Preprint Article Version 1 This version is not peer-reviewed

Chiral Trapped Headspace GC-QMS-IMS: Boosting Untargeted Benchtop Volatilomics to the Next Level

Version 1 : Received: 16 July 2024 / Approved: 16 July 2024 / Online: 16 July 2024 (13:01:20 CEST)

How to cite: Bodenbender, L.; Rohn, S.; Sauer, S.; Jungen, M.; Weller, P. Chiral Trapped Headspace GC-QMS-IMS: Boosting Untargeted Benchtop Volatilomics to the Next Level. Preprints 2024, 2024071331. https://doi.org/10.20944/preprints202407.1331.v1 Bodenbender, L.; Rohn, S.; Sauer, S.; Jungen, M.; Weller, P. Chiral Trapped Headspace GC-QMS-IMS: Boosting Untargeted Benchtop Volatilomics to the Next Level. Preprints 2024, 2024071331. https://doi.org/10.20944/preprints202407.1331.v1

Abstract

In the field of quality analysis of food and flavoring products, gas chromatography – quadrupole mass spectrometry – ion mobility spectrometry (GC-QMS-IMS) is a powerful technique for the simultaneous detection of volatile organic compounds (VOC) by both QMS and IMS. GC is an established technique for the separation of complex VOC-rich foods such as beverages, dairy and fruit products as well as flavorings in general. While the subsequent detection by IMS features soft ionization of fragile compounds (e.g., terpenes) with characteristic drift times, MS provides the analytes’ m/z-values for database substance identification. A limitation of the prominently used static headspace-based GC-QMS-IMS systems is the substantially higher sensitivity of IMS in comparison to full scan QMS, which results in the detection of relevant VOC only in IMS, but not in the QMS analyzer. The present study describes a new prototypic trapped-headspace (THS)-GC-QMS-IMS setup, with optimized active flow regulation, able to gain valuable data of both detectors. This ultimately allows the combination of a soft ionization with m/z values obtained from database-searchable electron ionization (EI) spectra and as such, offers a substantial advantage in fields of quality control. The new setup features aligned retention times for IMS and MS and sufficient signal intensities for QMS and IMS. The analytical setup was evaluated with a set of mango puree samples from various provenances and the data was evaluated by suitable machine learning approaches. The results demonstrate that THS-GC-QMS-IMS allows for the classification of mango purees from different cultivars and can be a promising alternative method for authenticity control of food, flavors, and beverages.

Keywords

HS-GC-MS-IMS; ion mobility spectrometry; volatile organic compounds; trapped headspace sampling; authentication; mango puree; chemometrics

Subject

Biology and Life Sciences, Food Science and Technology

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