Evaluation of data preprocessings for the comparison of GC–MS chemical profiles of seized cannabis samples

Slosse, Amorn; Durme, Filip Van; Samyn, Nele; Mangelings, Debby; Heyden, Yvan Vander

doi:10.1016/j.forsciint.2020.110228

Cited by 23 publications

(53 citation statements)

References 48 publications

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“…The composition of the street samples was previously analyzed in the forensic laboratory at NICC with standard methods in order to subsequently validate the electrochemical approach. The qualitative analysis of the street samples was performed using gas chromatography–mass spectrometry (GC–MS) 34 . The applied chromatographic methods are ISO17025 accredited and are continuously evaluated through participation to international quality control programs (UNODC and European Network of Forensic Science Institutes—ENFSI).…”

Section: Methodsmentioning

confidence: 99%

“…48,49 Moreover, electrochemical devices are becoming a solution as they offer excellent sensitivity, miniaturization, and affordable analysis. 45 The applicability of the electrochemical profile method to detect SC in seized samples was compared with a reference standard method (i.e., GC-MS 34 ) using seized samples provided by forensic institutes (i.e., NICC and NFI). During the analysis of the seized samples, a portable potentiostat connected to a laptop or tablet was used.…”

Section: Detection and Validation Of The Electrochemical Methods In Seized Samplesmentioning

confidence: 99%

“…The qualitative analysis of the street samples was performed using gas chromatography-mass spectrometry (GC-MS). 34 The applied chromatographic methods are ISO17025 accredited and are continuously evaluated through participation to international quality control programs (UNODC and European Network of Forensic Science Institutes-ENFSI). Figure S2a,b shows the SW voltammograms and corresponding calibration curves for five SCs, respectively.…”

Section: Instrumentation and Apparatusmentioning

confidence: 99%

See 2 more Smart Citations

Electrochemical profiling and liquid chromatography–mass spectrometry characterization of synthetic cathinones: From methodology to detection in forensic samples

Schram

Parrilla

Sleegers

et al. 2021

Drug Testing and Analysis

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The emergence of new psychoactive drugs in the market demands rapid and accurate tools for the on‐site classification of illegal and legal compounds with similar structures. Herein, a novel method for the classification of synthetic cathinones (SCs) is presented based on their electrochemical profile. First, the electrochemical profile of five common SC (i.e., mephedrone, ethcathinone, methylone, butylone, and 4‐chloro‐alpha‐pyrrolidinovalerophenone) is collected to build calibration curves using square wave voltammetry on graphite screen‐printed electrodes (SPEs). Second, the elucidation of the oxidation pathways, obtained by liquid chromatography–high‐resolution mass spectrometry, allows the pairing of the oxidation products to the SC electrochemical profile, providing a selective and robust classification. Additionally, the effect of common adulterants and illicit drugs on the electrochemical profile of the SC is explored. Interestingly, a cathodic pretreatment of the SPE allows the selective detection of each SC in presence of electroactive adulterants. Finally, the electrochemical approach is validated with gas chromatography–mass spectrometry by analyzing 26 confiscated samples from seizures and illegal webshops. Overall, the electrochemical method exhibits a successful classification of SC including structural derivatives, a crucial attribute in an ever‐diversifying drug market.

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Section: Methodsmentioning

confidence: 99%

Section: Detection and Validation Of The Electrochemical Methods In Seized Samplesmentioning

confidence: 99%

Section: Instrumentation and Apparatusmentioning

confidence: 99%

See 1 more Smart Citation

Electrochemical profiling and liquid chromatography–mass spectrometry characterization of synthetic cathinones: From methodology to detection in forensic samples

Schram

Parrilla

Sleegers

et al. 2021

Drug Testing and Analysis

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show abstract

“…PLS-DA is a multivariate classification method, which is based on a PLS regression algorithm and aims to find linear combinations of the original variables (latent variables (LV)) that better separate each class [ 59 , 60 ]. In our study, before PLS-DA calculation, the fourth root for data preprocessing was applied, which had previously shown efficiency discriminating seized cannabis samples obtained by GC-MS using the fourth root [ 61 ]. After auto-scaling, the number of latent variables was optimized with three-fold cross validation, with five latent variables (LV) maximizing the Non-Error Rate (NER) [ 62 ].…”

Section: Resultsmentioning

confidence: 99%

“…The threshold value for the separation of the classes was estimated using Bayes’ Theorem. Three-fold cross-validation was performed using venetian blinds splitting protocol and used to select the optimal number of latent variables based on Non-Error Rate [ 61 ]. Additional validation was performed using bootstrap and random resampling.…”

Section: Methodsmentioning

confidence: 99%

Verification of Chromatographic Profile of Primary Essential Oil of Pinus sylvestris L. Combined with Chemometric Analysis

Allenspach

Valder²,

Flamm³

et al. 2020

Molecules

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Chromatographic profiles of primary essential oils (EO) deliver valuable authentic information about composition and compound pattern. Primary EOs obtained from Pinus sylvestris L. (PS) from different global origins were analyzed using gas chromatography coupled to a flame ionization detector (GC-FID) and identified by GC hyphenated to mass spectrometer (GC-MS). A primary EO of PS was characterized by a distinct sesquiterpene pattern followed by a diterpene profile containing diterpenoids of the labdane, pimarane or abietane type. Based on their sesquiterpene compound patterns, primary EOs of PS were separated into their geographical origin using component analysis. Furthermore, differentiation of closely related pine EOs by partial least square discriminant analysis proved the existence of a primary EO of PS. The developed and validated PLS-DA model is suitable as a screening tool to assess the correct chemotaxonomic identification of a primary pine EOs as it classified all pine EOs correctly.

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

Slosse,

Van Durme,

Samyn

et al. 2023

Drug Testing and Analysis

Self Cite

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Yearly, 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‐location 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 relative to internal standard normalization that was used as reference. An additional intra‐plantation variability study with 130 samples verified whether the initial model contained sufficient within‐location information, but this was not the case. Hence, a combined data matrix was constructed with all seized samples. Log transformation provided the best FP results for both limits, that is, an improvement from 58% and 64% to 21% and 26%, respectively, was seen. The representativeness of these ‘linked’ thresholds was demonstrated using both cross‐validation and an external set, for which similar FP results as for the calibration set were obtained. By applying data pretreatment, a significant improvement was observed to distinguish seized samples. However, the FP rate is still not at an acceptable level to defend in court.

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Evaluation of data preprocessings for the comparison of GC–MS chemical profiles of seized cannabis samples

Cited by 23 publications

References 48 publications

Electrochemical profiling and liquid chromatography–mass spectrometry characterization of synthetic cathinones: From methodology to detection in forensic samples

Electrochemical profiling and liquid chromatography–mass spectrometry characterization of synthetic cathinones: From methodology to detection in forensic samples

Verification of Chromatographic Profile of Primary Essential Oil of Pinus sylvestris L. Combined with Chemometric Analysis

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

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