NANOlab Center of Excellence literature database -- Query Results

“Comparison of spectroscopic techniques combined with chemometrics for cocaine powder analysis”. Eliaerts J, Meert N, Dardenne P, Baeten V, Pierna J-AF, Van Durme F, De Wael K, Samyn N, Journal Of Analytical Toxicology 44, 851 (2020). http://doi.org/10.1093/JAT/BKAA101 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. Keywords: A1 Journal article; Pharmacology. Therapy; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation) Impact Factor: 2.5 DOI: 10.1093/JAT/BKAA101 Additional Links: UA library record; WoS full record; WoS citing articles show.php?record=7697
“Evaluation of a calibration transfer between a bench top and portable Mid-InfraRed spectrometer for cocaine classification and quantification”. Eliaerts J, Meert N, Dardenne P, Van Durme F, Baeten V, Samyn N, De Wael K, Talanta 209, 120481 (2020). http://doi.org/10.1016/J.TALANTA.2019.120481 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. Keywords: A1 Journal article; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation) Impact Factor: 6.1 Times cited: 2 DOI: 10.1016/J.TALANTA.2019.120481 Additional Links: UA library record; WoS full record; WoS citing articles show.php?record=6511

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.

Keywords: A1 Journal article; Pharmacology. Therapy; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)

Impact Factor: 2.5

DOI: 10.1093/JAT/BKAA101

Additional Links: UA library record; WoS full record; WoS citing articles

show.php?record=7697

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.