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The classification of Cannabis hemp cultivars by thermal desorption direct analysis in real time mass spectrometry (TD-DART-MS) with chemometrics

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Abstract

Cannabis has been cultivated as a source of food, fiber, and medicine globally, so the classification of Cannabis cultivars based on their chemical fingerprints is important to standardize and control the quality of Cannabis, ensure that patients receive a full and consistent spectrum of therapeutic benefits, and promote the further implementation of Cannabis-based products in clinical uses. In this study, a high-throughput analytical method, thermal desorption direct analysis in real time mass spectrometry (TD-DART-MS), was employed to classify various Cannabis hemp cultivars with multivariate analysis. Cannabis plant materials from four cultivars were analyzed directly by TD-DART-MS without solvent extraction. The total run time was 15 min including 8 min for data acquisition and 7 min for cooling down the thermal stage. Data preprocessing strategy such as data transformation was evaluated on the TD-DART-MS data set and cubic root transform has shown significant improvement to the classification. TD-DART-MS data was then processed by principal component analysis (PCA) and the results were compared with those from liquid chromatography-mass spectrometry (LC-MS) data. The samples were clustered based on cultivars by PCA, and the validation samples collected 2 months later were also grouped together with the original samples by cultivars after mean-centering the data sets. Partial least squares discriminant analysis (PLS-DA) models were constructed with the TD-DART-MS data sets and a 99.3 ± 0.3% classification accuracy was obtained from 100 independent bootstrapped Latin partition evaluations. Our results indicate that TD-DART-MS may be used as a screening tool for the classification of Cannabis cultivars.

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Acknowledgments

The authors acknowledge IonSense, Inc. for the support and assistance on DART ion source and BioChromato, Inc. for offering IonRocket device for thermal desorption DART-MS experiments.

Funding

Isabella Barnett received support from a MTSU Undergraduate Research Experience and Creative Activity (URECA) grant. This research received additional funding from GreenWay Herbal Products, LLC.

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Authors and Affiliations

  1. Department of Chemistry, Middle Tennessee State University, Murfreesboro, TN, 37132, USA

    Wen Dong, Jian Liang, Paul C. Kline & Mengliang Zhang

  2. Research Center for Traditional Chinese Medicine Resourcing and Ethnic Minority Medicine, Jiangxi University of Traditional Chinese Medicine, Nanchang, 330004, Jiangxi, China

    Jian Liang

  3. Forensic Science Program, College of Basic and Applied Sciences, Middle Tennessee State University, Murfreesboro, TN, 37132, USA

    Isabella Barnett & Mengliang Zhang

  4. Tennessee Center for Botanical Medicine Research, Middle Tennessee State University, Murfreesboro, TN, 37132, USA

    Paul C. Kline & Elliot Altman

  5. Department of Biology, Middle Tennessee State University, Murfreesboro, TN, 37132, USA

    Elliot Altman

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  1. Wen Dong
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  2. Jian Liang
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  3. Isabella Barnett
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Correspondence to Mengliang Zhang.

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Elliot Altman has equity ownership in GreenWay Herbal Products, LLC. The other authors declare that they have no conflict of interest

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Dong, W., Liang, J., Barnett, I. et al. The classification of Cannabis hemp cultivars by thermal desorption direct analysis in real time mass spectrometry (TD-DART-MS) with chemometrics. Anal Bioanal Chem 411, 8133–8142 (2019). https://doi.org/10.1007/s00216-019-02200-7

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