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Gas Chromatographic Fingerprint Analysis for the Comparison of Seized Cannabis Samples
Tijdschriftbijdrage - Tijdschriftartikel
Cannabis sativa L. is widely used as recreational illegal drugs. Illicit Cannabis profiling,
comparing seized samples, is challenging due to natural Cannabis heterogeneity. The aim of this
study was to use GC–FID and GC–MS herbal fingerprints for intra (within)- and inter (between)-
location variability evaluation. This study focused on finding an acceptable threshold to link seized
samples. Through Pearson correlation-coefficient calculations between intra-location samples, ‘linked’
thresholds were derived using 95% and 99% confidence limits. False negative (FN) and false positive
(FP) error rate calculations, aiming at obtaining the lowest possible FP value, were performed for
different data pre-treatments. Fingerprint-alignment parameters were optimized using Automated
Correlation-Optimized Warping (ACOW) or Design of Experiments (DoE), which presented similar
results. Hence, ACOW data, as reference, showed 54% and 65% FP values (95 and 99% confidence,
respectively). An additional fourth root normalization pre-treatment provided the best results for
both the GC–FID and GC–MS datasets. For GC–FID, which showed the best improved FP error
rate, 54 and 65% FP for the reference data decreased to 24 and 32%, respectively, after fourth root
transformation. Cross-validation showed FP values similar as the entire calibration set, indicating the
representativeness of the thresholds. A noteworthy improvement in discrimination between seized
Cannabis samples could be concluded.
comparing seized samples, is challenging due to natural Cannabis heterogeneity. The aim of this
study was to use GC–FID and GC–MS herbal fingerprints for intra (within)- and inter (between)-
location variability evaluation. This study focused on finding an acceptable threshold to link seized
samples. Through Pearson correlation-coefficient calculations between intra-location samples, ‘linked’
thresholds were derived using 95% and 99% confidence limits. False negative (FN) and false positive
(FP) error rate calculations, aiming at obtaining the lowest possible FP value, were performed for
different data pre-treatments. Fingerprint-alignment parameters were optimized using Automated
Correlation-Optimized Warping (ACOW) or Design of Experiments (DoE), which presented similar
results. Hence, ACOW data, as reference, showed 54% and 65% FP values (95 and 99% confidence,
respectively). An additional fourth root normalization pre-treatment provided the best results for
both the GC–FID and GC–MS datasets. For GC–FID, which showed the best improved FP error
rate, 54 and 65% FP for the reference data decreased to 24 and 32%, respectively, after fourth root
transformation. Cross-validation showed FP values similar as the entire calibration set, indicating the
representativeness of the thresholds. A noteworthy improvement in discrimination between seized
Cannabis samples could be concluded.
Tijdschrift: Molecules
ISSN: 1420-3049
Issue: 21
Volume: 26
Jaar van publicatie:2021
Trefwoorden:chromatographic fingerprint, alignment optimization, design of experiments, data preprocessing, comparison intra- and inter-location samples
BOF-keylabel:ja
IOF-keylabel:ja
BOF-publication weight:1
Auteurs:Regional
Authors from:Government, Higher Education
Toegankelijkheid:Open