Cannabis profiling of seized samples: An intra-location variability study using gas chromatography-mass spectrometry...

Area of Science:

• Forensic Science
• Analytical Chemistry
• Pharmacognosy

Background:

• Cannabis is a globally seized drug, necessitating reliable profiling for judicial investigations.
• Natural heterogeneity of cannabis complicates accurate comparison of seized herbal material.
• Gas chromatography-mass spectrometry (GC-MS) is utilized for cannabinoid profiling.

Purpose of the Study:

• To evaluate the effectiveness of data pretreatment methods in reducing false positives (FPs) during illicit cannabis profiling.
• To establish decision thresholds for comparing seized cannabis samples based on cannabinoid profiles.
• To assess the variability within and between cannabis cultivation locations.

Main Methods:

• Gas chromatography-mass spectrometry (GC-MS) was used to generate cannabinoid profiles.
• Pearson correlation coefficients and confidence limits (95% and 99%) were applied to intra-location samples.
• Log transformation was investigated as a data pretreatment method to minimize FP rates.
• A combined data matrix of all seized samples was constructed to improve model representativeness.

Main Results:

• Log transformation pretreatment significantly decreased FP rates compared to internal standard normalization.
• Initial dataset (97 samples) showed FP reduction from 38%/45% to 17%/22%.
• Combined dataset (all samples) with log transformation improved FP rates from 58%/64% to 21%/26%.

Conclusions:

• Data pretreatment, particularly log transformation, substantially enhances the ability to distinguish seized cannabis samples.
• Despite improvements, the current FP rate is not sufficiently low for definitive legal defense.
• Further refinement of analytical methods is required to achieve legally defensible cannabis profiling.