Linear discriminant analysis based on gas chromatographic measurements for geographical prediction of USA medical domestic cannabis

• Autorzy: Al Bakain Ramia Z. , Al-Degs Yahya S. , Cizdziel James V. , Elsohly Mahmoud A.

Identyfikatory

DOI

10.1556/1326.2020.00782

• Języki publikacji: EN

Abstrakty

EN

Fifty four domestically produced cannabis samples obtained from different USA states were quantitatively assayed by GC–FID to detect 22 active components: 15 terpenoids and 7 cannabinoids. The profiles of the selected compounds were used as inputs for samples grouping to their geographical origins and for building a geographical prediction model using Linear Discriminant Analysis. The proposed sample extraction and chromatographic separation was satisfactory to select 22 active ingredients with a wide analytical range between 5.0 and 1,000 µg/mL. Analysis of GC-profiles by Principle Component Analysis retained three significant variables for grouping job (Δ9-THC, CBN, and CBC) and the modest discrimination of samples based on their geographical origin was reported. PCA was able to separate many samples of Oregon and Vermont while a mixed classification was observed for the rest of samples. By using LDA as a supervised classification method, excellent separation of cannabis samples was attained leading to a classification of new samples not being included in the model. Using two principal components and LDA with GC–FID profiles correctly predict the geographical of 100% Washington cannabis, 86% of both Oregon and Vermont samples, and finally, 71% of Ohio samples.

Słowa kluczowe

EN

geographical prediction; medical cannabis; linear discriminant analysis; gas chromatography; principal; component analysis

• Wydawca: University of Silesia in Katowice ; Akademiai Kiado
• Czasopismo: Acta Chromatographica
• Rocznik: 2021
• Tom: Vol. 33, no. 2
• Strony: 179--187
• Opis fizyczny: Bibliogr. 22 poz., rys., tab.

Twórcy

autor

Al Bakain Ramia Z.

• Department of Chemistry, School of Science, The University of Jordan, P.O. Box 11942, Amman, Jordan

• https://orcid.org/0000-0003-0419-0828

autor

Al-Degs Yahya S.

• Chemistry Department, The Hashemite University, P.O. Box 150459, Zarqa, Jordan

autor

Cizdziel James V.

• Department of Chemistry and Biochemistry, University of Mississippi, University, MS, 38677, USA

autor

Elsohly Mahmoud A.

• National Center for Natural Products Research, University, MS, 38677-1848, USA
• Department of Pharmaceutics and Drug Delivery, School of Pharmacy, University of Mississippi, University, MS, 38677, USA

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).