Cannabis profiling of seized samples: An intra ‐location variability study using gas chromatography–mass spectrometry profiles and multivariate data analysis

A cannabis profiling approach was developed on a large and representative data set, combining statistics with multivariate data analysis. Based on the chemical profiles, the intra (within)- and inter (between)-location variabilities were studied. Different data pretreatments were evaluated on their discriminating power by calculating the false positive (FP) error rate. This manuscript indicated the large influence of data preprocessing with a significant decrease in FPs, but still not till a level acceptable to defend in court. AbstractYearly, cannabis belongs to the most seized drugs worldwide. During judicial investigations, illicit cannabis profiling can be performed to compare seized herbal material. However, comparison is challenging because of the natural heterogeneity of the psychoactive crop. Gas chromatography –mass spectrometry (GC–MS) profiles, consisting of eight cannabinoids, were used to study the intra-location (within) and inter-location (between) variabilities. Decision thresholds were derived from the 95% and 99% confidence limits, applying Pearson correlation coefficients for the intra-locat ion samples. The false negatives and false positives (FPs) determined the discriminative power of different pretreatments applied to obtain the lowest FP error rate possible. Initially, a 97 samples data set was used and with log transformation as pretreatment, a decrease in FPs from 38% and 45% FPs to 17% and 22%, for both confidence limits, respectively, was seen ...
Source: Drug Testing and Analysis - Category: Drugs & Pharmacology Authors: Tags: RESEARCH ARTICLE Source Type: research