Random Forest Processing of Direct Analysis in Real-Time Mass Spectrometric Data Enables Species Identification of Psychoactive Plants from Their Headspace Chemical Signatures-Reference-Cited by-同舟云学术

Random Forest Processing of Direct Analysis in Real-Time Mass Spectrometric Data Enables Species Identification of Psychoactive Plants from Their Headspace Chemical Signatures

Published:2019-09-11 Issue:13 Volume:4 Page:15636-15644
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

Appley Meghan Grace¹,Beyramysoltan Samira¹,Musah Rabi Ann¹^ORCID

Affiliation:

1. Department of Chemistry, University at Albany—State University of New York, 1400 Washington Avenue, Albany, New York 12222, United States

Funder

National Institute of Justice

National Science Foundation

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

http://pubs.acs.org/doi/pdf/10.1021/acsomega.9b02145

Reference24 articles.

1. Hammond, B.; Crean, C.; Levissianos, S.; Mermerci, D.; Tun Nay, S.; Otani, T.; Park, M.; Pazos, D.; Piñeros, K.; Umapornsakula, A.; Wong, Y. L.; Chawla, S. In The Challenges of New Psychoactive Substances, UNODC Global SMART Programme, 2013.

2. Headspace sampling and detection of cocaine, MDMA, and marijuana via volatile markers in the presence of potential interferences by solid phase microextraction–ion mobility spectrometry (SPME-IMS)

3. Enhancement in sample collection for the detection of MDMA using a novel planar SPME (PSPME) device coupled to ion mobility spectrometry (IMS)

4. Cocaine and other illicit drugs in airborne particulates in urban environments: A reflection of social conduct and population size

5. Characterization of the Volatile Components of Cannabis Preparations by Solid-Phase Microextraction Coupled to Headspace-Gas Chromatography with Mass Detector (SPME-HSGC/MS)

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