A comparison of high- and low-resolution gas chromatography–mass spectrometry for herbal product classification: A case study with Ocimum essential oils

Evelyn J. Abraham, E. Diane Wallace, Joshua J. Kellogg

Research output: Contribution to journalArticlepeer-review


Introduction: Selection of marker compounds for targeted chemical analysis is complicated when considering varying instrumentation and closely related plant species. High-resolution gas chromatography–mass spectrometry (GC–MS), via orbitrap detection, has yet to be evaluated for improved marker compound selection. Objective: This study directly compares high- and low-resolution GC–MS for botanical maker compound selection using Ocimum tenuiflorum L. (OT) and Ocimum gratissimum L. (OG) for botanical ingredient authentication. Methods: The essential oils of OT and OG were collected via hydrodistillation before untargeted chemical analysis with gas chromatography coupled to single-quadrupole (GC-SQ) and orbitrap (GC-Orbitrap) detectors. The Global Natural Products Social Molecular Networking (GNPS) software was used for compound annotation, and a manual search was used to find the 41 most common Ocimum essential oil metabolites. Results: The GC-Orbitrap resulted in 1.7-fold more metabolite detection and increased dynamic range compared to the GC-SQ. Spectral matching and manual searching were improved with GC-Orbitrap data. Each instrument had differing known compound concentrations; however, there was an overlap of six compounds with higher abundance in OG than OT and three compounds with a higher abundance in OT than OG, suggesting consistent detection of the most variable compounds. An unsupervised principal component analysis (PCA) could not discern the two species with either dataset. Conclusion: GC-Orbitrap instrumentation improves compound detection, dynamic range, and feature annotation in essential oil analysis. However, considering both high- and low-resolution data may improve reliable marker compound selection, as GC-Orbitrap analysis alone did not improve unsupervised separation of two Ocimum species compared to GC-SQ data.

Original languageEnglish (US)
Pages (from-to)680-691
Number of pages12
JournalPhytochemical Analysis
Issue number6
StatePublished - Aug 2023

All Science Journal Classification (ASJC) codes

  • Analytical Chemistry
  • Food Science
  • Biochemistry
  • Molecular Medicine
  • Plant Science
  • Drug Discovery
  • Complementary and alternative medicine

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