols oxidation upcycling |
| url | https://www.mdpi.com/2223-7747/11/23/3321 |
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