Rapid classification and quantification of cocaine in seized powders with ATR‐FTIR and chemometrics. Issue 10 (31st March 2017)
- Record Type:
- Journal Article
- Title:
- Rapid classification and quantification of cocaine in seized powders with ATR‐FTIR and chemometrics. Issue 10 (31st March 2017)
- Main Title:
- Rapid classification and quantification of cocaine in seized powders with ATR‐FTIR and chemometrics
- Authors:
- Eliaerts, Joy
Dardenne, Pierre
Meert, Natalie
Van Durme, Filip
Samyn, Nele
Janssens, Koen
De Wael, Karolien - Abstract:
- 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 shows 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‐FTIRAbstract : 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 shows 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. Copyright © 2016 John Wiley & Sons, Ltd. Abstract : ATR‐FTIR spectrometry combined with SVM resulted in a significant upgrade of the screening test to a reliable and straightforward classification and quantification tool for cocaine in seized drug powders. The entire process of classification (cocaine detected or cocaine not detected) and a reliable estimation of the cocaine content can be completed within less than four minutes per sample, emphasizing its potential for high throughput and on‐site applications. … (more)
- Is Part Of:
- Drug testing and analysis. Volume 9:Issue 10(2017)
- Journal:
- Drug testing and analysis
- Issue:
- Volume 9:Issue 10(2017)
- Issue Display:
- Volume 9, Issue 10 (2017)
- Year:
- 2017
- Volume:
- 9
- Issue:
- 10
- Issue Sort Value:
- 2017-0009-0010-0000
- Page Start:
- 1480
- Page End:
- 1489
- Publication Date:
- 2017-03-31
- Subjects:
- cocaine -- ATR‐FTIR -- chemometrics -- classification -- quantification -- SVM -- PLS
Drugs -- Analysis -- Periodicals
Drug testing -- Periodicals
Chemistry, Forensic -- Periodicals
615.1901 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1942-7611 ↗
http://rzblx1.uni-regensburg.de/ezeit/warpto.phtml?colors=7&jour_id=110501 ↗
http://www3.interscience.wiley.com/journal/121408477/home ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/dta.2149 ↗
- Languages:
- English
- ISSNs:
- 1942-7603
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3629.424000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 5291.xml