Affiliation:
1. Programa de Pós-Graduação em Ciências Farmacêuticas, Universidade Federal do Rio Grande do Sul, Av. Ipiranga 2752, Porto Alegre—RS, Brazil
2. Superintendência da Polícia Federal no Rio Grande Sul, Porto Alegre—RS, Brazil
3. Instituto Nacional de Ciência e Tecnologia Forense (INCT Forense), Brazil
Abstract
Abstract
Background
The analysis of plant material from Cannabis sativa L. has long been targeted on its main psychologically active metabolite, Δ9-tetrahydrocannabinol (THC). In addition to the diverse plant composition and medicinal interest in several cannabinoids, these compounds may also be related to the different characteristics of samples sold illegally. Currently, it is indisputable that other cannabinoids should also be considered on cannabis assays. Mass spectrometry has been used to identify and characterize substances in the most different scenarios, and knowing the analyte fragmentation profile is essential for characterizing samples of unknown origin.
Objective
In this work, a flow injection analysis–tandem mass spectrometry (FIA–ESI-MS/MS) with electrospray ionization in positive and negative modes was used to evaluate the fragmentation profiles of eight cannabinoids commonly found in cannabis samples: THC, tetrahydrocannabinolic acid (THCA), Δ8-tetrahydrocannabinol (Δ8-THC), cannabidiol (CBD), cannabidiolic acid (CBDA), cannabigerol (CBG), cannabigerolic acid (CBGA) and cannabinol (CBN).
Methods
By exploring the fragmentation data from mass spectrometry, the samples were classified using a chemometric model of partial least squares discriminant analysis (PLS-DA).
Results
When ESI in negative mode is used with adequate collision energies, it is possible to identify differences in the fragmentation of isomers. Based on that, chemometric tools were employed to classify different samples. The PLS-DA applied to FIA–ESI-MS/MS data yielded satisfactory classification.
Conclusion
Thus, the results presented can be applied as a preliminary tool in the analysis of unknown samples, guiding for more accurate investigations in terms of chemical composition.
Highlights
Study of the cannabinoid fragmentation pattern by flow injection mass spectrometry. Cannabinoids distinction by fragment spectra after negative electrospray ionization. Multivariate data analysis (PLS-DA) allowed to classify different cannabis samples.
Publisher
Oxford University Press (OUP)
Subject
Pharmacology,Agronomy and Crop Science,Environmental Chemistry,Food Science,Analytical Chemistry
Cited by
3 articles.
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