With an increasing appreciation for the unique pharmacological properties associated with distinct, individual cannabinoids of Cannabis sativa, there is demand for accurate and reliable quantification for a growing number of them. Although recent methods are based on highly selective chromatography-mass spectrometry technology, most are limited to a few cannabinoids, while relying on unnecessarily sophisticated and expensive ultra-high performance liquid chromatography and tandem mass spectrometry. Here we report an optimised, simple extraction method followed by a reliable and simple high performance liquid chromatography method for separation. The detection is performed using a time-of-flight mass spectrometer that is available in most natural products research laboratories. Due to the simplicity of instrumentation, and the robustness resulting from a high resolution in the chromatography of isobaric cannabinoids, the method is well suited for routine phytocannabinoid analysis for a range of applications. The method was validated in terms of detection and quantification limits, repeatability, and recoveries for a total of 17 cannabinoids: detection limits were in the range 11–520 pg when using a 1 µL sample injection volume, and the recovery percentages ranged from 85% to 108%. The validated method was subsequently applied to determine cannabinoid composition in the inflorescences of several medicinal Cannabis sativa varieties.

Commercial tea tree oil (TTO) has to conform chemically to the international standard ISO4730: 2017, which defines acceptable ranges for the 15 main terpenoids therein. Lack of in‐house capacity for the technology typically required for terpenoid quantification (GC‐FID) necessitates that Australian TTO producers outsource the analyses to commercial service providers. This is associated with high cost and slow turnaround times, which have been recognized as limiting factors for TTO process optimization in the areas of quality assurance, distillation and blending. This paper describes the testing of two custom portable Raman devices with different lasers (785 and 1064 nm) for the relative quantification of the 15 main TTO components using model‐based predictions. Initial testing showed that the 1064‐nm device provided superior data for TTO predictions. Machine‐learning algorithms were trained with spectral data from the 1064‐nm device and corresponding GC‐FID data from 214 TTO samples. Hold‐over validation (HV) correlations between actual and predicted values using up to 53 unseen samples showed r² at or above 0.92 for 10 and at or above 0.95 for 6 of the 15 specified terpenoids. The highly abundant key TTO quality compound terpinen‐4‐ol showed an HV r² of 0.96 with a root mean square error (RMSE) of 0.37%, whereas the lowly abundant key compound 1,8‐cineole showed an HV r² of 1.00 with a RMSE of 0.13%. These results indicated a strong potential for Raman spectrometry to provide real‐time product quality data at TTO distillation sites enabling direct feedback control and process optimisations.