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DOI . ORG {}

  1. Analyzed Page
  2. Matching Content Categories
  3. CMS
  4. Monthly Traffic Estimate
  5. How Does Doi.org Make Money
  6. Keywords
  7. Topics
  8. Questions
  9. Schema
  10. External Links
  11. Analytics And Tracking
  12. Libraries
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  14. CDN Services

We began analyzing https://link.springer.com/article/10.1007/s00216-022-04026-2, but it redirected us to https://link.springer.com/article/10.1007/s00216-022-04026-2. The analysis below is for the second page.

Title[redir]:
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

Matching Content Categories {📚}

  • Science
  • Education
  • Careers

Content Management System {📝}

What CMS is doi.org built with?

Custom-built

No common CMS systems were detected on Doi.org, and no known web development framework was identified.

Traffic Estimate {📈}

What is the average monthly size of doi.org audience?

🌠 Phenomenal Traffic: 5M - 10M visitors per month


Based on our best estimate, this website will receive around 5,000,420 visitors per month in the current month.

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How Does Doi.org Make Money? {💸}

We can't see how the site brings in money.

The purpose of some websites isn't monetary gain; they're meant to inform, educate, or foster collaboration. Everyone has unique reasons for building websites. This could be an example. Doi.org might be making money, but it's not detectable how they're doing it.

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?

Schema {🗺️}

WebPage:
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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
         dateModified: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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         Principal component analysis
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         Cannabinomics
         Metabolomics
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         Characterization and Evaluation of Materials
         Food Science
         Monitoring/Environmental Analysis
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            address:
               name:Institute of Forensic Medicine, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
               type:PostalAddress
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      name:Eva Scheurer
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            address:
               name:Institute of Forensic Medicine, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
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      name:Institute of Forensic Medicine, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
      name:Institute of Forensic Medicine, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
      name:Institute of Forensic Medicine, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
      name:Institute of Forensic Medicine, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
      name:Institute of Forensic Medicine, Department of Biomedical Engineering, University of Basel, Basel, Switzerland

External Links {🔗}(310)

Analytics and Tracking {📊}

  • Google Tag Manager

Libraries {📚}

  • Clipboard.js
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Emails and Hosting {✉️}

Mail Servers:

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Name Servers:

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CDN Services {📦}

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