Atmospheric pressure chemical ionisation (APCI) and photoionisation (APPI) mass spectrometry for detection of unsaturated fatty acids: Potential for rapid detection of adulteration of vegetable oils

Ilya Strashnov*, Jamie D. Gilmour, Andrew Cannavan, Gang Chen, Champa Dissanayake, Biyagamage Ruchika Fernando, Simon Kelly, Syahidah Akmal Muhammad, Dileep Kumar Singh, Zhenzhen Xu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Adulteration of vegetable oils to maximize profit is a worldwide problem. Atmospheric pressure chemical ionisation (APCI) and photoionisation (APPI) mass spectrometry methods were developed to detect the relative abundances of unsaturated fatty acids (FAs) present in vegetable oils with the objective of high throughput and rapid identification of adulteration. The ionisation efficiencies of both methods for unsaturated FA analysis, which are the most abundant in vegetable oils, have been found to be up to ∼2 orders of magnitude higher than those for saturated FAs. Using a quick calibration process, unsaturated FAs can be rapidly (within ∼2 min/sample) determined by comparison to standards (rapeseed oil), which allowed for calculation of correction factors for differences in ionisation efficiencies. Both techniques have been used in quick screening of the retail vegetable oils purchased in Sri Lanka and India. A simple chi-squared test has been applied to the C18:1, C18:2 and C18:3 FA experimental data. It is possible to differentiate e.g. olive, palm, sunflower, rapeseed, soya, mustard and other vegetable oils and make a quick decision based on chi-squared statistics regarding possible adulteration. The experimental values of FAs are in excellent agreement with those obtained by gas chromatography with a precision (RSD) of <3% for the most abundant FAs. The developed approach can be used for rapid screening of a large number of vegetable oil samples for possible adulteration prior to full GC analysis.

Original languageEnglish
Pages (from-to)3819-3828
Number of pages10
JournalAnalytical Methods
Volume11
Issue number30
DOIs
Publication statusPublished - 4 Jul 2019

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