Issue 10, 2019

Non-contact light-radiation thermal desorption-assisted LTP ionization miniature ion trap mass spectrometry for rapid analysis of the flavouring substances in pipe tobacco

Abstract

A novel method was established for rapid detection and confirmation of flavouring substances in flavoured pipe tobacco by a light-radiation thermal desorption-assisted low temperature plasma ionization source coupled with a miniature ion trap mass spectrometer (TD-LTP-ITMS). To improve the sensitivity of flavouring substances with low volatility, the heated light from a halogen lamp was applied to improve the partial pressure in the atmosphere. Four common flavours, vanillin, ethyl vanillin, tartaric acid and citric acid, were selected to demonstrate the signal intensities achieved with light-radiation heating. The experimental results prove that the signals were enhanced by more than 2.1 fold compared with those obtained at room temperature. Quantitative analysis was also performed, and the linear range was about two orders of magnitude. TD-LTP-ITMS was optimized to analyze each sample of the flavoured pipe tobacco and its extracted liquid within twenty seconds of heating. Meanwhile, vanillin and ethyl vanillin were confirmed by tandem mass spectrometry (MS/MS) in a complex matrix. The experimental results indicate that the developed method has the potential to rapidly determine the flavouring substances in complex matrices with high throughput.

Graphical abstract: Non-contact light-radiation thermal desorption-assisted LTP ionization miniature ion trap mass spectrometry for rapid analysis of the flavouring substances in pipe tobacco

Supplementary files

Article information

Article type
Technical Note
Submitted
21 Dec 2018
Accepted
06 Feb 2019
First published
25 Feb 2019

Anal. Methods, 2019,11, 1410-1415

Non-contact light-radiation thermal desorption-assisted LTP ionization miniature ion trap mass spectrometry for rapid analysis of the flavouring substances in pipe tobacco

C. Song, S. Wang, W. Wang, C. Xu, G. Chai, L. Ji, J. Zhang, W. Yang and W. Zhao, Anal. Methods, 2019, 11, 1410 DOI: 10.1039/C8AY02784F

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