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Title:
Beyond Δ9-tetrahydrocannabinol and cannabidiol: chemical differentiation of cannabis varieties applying targeted and untargeted analysis | Analytical and Bioanalytical Chemistry
Description:
Cannabis sativa (C. sativa) is commonly chemically classified based on its Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD) content ratios. However, the plant contains nearly 150 additional cannabinoids, referred to as minor cannabinoids. Minor cannabinoids are gaining interest for improved plant and product characterization, e.g., for medical use, and bioanalytical questions in the medico-legal field. This study describes the development and validation of an analytical method for the elucidation of minor cannabinoid fingerprints, employing liquid chromatography coupled to high-resolution mass spectrometry. The method was used to characterize inflorescences from 18 different varieties of C. sativa, which were cultivated under the same standardized conditions. Complementing the targeted detection of 15 cannabinoids, untargeted metabolomics employing in silico assisted data analysis was used to detect additional plant ingredients with focus on cannabinoids. Principal component analysis (PCA) was used to evaluate differences between varieties. The overall purpose of this study was to examine the ability of targeted and non-targeted metabolomics using the mentioned techniques to distinguish cannabis varieties from each other by their minor cannabinoid fingerprint. Quantitative determination of targeted cannabinoids already gave valuable information on cannabinoid fingerprints as well as inter- and intra-variety variability of cannabinoid contents. The untargeted workflow led to the detection of 19 additional compounds. PCA of the targeted and untargeted datasets revealed further subgroups extending commonly applied phenotype classification systems of cannabis. This study presents an analytical method for the comprehensive characterization of C. sativa varieties. Graphical abstract
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Keywords {🔍}
cannabis, cannabinoids, varieties, article, pubmed, google, scholar, analysis, untargeted, plant, compounds, cas, targeted, data, thc, cannabinoid, presented, sativa, cbd, additional, pca, mass, analytes, ngml, chemical, detected, phenotype, samples, content, thca, ionization, full, study, approach, results, belonging, table, shown, analytical, plants, levels, range, gold, pot, workflow, method, obtained, applying, product, found,
Topics {✒️}
eva scheurer & katja mercer-chalmers-bender katja mercer-chalmers-bender principal component analysis high-resolution mass spectrometry high-performance liquid chromatography org/res/wdr2021/field/wdr21_booklet_3 similar thc/cbd profile electrospray ionization-mass spectrometry united nations office gc–ms chemical profiles short-term environmental stresses acceptable mass error ± 5 ppm article download pdf similar cannabinoid profiles lc–ms grade methanol high mass-resolution shorter alkyl-chain homologues analytes behave counter-directional cannabidiol n-hexyl homolog extensive phytocannabinoid profiles variety malawi × super skunk applying mass spectrometry deuterated thc-metabolites 11-hydroxy-thc united nations reported article monti dedicated structure-based workflow phytocannabinoid-terpenoid entourage effects 1007/s00216-020-02862-8 chemical profile freeman tp 7-epoxy-gbga isomer 1 detect inter-variety differences full scan acquisition inter-variety cannabinoid variability small sample size privacy choices/manage cookies results hplc-hrms analysis springer international publishing view esi-lc/ms approach malawi × super skunk full scan data trans-δ9-tetrahydrocannabiphorol content untargeted metabolomics employing full scan measurement dried stinging nettles mass spectrom rev traffic drug testing minor cannabinoid fingerprints gas chromatography
Questions {❓}
- Cannabis policies in Canada: how will we know which is best?
- Detectability of various cannabinoids in plasma samples of cannabis users: Indicators of recent cannabis use?
- How does cannabidiol (CBD) influence the acute effects of delta-9-tetrahydrocannabinol (THC) in humans?
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headline:Beyond Δ9-tetrahydrocannabinol and cannabidiol: chemical differentiation of cannabis varieties applying targeted and untargeted analysis
description:Cannabis sativa (C. sativa) is commonly chemically classified based on its Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD) content ratios. However, the plant contains nearly 150 additional cannabinoids, referred to as minor cannabinoids. Minor cannabinoids are gaining interest for improved plant and product characterization, e.g., for medical use, and bioanalytical questions in the medico-legal field. This study describes the development and validation of an analytical method for the elucidation of minor cannabinoid fingerprints, employing liquid chromatography coupled to high-resolution mass spectrometry. The method was used to characterize inflorescences from 18 different varieties of C. sativa, which were cultivated under the same standardized conditions. Complementing the targeted detection of 15 cannabinoids, untargeted metabolomics employing in silico assisted data analysis was used to detect additional plant ingredients with focus on cannabinoids. Principal component analysis (PCA) was used to evaluate differences between varieties. The overall purpose of this study was to examine the ability of targeted and non-targeted metabolomics using the mentioned techniques to distinguish cannabis varieties from each other by their minor cannabinoid fingerprint. Quantitative determination of targeted cannabinoids already gave valuable information on cannabinoid fingerprints as well as inter- and intra-variety variability of cannabinoid contents. The untargeted workflow led to the detection of 19 additional compounds. PCA of the targeted and untargeted datasets revealed further subgroups extending commonly applied phenotype classification systems of cannabis. This study presents an analytical method for the comprehensive characterization of C. sativa varieties.
datePublished:2022-04-05T00:00:00Z
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headline:Beyond Δ9-tetrahydrocannabinol and cannabidiol: chemical differentiation of cannabis varieties applying targeted and untargeted analysis
description:Cannabis sativa (C. sativa) is commonly chemically classified based on its Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD) content ratios. However, the plant contains nearly 150 additional cannabinoids, referred to as minor cannabinoids. Minor cannabinoids are gaining interest for improved plant and product characterization, e.g., for medical use, and bioanalytical questions in the medico-legal field. This study describes the development and validation of an analytical method for the elucidation of minor cannabinoid fingerprints, employing liquid chromatography coupled to high-resolution mass spectrometry. The method was used to characterize inflorescences from 18 different varieties of C. sativa, which were cultivated under the same standardized conditions. Complementing the targeted detection of 15 cannabinoids, untargeted metabolomics employing in silico assisted data analysis was used to detect additional plant ingredients with focus on cannabinoids. Principal component analysis (PCA) was used to evaluate differences between varieties. The overall purpose of this study was to examine the ability of targeted and non-targeted metabolomics using the mentioned techniques to distinguish cannabis varieties from each other by their minor cannabinoid fingerprint. Quantitative determination of targeted cannabinoids already gave valuable information on cannabinoid fingerprints as well as inter- and intra-variety variability of cannabinoid contents. The untargeted workflow led to the detection of 19 additional compounds. PCA of the targeted and untargeted datasets revealed further subgroups extending commonly applied phenotype classification systems of cannabis. This study presents an analytical method for the comprehensive characterization of C. sativa varieties.
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Minor cannabinoids
High-resolution mass spectrometry
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Metabolomics
Chemotaxonomy
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Biochemistry
general
Laboratory Medicine
Characterization and Evaluation of Materials
Food Science
Monitoring/Environmental Analysis
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