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Title: Direct analysis of volatile organic compounds in foods by headspace extraction atmospheric pressure chemical ionisation mass spectrometry
Authors: Perez-Hurtado, P.
Palmer, Elliott A.
Owen, T.
Aldcroft, Clive
Allen, M.H.
Jones, J.
Creaser, Colin S.
Lindley, Martin R.
Turner, Matthew A.
Reynolds, James C.
Issue Date: 2017
Publisher: Wiley © The Authors
Citation: PEREZ-HURTADO, P. ... et al, 2017. Direct analysis of volatile organic compounds in foods by headspace extraction atmospheric pressure chemical ionisation mass spectrometry. Rapid Communications in Mass Spectrometry, 31 (22), pp. 1947–1956.
Abstract: Rationale The rapid screening of volatile organic compounds (VOCs) by direct analysis has potential applications in the areas of food and flavour science. Currently the technique of choice for VOC analysis is gas chromatography-mass spectrometry (GC/MS). However, the long chromatographic run times and elaborate sample preparation associated with this technique has led a movement towards direct analysis techniques, such as selected ion flow tube mass spectrometry (SIFT-MS), proton transfer reaction mass spectrometry (PTR-MS) and electronic noses. The work presented here describes the design and construction of a Venturi jet-pump based modification for a compact mass spectrometer which enables the direct introduction of volatiles for qualitative and quantitative analysis. Methods Volatile organic compounds were extracted from the headspace of heated vials into the atmospheric pressure chemical ionization source of a quadrupole mass spectrometer using a Venturi pump. Samples were analysed directly with no prior sample preparation. Principal component analysis was used to differentiate between different classes of samples. Results The interface is shown to able to routinely detect problem analytes such as fatty acids and biogenic amines without the requirement of a derivatisation step, and is shown to be able to discriminate between four different varieties of cheese with good intra and inter-day reproducibility using an unsupervised principal component analysis model. Quantitative analysis is demonstrated using indole standards with limits of detection and quantification of 0.395 µg/ml and 1.316 µg/ml respectively, and then applied to measure indole in aged pork samples. Conclusions The methodology described has shown to be able to routinely detect highly reactive analytes such as volatile fatty acids and diamines without the need for a derivatisation step or lengthy chromatographic separations. The capability of the system is demonstrated by discriminating between different varieties of cheese and monitoring the spoilage of meats.
Description: This is an Open Access Article. It is published by Wiley under the Creative Commons Attribution 4.0 International Licence (CC BY). Full details of this licence are avaialble at: http://creativecommons.org/licenses/by/4.0/
Sponsor: The authors are grateful for the financial support from the EPSRC, which was awarded as part of the impact acceleration account.
Version: Published
DOI: 10.1002/rcm.7975
URI: https://dspace.lboro.ac.uk/2134/26424
Publisher Link: https://doi.org/10.1002/rcm.7975
Related Resource: https://doi.org/10.17028/rd.lboro.5841321
ISSN: 0951-4198
Appears in Collections:Published Articles (Chemistry)

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