Analytical and chemometric approaches for quality characterization of Cannabis sativa L. with focus on cannabinoids

The quality characterization of Cannabis sativa L., especially with respect to its containing cannabinoids, is associated with many analytical challenges. Within this context, the power of chemometrics is recognized for interpretation and optimization of analytical procedures [1], as was undertaken in this work. Initially, Design of Experiments was employed for the optimization of extraction conditions following rational comparison of extraction techniques [2]. In parallel, effective chromatographic methods based on UPLC-PDA and GC-MS were developed for quantitative purposes and characterization of extracts. Pattern recognition techniques were then applied on HPTLC chromatograms to investigate the effect of extraction solvent on metabolite fingerprints and cannabinoid yield. Furthermore, classification and discrimination of hemp samples from different Greek regions and cultivars was attempted through chemometric processing. To this end, both first- and second-order data from LC-PDA were analyzed with multivariate techniques, also exploiting the multi-way nature of data. Finally, an NMR-based workflow was developed for metabolic profiling of C. sativa samples and identification of potential biomarker compounds.

 

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There is no conflict of interest

• References

• 1 Mudge EM. et al Sci Rep 2018; 8: 13090
• 2 Tzimas PS. et al Anal Chim Acta 2021; 1150: 338200.

Publikationsverlauf

Artikel online veröffentlicht:
13. Dezember 2021