Pocket-size near-infrared spectrometer for narcotic materials identification

Pederson, Christopher G.; Friedrich, Donald M.; Hsiung, Chang; Gunten, Marc von; O’Brien, Nada A.; Ramaker, Henk‐Jan; Sprang, Eric van; Dreischor, M. W.

doi:10.1117/12.2050019

Cited by 12 publications

(11 citation statements)

References 2 publications

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“…Earlier studies report on the limited effect of plastic packaging on the NIR signal. 41,42 Future studies on the effect of packaging materials might therefore be beneficial as this will even further reduce the risk of the investigating officer being exposed to harmful substances. Also, in this study only white-or off-white-colored powders were included in the model as this is the most common appearance of cocaine sam- can safeguard the quality of the on-scene analysis "from a distance" and in "real time" as the model returns an analysis outcome to the smartphone almost instantly.…”

Section: External Validation and Unknown Samplesmentioning

confidence: 99%

Rapid and robust on‐scene detection of cocaine in street samples using a handheld near‐infrared spectrometer and machine learning algorithms

Kranenburg

Verduin

Weesepoel

et al. 2020

Drug Testing and Analysis

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On-scene drug detection is an increasingly significant challenge due to the fastchanging drug market as well as the risk of exposure to potent drug substances. Conventional colorimetric cocaine tests involve handling of the unknown material and are prone to false-positive reactions on common pharmaceuticals used as cutting agents. This study demonstrates the novel application of 740-1070 nm small-wavelength-range near-infrared (NIR) spectroscopy to confidently detect cocaine in case samples. Multistage machine learning algorithms are used to exploit the limited spectral features and predict not only the presence of cocaine but also the concentration and sample composition. A model based on more than 10,000 spectra from case samples yielded 97% true-positive and 98% true-negative results. The practical applicability is shown in more than 100 case samples not included in the model design. One of the most exciting aspects of this on-scene approach is that the model can almost instantly adapt to changes in the illicit-drug market by updating metadata with results from subsequent confirmatory laboratory analyses. These results demonstrate that advanced machine learning strategies applied on limited-range NIR spectra from economic handheld sensors can be a valuable procedure for rapid on-site detection of illicit substances by investigating officers. In addition to forensics, this interesting approach could be beneficial for screening and classification applications in the pharmaceutical, food-safety, and environmental domains.

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Section: External Validation and Unknown Samplesmentioning

confidence: 99%

Rapid and robust on‐scene detection of cocaine in street samples using a handheld near‐infrared spectrometer and machine learning algorithms

Kranenburg

Verduin

Weesepoel

et al. 2020

Drug Testing and Analysis

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“…The main advantages of NIRS are its comparatively low cost, fast measurements and easy handling [25,26]. Furthermore, it is possible to miniaturize NIR technology and thus reduce costs and weight, as well as improve consumer-friendliness [27,28]. With the miniaturization process beginning already a decade ago, its main challenge was to preserve spectral performance in terms of wavenumber range and resolution [28].…”

Section: Introductionmentioning

confidence: 99%

Investigations into the Performance of a Novel Pocket-Sized Near-Infrared Spectrometer for Cheese Analysis

et al. 2019

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The performance of a newly developed pocket-sized near-infrared (NIR) spectrometer was investigated by analysing 46 cheese samples for their water and fat content, and comparing results with a benchtop NIR device. Additionally, the automated data analysis of the pocket-sized spectrometer and its cloud-based data analysis software, designed for laypeople, was put to the test by comparing performances to a highly sophisticated multivariate data analysis software. All developed partial least squares regression (PLS-R) models yield a coefficient of determination (R2) of over 0.9, indicating high correlation between spectra and reference data for both spectrometers and all data analysis routes taken. In general, the analysis of grated cheese yields better results than whole pieces of cheese. Additionally, the ratios of performance to deviation (RPDs) and standard errors of prediction (SEPs) suggest that the performance of the pocket-sized spectrometer is comparable to the benchtop device. Small improvements are observable, when using sophisticated data analysis software, instead of automated tools.

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“…These instruments are generally light weight and can be easily moved throughout a laboratory and brought to the crime scene. Most of these portable techniques are based on Raman and IR spectroscopy [1–5]. Portable Raman spectroscopy is valuable for on‐site detection of drugs because it does not need to be in contact with the substance and can even detect drugs through plastic bags, which is very common packaging for illicit substances [4].…”

Section: Introductionmentioning

confidence: 99%

“…The Randox mephedrone/methcathinone kit was the only immunoassay that could detect a wide range of synthetic cathinones [15]. Numerous instrumental methods can be used to detect and identify synthetic cathinones, including GC‐EI‐MS [16‐21], GC‐EI‐MS/MS [16,22,23], gas chromatography cold electron impact with quadrupole time‐of‐flight mass spectrometry (GC‐cold EI‐QTOF‐MS) [17], gas chromatography with positive chemical ionization tandem mass spectrometry (GC‐PCI‐MS/MS) [22], gas chromatography infrared spectroscopy (GC‐IR) [16], gas chromatography with vacuum ultraviolet detection (GC‐VUV) [24], high performance liquid chromatography with photodiode array ultraviolet detection (HPLC‐UV PDA) [23], ultra high performance liquid chromatography with electrospray time of flight mass spectrometry (UHPLC‐ESI‐TOF‐MS) [19,25], UHPLC‐UV PDA‐ESI‐MS [26,27], UHPLC‐ESI‐MS/MS [28], multidimensional UHPLC‐UV PDA‐ESI‐MS [29], capillary electrophoresis (CE‐UV PDA) [27], CE‐UV PDA‐MS [30], ultrahigh performance supercritical fluid chromatography (UHPSFC)‐UV PDA‐ESI‐MS [11,19,31], ion mobility spectrometry (IMS) [32], IMS‐ESI‐MS [32], direct analysis in real time (DART)‐TOF‐MS [33], DART‐IMS‐TOF‐MS [34], Raman spectroscopy [35], portable Raman spectroscopy [1–5], IR spectroscopy [35], portable IR spectroscopy [1‐5], and nuclear magnetic resonance spectroscopy (NMR) [36,37]. These instruments either lack portability, and/or are lacking in specificity, and/or are problematic for mixtures.…”

Section: Introductionmentioning

confidence: 99%

The separation and identification of synthetic cathinones by portable low microflow liquid chromatography with dual capillary columns in series and dual wavelength ultraviolet detection

May

Pavone

Lurie

2020

J of Separation Science

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This study ascertained the viability of a portable liquid chromatograph, operating at low microliter per minute flow, for the analysis of seized drugs at remote sites as well as in laboratory settings. Synthetic cathinones were screened using dual capillary columns in series, C8 and biphenyl, with on-column ultraviolet detection at 255 and 275 nm. The relative retention times of the two columns in series and their peak area absorbance ratio were used to determine if the 16 synthetic cathinones investigated could be uniquely identified in these conditions. Based on these parameters all of the analytes could be distinguished. Representative mixtures of synthetic cathinones were used to determine the repeatability, linearity, and limits of detection of the method. This cost effective and green instrumentation has the potential to satisfy minimum international guidelines for the analysis of seized drugs. K E Y W O R D S dual capillary columns in series, dual on-column UV detection, portable liquid chromatography, synthetic cathinones 3756

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Pocket-size near-infrared spectrometer for narcotic materials identification

Cited by 12 publications

References 2 publications

Rapid and robust on‐scene detection of cocaine in street samples using a handheld near‐infrared spectrometer and machine learning algorithms

Rapid and robust on‐scene detection of cocaine in street samples using a handheld near‐infrared spectrometer and machine learning algorithms

Investigations into the Performance of a Novel Pocket-Sized Near-Infrared Spectrometer for Cheese Analysis

The separation and identification of synthetic cathinones by portable low microflow liquid chromatography with dual capillary columns in series and dual wavelength ultraviolet detection

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