de Falco, Bruna (2017) Metabolomic fingerprinting of food plants by nuclear magnetic resonance spectroscopy and gas chromatography/mass spectrometry. [Tesi di dottorato]
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| Item Type: | Tesi di dottorato |
|---|---|
| Resource language: | English |
| Title: | Metabolomic fingerprinting of food plants by nuclear magnetic resonance spectroscopy and gas chromatography/mass spectrometry |
| Creators: | Creators Email de Falco, Bruna defalcobruna@gmail.com |
| Date: | 10 April 2017 |
| Number of Pages: | 174 |
| Institution: | Università degli Studi di Napoli Federico II |
| Department: | Agraria |
| Dottorato: | Scienze agrarie e agroalimentari |
| Ciclo di dottorato: | 29 |
| Coordinatore del Corso di dottorato: | nome email D'Urso, Guido durso@unina.it |
| Tutor: | nome email Lanzotti, Virginia UNSPECIFIED |
| Date: | 10 April 2017 |
| Number of Pages: | 174 |
| Keywords: | Artichoke; cynara; sage; salvia; NMR; GCMS; PCA |
| Settori scientifico-disciplinari del MIUR: | Area 03 - Scienze chimiche > CHIM/06 - Chimica organica |
| Date Deposited: | 06 May 2017 14:37 |
| Last Modified: | 13 Mar 2018 13:28 |
| URI: | http://www.fedoa.unina.it/id/eprint/11729 |
| DOI: | 10.6093/UNINA/FEDOA/11729 |
Collection description
Metabolomic analysis of food plants allows to obtain a fingerprinting of plant extracts by using different techniques, such as NMR spectroscopy and mass spectrometry coupled with multivariate data analysis. In this dissertation, two plants of great interest in food industry were studied: the artichoke and sage. The metabolic profile of fourteen artichoke populations (Cynara cardunculus L. var. scolymus L. Fiori) and one cultivated cardoon (Cynara cardunculus L. var. altilis DC) was characterised. A comparative analysis between commercial short-day flowering chia (S. hispanica) seeds and mutant genotypes was also achieved in order to define possible differences in the chemical composition due to mutations. The analysis was also extended to two samples of chia seeds to evaluate the effect of fertilization and irrigation on the metabolite composition. Findings showed that an untargeted metabolomic approach may be an effective tool for chemotaxonomy classification when limited information are available. Moreover, metabolomics can be used as monitoring technique to control the agronomic management and its non-invasive features make it an ideal tool for pharmaceutical, agricultural and food industries.
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