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Author |
Eliaerts, J.; Meert, N.; Dardenne, P.; Baeten, V.; Pierna, J.-A.F.; Van Durme, F.; De Wael, K.; Samyn, N. |
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Title |
Comparison of spectroscopic techniques combined with chemometrics for cocaine powder analysis |
Type |
A1 Journal article |
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Year  |
2020 |
Publication |
Journal Of Analytical Toxicology |
Abbreviated Journal |
J Anal Toxicol |
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Volume |
44 |
Issue |
8 |
Pages |
851-860 |
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Keywords |
A1 Journal article; Pharmacology. Therapy; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation) |
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Abstract |
Spectroscopic techniques combined with chemometrics are a promising tool for analysis of seized drug powders. In this study, the performance of three spectroscopic techniques [Mid-InfraRed (MIR), Raman and Near-InfraRed (NIR)] was compared. In total, 364 seized powders were analyzed and consisted of 276 cocaine powders (with concentrations ranging from 4 to 99 w%) and 88 powders without cocaine. A classification model (using Support Vector Machines [SVM] discriminant analysis) and a quantification model (using SVM regression) were constructed with each spectral dataset in order to discriminate cocaine powders from other powders and quantify cocaine in powders classified as cocaine positive. The performances of the models were compared with gas chromatography coupled with mass spectrometry (GC-MS) and gas chromatography with flame-ionization detection (GC-FID). Different evaluation criteria were used: number of false negatives (FNs), number of false positives (FPs), accuracy, root mean square error of cross-validation (RMSECV) and determination coefficients (R-2). Ten colored powders were excluded from the classification data set due to fluorescence background observed in Raman spectra. For the classification, the best accuracy (99.7%) was obtained with MIR spectra. With Raman and NIR spectra, the accuracy was 99.5% and 98.9%, respectively. For the quantification, the best results were obtained with NIR spectra. The cocaine content was determined with a RMSECV of 3.79% and a R-2 of 0.97. The performance of MIR and Raman to predict cocaine concentrations was lower than NIR, with RMSECV of 6.76% and 6.79%, respectively and both with a R-2 of 0.90. The three spectroscopic techniques can be applied for both classification and quantification of cocaine, but some differences in performance were detected. The best classification was obtained with MIR spectra. For quantification, however, the RMSECV of MIR and Raman was twice as high in comparison with NIR. Spectroscopic techniques combined with chemometrics can reduce the workload for confirmation analysis (e.g., chromatography based) and therefore save time and resources. |
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Wos |
000606735000011 |
Publication Date |
2020-08-04 |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0146-4760; 1945-2403 |
ISBN |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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Impact Factor |
2.5 |
Times cited |
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Open Access |
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Notes |
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Approved |
Most recent IF: 2.5; 2020 IF: 2.409 |
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Call Number |
UA @ admin @ c:irua:175117 |
Serial |
7697 |
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Author |
Eliaerts, J.; Meert, N.; Dardenne, P.; Van Durme, F.; Baeten, V.; Samyn, N.; De Wael, K. |
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Title |
Evaluation of a calibration transfer between a bench top and portable Mid-InfraRed spectrometer for cocaine classification and quantification |
Type |
A1 Journal article |
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Year |
2020 |
Publication |
Talanta |
Abbreviated Journal |
Talanta |
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Volume |
209 |
Issue |
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Pages |
120481 |
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Keywords |
A1 Journal article; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation) |
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Abstract |
A portable Fourier Transform Mid-InfraRed (FT-MIR) spectrometer using Attenuated Total Reflectance (ATR) sampling is used for daily routine screening of seized powders. Earlier, ATR-FT-MIR combined with Support Vector Machines (SVM) algorithms resulted in a significant improvement of the screening method to a reliable and straightforward classification and quantification tool for both cocaine and levamisole. However, can this tool be transferred to new (hand-held) devices, without loss of the extensive data set? The objective of this study was to perform a calibration transfer between a newly purchased bench top (BT) spectrometer and a portable (P) spectrometer with existing calibration models. Both instruments are from the same brand and have identical characteristics and acquisition parameters (FT instrument, resolution of 4 cm(-1) and wavenumber range 4000 to 500 cm(-1)). The original SVM classification model (n = 515) and SVM quantification model (n = 378) were considered for the transfer trial. Three calibration transfer strategies were assessed: 1) adjustment of slope and bias; 2) correction of spectra from the new instrument BT to P using Piecewise Direct Standardization (PDS) and 3) building a new mixed instrument model with spectra of both instruments. For each approach, additional cocaine powders were measured (n = 682) and the results were compared with GC-MS and GC-FID. The development of a mixed instrument model was the most successful in terms of performance. The future strategy of a mixed model allows applying the models, developed in the laboratory, to portable instruments that are used on-site, and vice versa. The approach offers opportunities to exchange data within a network of forensic laboratories using other FT-MIR spectrometers. |
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Wos |
000509632900016 |
Publication Date |
2019-10-21 |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0039-9140; 1873-3573 |
ISBN |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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Impact Factor |
6.1 |
Times cited |
2 |
Open Access |
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Notes |
; ; |
Approved |
Most recent IF: 6.1; 2020 IF: 4.162 |
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Call Number |
UA @ admin @ c:irua:166475 |
Serial |
6511 |
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Author |
Eliaerts, J.; Meert, N.; Van Durme, F.; Samyn, N.; De Wael, K.; Dardenne, P. |
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Title |
Practical tool for sampling and fast analysis of large cocaine seizures |
Type |
A1 Journal article |
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Year |
2018 |
Publication |
Drug testing and analysis |
Abbreviated Journal |
Drug Test Anal |
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Volume |
10 |
Issue |
6 |
Pages |
1039-1042 |
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Keywords |
A1 Journal article; Pharmacology. Therapy; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation) |
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Abstract |
Large quantities of illicit drugs are frequently seized by law enforcement. In such cases, a representative number of samples needs to be quickly examined prior to destruction. No procedure has yet been set up which rapidly provides information regarding the homogeneity of the samples, the presence of controlled substances and the degree of purity. This study establishes a protocol for fast analysis of cocaine and its most common cutting agent, levamisole, in large seizures. The protocol is based on a hypergeometric sampling approach combined with FTIR spectrometry and Support Vector Machines (SVM) algorithms as analysis methods. To demonstrate the practical use of this approach, five large cocaine seizures (consisting between 45 and 85 units) were analysed simultaneously with GC-MS, GC-FID and a portable FTIR spectrometer using Attenuated Total Reflectance (ATR) sampling combined with SVM models. According to the hypergeometric sampling plan of the Drugs Working Group ENFSI guidelines, the required number of subsamples ranged between 19 and 23. Considering the identification analyses, the SVM models detected cocaine and levamisole in all subsamples of cases 1 to 5 (100% correct classification), which was confirmed by GC-MS analysis. Considering the quantification analyses, the SVM models were able to estimate the cocaine and levamisole content in each subsample, compared to GC-FID data. The developed strategy is easy, cost effective and provides immediate information about both the presence and concentration of cocaine and levamisole. By using this new strategy, the number of confirmation analyses with laborious and expensive chromatographic techniques could be significantly reduced. |
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Wos |
000435270300016 |
Publication Date |
2018-02-03 |
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Series Editor |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1942-7603; 1942-7611 |
ISBN |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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Impact Factor |
3.469 |
Times cited |
1 |
Open Access |
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Notes |
; Belgian Science Policy Office (BELSPO), Grant/Award Number: WE/49/N14-O14 ; |
Approved |
Most recent IF: 3.469 |
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Call Number |
UA @ admin @ c:irua:148760 |
Serial |
5781 |
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Author |
Eliaerts, J.; Dardenne, P.; Meert, N.; Van Durme, F.; Samyn, N.; Janssens, K.; De Wael, K. |
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Title |
Rapid classification and quantification of cocaine in seized powders with ATR-FTIR and chemometrics |
Type |
A1 Journal article |
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Year |
2017 |
Publication |
Drug testing and analysis |
Abbreviated Journal |
Drug Test Anal |
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Volume |
9 |
Issue |
10 |
Pages |
1480-1489 |
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Keywords |
A1 Journal article; Pharmacology. Therapy; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation) |
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Abstract |
Traditionally, fast screening for the presence of cocaine in unknown powders is performed by means of colour tests. The major drawbacks of these tests are subjective colour evaluation depending on the operator (50 shades of blue) and a lack of selectivity. An alternative fast screening technique is Fourier Transform InfraRed (FTIR) spectrometry. This technique provides spectra that are difficult to interpret without specialized expertise and showing a lack of sensitivity for the detection of cocaine in mixtures. To overcome these limitations, a portable FTIR spectrometer using Attenuated Total Reflectance (ATR) sampling was combined with a multivariate technique, called Support Vector Machines (SVM). Representative street drug powders (n = 482), seized during the period January 2013 to July 2015, and reference powders (n = 33) were used to build and validate a classification model (n = 515) and a quantification model (n = 378). Both models were compared with the conventional chromatographic techniques. The SVM classification model showed a high sensitivity, specificity and efficiency (99%). The SVM quantification model determined cocaine content with a root mean squared error of prediction (RMSEP) of 6% calculated over a wide working range from 4 to 99 w%. In conclusion, the developed models resulted in a clear output (cocaine detected or cocaine not detected) and a reliable estimation of the cocaine content in a wide variety of mixtures. The ATR-FTIR technique combined with SVM is a straightforward, user-friendly and fast approach for routine classification and quantification of cocaine in seized powders. |
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Corporate Author |
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Thesis |
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Publisher |
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Editor |
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Wos |
000413685200001 |
Publication Date |
2016-12-17 |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1942-7603; 1942-7611 |
ISBN |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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Impact Factor |
3.469 |
Times cited |
9 |
Open Access |
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Notes |
; ; |
Approved |
Most recent IF: 3.469 |
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Call Number |
UA @ admin @ c:irua:139483 |
Serial |
5799 |
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| Permanent link to this record |
