Gas Chromatographic Fingerprint Analysis for the Comparison of Seized Cannabis Samples

<i>Cannabis sativa</i> 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...

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Autores principales:	Amorn Slosse, Filip Van Durme, Nele Samyn, Debby Mangelings, Yvan Vander Heyden
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	chromatographic fingerprint alignment optimization design of experiments data pre-processing comparison intra- and inter-location samples Organic chemistry QD241-441
Acceso en línea:	https://doaj.org/article/280787fe76794fa3a3bfece31c391a06
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spelling	oai:doaj.org-article:280787fe76794fa3a3bfece31c391a062021-11-11T18:36:39ZGas Chromatographic Fingerprint Analysis for the Comparison of Seized Cannabis Samples10.3390/molecules262166431420-3049https://doaj.org/article/280787fe76794fa3a3bfece31c391a062021-11-01T00:00:00Zhttps://www.mdpi.com/1420-3049/26/21/6643https://doaj.org/toc/1420-3049<i>Cannabis sativa</i> 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.Amorn SlosseFilip Van DurmeNele SamynDebby MangelingsYvan Vander HeydenMDPI AGarticlechromatographic fingerprintalignment optimizationdesign of experimentsdata pre-processingcomparison intra- and inter-location samplesOrganic chemistryQD241-441ENMolecules, Vol 26, Iss 6643, p 6643 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	chromatographic fingerprint alignment optimization design of experiments data pre-processing comparison intra- and inter-location samples Organic chemistry QD241-441
spellingShingle	chromatographic fingerprint alignment optimization design of experiments data pre-processing comparison intra- and inter-location samples Organic chemistry QD241-441 Amorn Slosse Filip Van Durme Nele Samyn Debby Mangelings Yvan Vander Heyden Gas Chromatographic Fingerprint Analysis for the Comparison of Seized Cannabis Samples
description	<i>Cannabis sativa</i> 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.
format	article
author	Amorn Slosse Filip Van Durme Nele Samyn Debby Mangelings Yvan Vander Heyden
author_facet	Amorn Slosse Filip Van Durme Nele Samyn Debby Mangelings Yvan Vander Heyden
author_sort	Amorn Slosse
title	Gas Chromatographic Fingerprint Analysis for the Comparison of Seized Cannabis Samples
title_short	Gas Chromatographic Fingerprint Analysis for the Comparison of Seized Cannabis Samples
title_full	Gas Chromatographic Fingerprint Analysis for the Comparison of Seized Cannabis Samples
title_fullStr	Gas Chromatographic Fingerprint Analysis for the Comparison of Seized Cannabis Samples
title_full_unstemmed	Gas Chromatographic Fingerprint Analysis for the Comparison of Seized Cannabis Samples
title_sort	gas chromatographic fingerprint analysis for the comparison of seized cannabis samples
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/280787fe76794fa3a3bfece31c391a06
work_keys_str_mv	AT amornslosse gaschromatographicfingerprintanalysisforthecomparisonofseizedcannabissamples AT filipvandurme gaschromatographicfingerprintanalysisforthecomparisonofseizedcannabissamples AT nelesamyn gaschromatographicfingerprintanalysisforthecomparisonofseizedcannabissamples AT debbymangelings gaschromatographicfingerprintanalysisforthecomparisonofseizedcannabissamples AT yvanvanderheyden gaschromatographicfingerprintanalysisforthecomparisonofseizedcannabissamples
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Gas Chromatographic Fingerprint Analysis for the Comparison of Seized Cannabis Samples

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