Streamlining Cannabis Testing Using GC-MS and GCxGC-MS

Significance of the Topic

Cannabis products contain a complex mix of terpenes and cannabinoids that determine their potency, aroma, and therapeutic effects. Accurate compositional analysis is critical for product safety, quality assurance, and compliance with regulatory standards. GC-TOFMS and GCxGC-TOFMS provide enhanced separation and detection capabilities, enabling laboratories to profile diverse analytes across broad concentration ranges while reducing manual sample handling.

Objectives and Study Overview

This work aimed to streamline cannabis testing by minimizing sample preparation, shortening analysis times, and maximizing information obtained per run. The study evaluated both one-dimensional GC-TOFMS and comprehensive two-dimensional GCxGC-TOFMS approaches, assessed automated data processing strategies, and compared their performance in identifying terpenes, cannabinoids, and miscellaneous compounds in various cannabis-derived products.

Methodology and Instrumentation

Samples were prepared by solvent extraction targeting monoterpenes (C10), sesquiterpenes (C15), diterpenes (C20), and cannabinoids. Analyses employed GC-TOFMS and GCxGC-TOFMS with the following parameters:

• Injection: 1 µL liquid injection at 250 °C
• Carrier gas: helium at 1.0 mL/min constant flow
• First-dimension column: Rxi-5 MS (30 m × 0.25 mm × 0.25 µm)
• Second-dimension column: Rxi-17 Sil MS (0.6 m × 0.25 mm × 0.25 µm)
• Oven program: 40 °C (5 min), ramp 10 °C/min to 300 °C, hold 2 min; secondary oven 5 °C above primary
• Modulation: 2 s period with 15 °C offset relative to secondary oven
• Mass spectrometer: LECO Pegasus BT 4D, EI ionization at 250 °C, mass range 45–600 m/z, acquisition 10 spectra/s (1D) and 200 spectra/s (2D)

Instrumentation Used

• Gas chromatograph: Agilent 7890 with LECO dual-stage quad jet modulator and L-PAL 3 autosampler
• Mass spectrometer: LECO Pegasus BT 4D (electron ionization, m/z 45–600)
• Automated software: spectral deconvolution, library similarity search, mass delta calculation, retention index filtering

Key Results and Discussion

• GC-TOFMS effectively deconvoluted major terpenes such as β-ocimene and m-camphorene, achieving library similarities >850/1000 and mass deltas <0.1 Da.
• GCxGC-TOFMS enhanced separation of coeluting compounds and extended coverage of minor constituents across C10–C20 classes.
• Comprehensive two-dimensional analysis provided clear resolution and confident identification of cannabinoids including Δ9-THC, CBD, and CBG.
• Automated processing accelerated data review and increased compound identification certainty by combining spectral similarity, mass accuracy, and retention index filtering.

Benefits and Practical Applications

• Unified profiling replaces multiple targeted assays, simplifying laboratory workflows.
• Reduced sample preparation and faster throughput boost efficiency for high-volume testing.
• Improved resolution enhances quantitation accuracy and impurity detection for QA/QC.
• Method flexibility supports analysis of diverse cannabis matrices and product types.

Future Trends and Opportunities

Emerging developments in high-throughput automation, machine learning–driven spectral interpretation, and real-time screening promise further advances in cannabis analysis. Integration of GCxGC with orthogonal detection techniques, expansion of spectral libraries, and cloud-based data sharing will enhance regulatory oversight and product transparency.

Conclusion

The combined use of GC-TOFMS and GCxGC-TOFMS delivers robust, efficient profiling of cannabis terpenes and cannabinoids. Streamlined sample preparation, comprehensive separation, and automated data processing create powerful workflows for ensuring product quality, safety, and regulatory compliance.