High-Performance Thin-Layer Chromatography hyphenated with image processing and chemometrics as a tool for forensic discrimination of Cannabis sativa L. chemotypes

Abstract

Cannabis sativa L. is the most widely cultivated, trafficked, and abused illicit drug. The reliable distinction between drug type and fiber type C. sativa remains a topic of interest for forensic chemists. For the first time, we applied a combination of simple, cost-effective, and reliable High-Performance Thin-Layer Chromatography (HPTLC) with image analysis as well as sophisticated multivariate tools for differentiating C. sativa drug, fiber and intermediate chemotypes. After extraction, major cannabinoids from 43 seized C. sativa were separated using the HPTLC method. Peak areas of Δ9-THC, CBN, and CBD were calculated by simple image processing, and Xfactor = [THC + CBN]/CBD was determined as criteria used to discriminate three C. sativa chemotypes. The obtained results were compared with Gas Chromatography with Flame Ionization Detection (GC-FID) as the reference method for the determination of Xfactor.Principal Component Analysis and Hierarchic Cluster Analysis were applied to classify three C. sativa chemotypes according to their chemical pattern. The proposed approach clearly distinguishes 26 drugs, 13 fiber, and 4 intermediate chemotypes in seized C. sativa, aligning with GC-FID analysis. The results showed that the HPTLC technique in combination with multivariate methods is an accurate and reliable tool for high-throughput and forensic screening of three C. sativa chemotypes. Compounds such as Δ9-THC and CBD were marked as the most important cannabinoids responsible for the classification of the seized C. sativa chemotypes.