The importance of wavelength selection in on-scene identification of drugs of abuse with portable near-infrared spectroscopy

Both the increasing volume and diversity of drugs-of-abuse encountered by investigation services necessitates the need for fast on-scene detectors to detect and identify a broad range of substances. Near-Infrared (NIR) spectroscopy is suitable for presumptive drugs testing by miniaturized sensors implemented in portable devices. Currently, a myriad of different portable NIR spectrometers is available that utilize different wavelength ranges. This study presents a comparison of NIR spectra of frequently occuring drugs analyzed by five different devices. A 350 – 2500 nm range laboratory grade VIS-NIR spectrometer was used to gain insight in spectral ranges diagnostic for substances relevant in forensic science. Obtained spectra were compared to the output of portable spectrometers operating in the 740 – 1070 nm, 950 – 1650 nm, 1550 – 1950 nm and 1300 – 2600 nm range. The results yielded novel insights in the usability of individual spectrometers by visual inspection of NIR spectra as well as comparative statistics with reference substances. For MDMA detection, an instrument capable of detecting a highly abundant and specific peak at 2020 nm is beneficial whereas colored samples are more difficult to detect by lower wavelength range sensors. Relatively pure, lightly colored samples may be correctly characterized by all sensors. These findings may aid NIR spectrometer selection in forensic practice as well as future studies on instrument selectivity or cross-platform calibration transfer

ZIP file: Dataset of Near-Infrared Spectral Data of Illicit-Drugs and Forensic Casework Samples Analyzed by Five Portable Spectrometers Operating in Different Wavelength Ranges

ZIP file with Dataset of Near-Infrared Spectral Data of Illicit-Drugs and Forensic Casework Samples Analyzed by Five Portable Spectrometers Operating in Different Wavelength Ranges. Additional details can be found in the related Data in Brief manuscript (https://doi.org/10.1016/j.dib.2022.108660). This data is accompanying the research described in the article: R.F. Kranenburg, Y. Weesepoel, M. Alewijn, S. Sap, P.W.F. Arisz, A. van Esch, P.H.J. Keizers, A.C. van Asten, The Importance of Wavelength Selection in On-Scene Identification of Drugs of Abuse with Portable Near-Infrared Spectroscopy, Forensic Chem. (2022) 100437. https://doi.org/10.1016/j.forc.2022.100437  </p

ZIP file: Dataset of Near-Infrared Spectral Data of Illicit-Drugs and Forensic Casework Samples Analyzed by Five Portable Spectrometers Operating in Different Wavelength Ranges

ZIP file with Dataset of Near-Infrared Spectral Data of Illicit-Drugs and Forensic Casework Samples Analyzed by Five Portable Spectrometers Operating in Different Wavelength Ranges. Additional details can be found in the related Data in Brief manuscript (https://doi.org/10.1016/j.dib.2022.108660). This data is accompanying the research described in the article: R.F. Kranenburg, Y. Weesepoel, M. Alewijn, S. Sap, P.W.F. Arisz, A. van Esch, P.H.J. Keizers, A.C. van Asten, The Importance of Wavelength Selection in On-Scene Identification of Drugs of Abuse with Portable Near-Infrared Spectroscopy, Forensic Chem. (2022) 100437. https://doi.org/10.1016/j.forc.2022.100437  </p

Dataset of Near-Infrared Spectral Data of Illicit-Drugs and Forensic Casework Samples Analyzed by Five Portable Spectrometers Operating in Different Wavelength Ranges

Dataset of Near-Infrared Spectral Data of Illicit-Drugs and Forensic Casework Samples Analyzed by Five Portable Spectrometers Operating in Different Wavelength Ranges. Additional details can be found in the related Data in Brief manuscript (submitted). This data is accompanying the research described in the article: R.F. Kranenburg, Y. Weesepoel, M. Alewijn, S. Sap, P.W.F. Arisz, A. van Esch, P.H.J. Keizers, A.C. van Asten, The Importance of Wavelength Selection in On-Scene Identification of Drugs of Abuse with Portable Near-Infrared Spectroscopy, Forensic Chem. (2022) 100437. https://doi.org/10.1016/j.forc.2022.100437  </p

Identifying antimicrobials and their metabolites in wastewater and surface water with effect-directed analysis

This study aimed to identify antimicrobial contaminants in the aquatic environment with effect-directed analysis. Wastewater influent, effluent, and surface water (up- and downstream of the discharge location) were sampled at two study sites. The samples were enriched, subjected to high-resolution fractionation, and the resulting 80 fractions were tested in an antibiotics bioassay. The resulting bioactive fractions guided the suspect and nontargeted identification strategy in the high-resolution mass spectrometry data that was recorded in parallel. Chemical features were annotated with reference databases, assessed on annotation quality, and assigned identification confidence levels. To identify antibiotic metabolites, Phase I metabolites were predicted in silico for over 500 antibiotics and included as a suspect list. Predicted retention times and fragmentation patterns reduced the number of annotations to consider for confirmation testing. Overall, the bioactivity of three fractions could be explained by the identified antibiotics (clarithromycin and azithromycin) and an antibiotic metabolite (14-OH(R) clarithromycin), explaining 78% of the bioactivity measured at one study site. The applied identification strategy successfully identified antibiotic metabolites in the aquatic environment, emphasizing the need to include the toxic effects of bioactive metabolites in environmental risk assessments

Dataset of Near-Infrared Spectral Data of Illicit-Drugs and Forensic Casework Samples Analyzed by Five Portable Spectrometers Operating in Different Wavelength Ranges

Dataset of Near-Infrared Spectral Data of Illicit-Drugs and Forensic Casework Samples Analyzed by Five Portable Spectrometers Operating in Different Wavelength Ranges. Additional details can be found in the related Data in Brief manuscript (submitted). This data is accompanying the research described in the article: R.F. Kranenburg, Y. Weesepoel, M. Alewijn, S. Sap, P.W.F. Arisz, A. van Esch, P.H.J. Keizers, A.C. van Asten, The Importance of Wavelength Selection in On-Scene Identification of Drugs of Abuse with Portable Near-Infrared Spectroscopy, Forensic Chem. (2022) 100437. https://doi.org/10.1016/j.forc.2022.100437  </p

The influence of water of crystallization in NIR-based MDMA·HCl detection

The large numbers of 3,4-methylenedioxy-N-methylamphetamine (MDMA) formulations encountered by the police and border security necessitates the need for safe, rapid and reliable tests to be performed on-site. Near-infrared (NIR) spectroscopy is a promising technique for on-scene illicit-drug detection because of its rapid analysis, non-invasive nature, broad scope to detect various substances, and small-sized sensors suitable for portable operation. The NIR spectrum of MDMA shows an intriguing, intense peak at ∼2000 nm that was found characteristic for MDMA within a large set of drugs and drug-related substances. Herein, we show that this peak can be attributed to water molecules of crystallization in the MDMA lattice. Drying experiments showed that both an anhydrous and hydrated form of MDMA·HCl exists with significantly different NIR spectra. At ambient conditions, the anhydrous form converted back to the hydrated form within 2 months. Our data analysis model was able to identify MDMA·HCl in mixtures of both forms. Assessment of seized casework materials showed that the majority of MDMA·HCl in The Netherlands is of the hydrated type. This is explained by the use of water-containing concentrated hydrochloric acid in the final conversion step of MDMA-base to the hydrochloride salt in clandestine laboratories. These findings provide insight in the challenges associated with NIR-based identification of drugs that may appear in various crystalline forms. Awareness on the existence of these forms and the consequences of library and data-model design to cope with this phenomenon will increase the robustness of on-site NIR-based drug detection