Issue 22, 2019

Influence of photooxidation on the lipid profile of rapeseed oil using UHPLC-QTOF-MS and multivariate data analysis

Abstract

Rapeseed oil, the third most commonly consumed vegetable oil in the world, can easily deteriorate under photooxidative conditions. However, there is no data describing its lipid profile, which provides good information on the stability and quality of the oil. This paper aims to study the lipid composition of rapeseed oil during storage for 12 days under light by ultrahigh-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS). 112 kinds of triacylglycerol (TAG), 13 kinds of diacylglycerol (DAG) and 32 kinds of (phospholipid) PL were identified quantitatively. The total lipid content decreased from 4.14 × 108 to 3.21 × 108 ng mL−1. Unsupervised principal component analysis (PCA) and supervised orthogonal partial least square (OPLS) analysis were employed for the characterization of statistically significant differences in identified lipid species, providing better visualization of lipidomic differences between control and experimental samples. The distribution of lipid classes was modified with a decreased proportion of TAG accompanied by the increase of DAG and PLs. Some unique lipid species, such as TG (18:1/18:2/18:2), TG (18:1/18:1/18:1), TG (18:2/22:1/22:1), DG (18:2/18:2), and DG (18:1/18:1) showed great changes and some PA species, including PA (18:2/18:2), PA (18:1/18:2), PA (18:1/18:1) and PA (16:0/18:2), emerged during the last three days of storage. The data can serve as a theoretical basis for the quality assessment of rapeseed oil during storage.

Graphical abstract: Influence of photooxidation on the lipid profile of rapeseed oil using UHPLC-QTOF-MS and multivariate data analysis

Supplementary files

Article information

Article type
Paper
Submitted
23 Feb 2019
Accepted
19 Apr 2019
First published
23 Apr 2019

Anal. Methods, 2019,11, 2903-2917

Influence of photooxidation on the lipid profile of rapeseed oil using UHPLC-QTOF-MS and multivariate data analysis

Y. Wu, F. Xu, S. Ji, J. Ji, F. Qin, X. Ju and L. Wang, Anal. Methods, 2019, 11, 2903 DOI: 10.1039/C9AY00385A

To request permission to reproduce material from this article, please go to the Copyright Clearance Center request page.

If you are an author contributing to an RSC publication, you do not need to request permission provided correct acknowledgement is given.

If you are the author of this article, you do not need to request permission to reproduce figures and diagrams provided correct acknowledgement is given. If you want to reproduce the whole article in a third-party publication (excluding your thesis/dissertation for which permission is not required) please go to the Copyright Clearance Center request page.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements