Geographical Characterization of Tunisian Olive Tree Leaves (cv. Chemlali) Using HPLC-ESI-TOF and IT/MS Fingerprinting with Hierarchical Cluster Analysis
The olive plant has been extensively studied for its nutritional value, whereas its leaves have been specifically recognized as a processing by-product. Leaves are considered by-products of olive farming, representing a significant material arriving to the olive mill. They have been considered for c...
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Journal of Analytical Methods in Chemistry |
| Online Access: | http://dx.doi.org/10.1155/2018/6789704 |
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| author | Amani Taamalli David Arráez Román Ana María Gómez Caravaca Mokhtar Zarrouk Antonio Segura Carretero |
| author_facet | Amani Taamalli David Arráez Román Ana María Gómez Caravaca Mokhtar Zarrouk Antonio Segura Carretero |
| author_sort | Amani Taamalli |
| collection | DOAJ |
| description | The olive plant has been extensively studied for its nutritional value, whereas its leaves have been specifically recognized as a processing by-product. Leaves are considered by-products of olive farming, representing a significant material arriving to the olive mill. They have been considered for centuries as an important herbal remedy in Mediterranean countries. Their beneficial properties are generally attributed to the presence of a range of phytochemicals such as secoiridoids, triterpenes, lignans, and flavonoids. With the aim to study the impact of geographical location on the phenolic compounds, Olea europaea leaves were handpicked from the Tunisian cultivar “Chemlali” from nine regions in the north, center, and south of Tunisia. The ground leaves were then extracted with methanol : water 80% (v/v) and analyzed by using high-performance liquid chromatography coupled to electrospray time of flight and ion trap mass spectrometry analyzers. A total of 38 compounds could be identified. Their contents showed significant variation among samples from different regions. Hierarchical cluster analysis was applied to highlight similarities in the phytochemical composition observed between the samples of different regions. |
| format | Article |
| id | doaj-art-ef6464d0ad864db381003a3d8d424ab2 |
| institution | Kabale University |
| issn | 2090-8865 2090-8873 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Analytical Methods in Chemistry |
| spelling | doaj-art-ef6464d0ad864db381003a3d8d424ab22025-02-03T06:48:39ZengWileyJournal of Analytical Methods in Chemistry2090-88652090-88732018-01-01201810.1155/2018/67897046789704Geographical Characterization of Tunisian Olive Tree Leaves (cv. Chemlali) Using HPLC-ESI-TOF and IT/MS Fingerprinting with Hierarchical Cluster AnalysisAmani Taamalli0David Arráez Román1Ana María Gómez Caravaca2Mokhtar Zarrouk3Antonio Segura Carretero4Laboratoire de Biotechnologie de l’Olivier, Centre de Biotechnologie de Borj-Cedria, Hammam-Lif, TunisiaCenter of Research and Development of Functional Food, Health Science Technological Park, Avda. del Conocimiento s/n, 18100 Granada, SpainCenter of Research and Development of Functional Food, Health Science Technological Park, Avda. del Conocimiento s/n, 18100 Granada, SpainLaboratoire de Biotechnologie de l’Olivier, Centre de Biotechnologie de Borj-Cedria, Hammam-Lif, TunisiaCenter of Research and Development of Functional Food, Health Science Technological Park, Avda. del Conocimiento s/n, 18100 Granada, SpainThe olive plant has been extensively studied for its nutritional value, whereas its leaves have been specifically recognized as a processing by-product. Leaves are considered by-products of olive farming, representing a significant material arriving to the olive mill. They have been considered for centuries as an important herbal remedy in Mediterranean countries. Their beneficial properties are generally attributed to the presence of a range of phytochemicals such as secoiridoids, triterpenes, lignans, and flavonoids. With the aim to study the impact of geographical location on the phenolic compounds, Olea europaea leaves were handpicked from the Tunisian cultivar “Chemlali” from nine regions in the north, center, and south of Tunisia. The ground leaves were then extracted with methanol : water 80% (v/v) and analyzed by using high-performance liquid chromatography coupled to electrospray time of flight and ion trap mass spectrometry analyzers. A total of 38 compounds could be identified. Their contents showed significant variation among samples from different regions. Hierarchical cluster analysis was applied to highlight similarities in the phytochemical composition observed between the samples of different regions.http://dx.doi.org/10.1155/2018/6789704 |
| spellingShingle | Amani Taamalli David Arráez Román Ana María Gómez Caravaca Mokhtar Zarrouk Antonio Segura Carretero Geographical Characterization of Tunisian Olive Tree Leaves (cv. Chemlali) Using HPLC-ESI-TOF and IT/MS Fingerprinting with Hierarchical Cluster Analysis Journal of Analytical Methods in Chemistry |
| title | Geographical Characterization of Tunisian Olive Tree Leaves (cv. Chemlali) Using HPLC-ESI-TOF and IT/MS Fingerprinting with Hierarchical Cluster Analysis |
| title_full | Geographical Characterization of Tunisian Olive Tree Leaves (cv. Chemlali) Using HPLC-ESI-TOF and IT/MS Fingerprinting with Hierarchical Cluster Analysis |
| title_fullStr | Geographical Characterization of Tunisian Olive Tree Leaves (cv. Chemlali) Using HPLC-ESI-TOF and IT/MS Fingerprinting with Hierarchical Cluster Analysis |
| title_full_unstemmed | Geographical Characterization of Tunisian Olive Tree Leaves (cv. Chemlali) Using HPLC-ESI-TOF and IT/MS Fingerprinting with Hierarchical Cluster Analysis |
| title_short | Geographical Characterization of Tunisian Olive Tree Leaves (cv. Chemlali) Using HPLC-ESI-TOF and IT/MS Fingerprinting with Hierarchical Cluster Analysis |
| title_sort | geographical characterization of tunisian olive tree leaves cv chemlali using hplc esi tof and it ms fingerprinting with hierarchical cluster analysis |
| url | http://dx.doi.org/10.1155/2018/6789704 |
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