Quantitative assessment of epoxide formation in oil and mayonnaise by 1H-13C HSQC NMR spectroscopy
[Display omitted] •Epoxides can be quantified reproducibly and sensitively by HSQC NMR.•Lipid hydroperoxides, aldehydes, and epoxides can be quantified simultaneously.•Epoxides appear to be primarily formed via alkoxyl radicals.•Epoxides have a limited potential as an early oxidation marker.•Quantif...
Gespeichert in:
Veröffentlicht in: | Food chemistry 2022-10, Vol.390, p.133145-133145, Article 133145 |
---|---|
Hauptverfasser: | , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | [Display omitted]
•Epoxides can be quantified reproducibly and sensitively by HSQC NMR.•Lipid hydroperoxides, aldehydes, and epoxides can be quantified simultaneously.•Epoxides appear to be primarily formed via alkoxyl radicals.•Epoxides have a limited potential as an early oxidation marker.•Quantification of epoxides is critical for resolving lipid oxidation pathways.
Lipid oxidation is detrimental for the quality of oil-based foods. Historically, lipid oxidation research focussed on hydroperoxides and aldehydes, but a third class, the epoxides, have been proposed to resolve observed mechanistic anomalies. Here, we developed a 2D 1H-13C HSQC NMR spectroscopic method to quantify epoxides in food in a reproducible (relative standard deviation ≤11.6 %) and sensitive (LoQ 0.62 mmol/kg oil) manner. Lipid hydroperoxides, aldehydes, and epoxides generated in rapeseed oil and mayonnaise were quantified over time by NMR. Epoxides accounted at most for 10–40 % of the products. They were formed after hydroperoxide accumulation, most likely primarily via alkoxyl radical intermediates, which limits their potential as an early oxidation marker. As 99 % and ∼60 % of the epoxide signal intensities were assigned in a fatty acid and sub-structure specific manner, respectively, our quantitative HSQC method will enable unravelling and quantitative modelling of lipid oxidation mechanisms. |
---|---|
ISSN: | 0308-8146 1873-7072 |
DOI: | 10.1016/j.foodchem.2022.133145 |