Direct study of minor extra-virgin olive oil components without any sample modification. 1H NMR multisupression experiment: A powerful tool
•1H NMR multisupression approach gives very valuable information on EVOO composition.•Signals of sterols, triterpenes, squalene, fatty alcohols and wax esters were described.•Signals of phenols like tyrosol, hydroxytyrosol, oleocanthal and oleacein were also discussed.•This powerful tool is simple,...
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Veröffentlicht in: | Food chemistry 2017-08, Vol.228, p.301-314 |
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Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •1H NMR multisupression approach gives very valuable information on EVOO composition.•Signals of sterols, triterpenes, squalene, fatty alcohols and wax esters were described.•Signals of phenols like tyrosol, hydroxytyrosol, oleocanthal and oleacein were also discussed.•This powerful tool is simple, fast and does not require any modification of EVOO sample.
Proton Nuclear Magnetic Resonance (1H NMR) was employed to study monovarietal commercial Spanish extra-virgin olive oils (EVOO) (Arbequina, Arroniz, Cornicabra, Hojiblanca and Picual). Each sample was analyzed by a standard pulse and by an experiment suppressing the main lipid signals, enabling the detection of signals of minor components. The aim was to determine the possibilities of both 1H NMR approaches to characterize EVOO composition, focusing on acyl groups, squalene, sterols, triterpene acids/esters, fatty alcohols, wax esters and phenols (lignans, tyrosol, hydroxytyrosol, oleocanthal, oleacein, oleokoronal, oleomissional, ligstrodials and oleuropeindials), and to determine hydrolysis and oxidation levels. The signal assignments (in deuterated chloroform) are thoroughly described, identifying for the first time those of the protons of esters of phytol and of geranylgeraniol. Correct signal assignment is fundamental for obtaining sound results when interpreting statistical data from metabolomic studies of EVOO composition and adulteration, making it possible to differentiate and classify oils. |
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ISSN: | 0308-8146 1873-7072 |
DOI: | 10.1016/j.foodchem.2017.02.009 |