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Sensor for Rapid In-Field Classification of Cannabis Samples Based on Near-Infrared Spectroscopy.
Zimmerleiter, Robert; Greibl, Wolfgang; Meininger, Gerold; Duswald, Kristina; Hannesschläger, Günther; Gattinger, Paul; Rohm, Matthias; Fuczik, Christian; Holzer, Robert; Brandstetter, Markus.
Afiliación
  • Zimmerleiter R; Research Center for Non-Destructive Testing GmbH, Altenberger Straße 69, 4040 Linz, Austria.
  • Greibl W; Criminal Intelligence Service, Forensic Science, Josef Holaubek Platz, 1090 Wien, Austria.
  • Meininger G; Spath Micro Electronic Design GmbH, Reininghausstraße 13, 8020 Graz, Austria.
  • Duswald K; Research Center for Non-Destructive Testing GmbH, Altenberger Straße 69, 4040 Linz, Austria.
  • Hannesschläger G; Research Center for Non-Destructive Testing GmbH, Altenberger Straße 69, 4040 Linz, Austria.
  • Gattinger P; Research Center for Non-Destructive Testing GmbH, Altenberger Straße 69, 4040 Linz, Austria.
  • Rohm M; IFHA/Christian Fuczik-Chemisches Labor GmbH, Gerhardusgasse 25/3.OG, 1200 Wien, Austria.
  • Fuczik C; IFHA/Christian Fuczik-Chemisches Labor GmbH, Gerhardusgasse 25/3.OG, 1200 Wien, Austria.
  • Holzer R; Research Center for Non-Destructive Testing GmbH, Altenberger Straße 69, 4040 Linz, Austria.
  • Brandstetter M; Research Center for Non-Destructive Testing GmbH, Altenberger Straße 69, 4040 Linz, Austria.
Sensors (Basel) ; 24(10)2024 May 17.
Article en En | MEDLINE | ID: mdl-38794042
ABSTRACT
A rugged handheld sensor for rapid in-field classification of cannabis samples based on their THC content using ultra-compact near-infrared spectrometer technology is presented. The device is designed for use by the Austrian authorities to discriminate between legal and illegal cannabis samples directly at the place of intervention. Hence, the sensor allows direct measurement through commonly encountered transparent plastic packaging made from polypropylene or polyethylene without any sample preparation. The measurement time is below 20 s. Measured spectral data are evaluated using partial least squares discriminant analysis directly on the device's hardware, eliminating the need for internet connectivity for cloud computing. The classification result is visually indicated directly on the sensor via a colored LED. Validation of the sensor is performed on an independent data set acquired by non-expert users after a short introduction. Despite the challenging setting, the achieved classification accuracy is higher than 80%. Therefore, the handheld sensor has the potential to reduce the number of unnecessarily confiscated legal cannabis samples, which would lead to significant monetary savings for the authorities.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Cannabis / Espectroscopía Infrarroja Corta Límite: Humans Idioma: En Revista: Sensors (Basel) Año: 2024 Tipo del documento: Article País de afiliación: Austria

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Cannabis / Espectroscopía Infrarroja Corta Límite: Humans Idioma: En Revista: Sensors (Basel) Año: 2024 Tipo del documento: Article País de afiliación: Austria