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2 2021

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

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

Acta Chromatographica

2021

Vol. 33, no. 2

179--187

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.

Comprehensive chromatographic profiling of cannabis from 23 USA States marketed for medical purposes

Al Bakain Ramia Z, Al-Degs Yahya, Cizdziel James V., Elsohly Mahmoud A.

Acta Chromatographica

2021

Vol. 33, no. 1

78--90

In this research, cannabis varieties represent 23 USA States were assayed by GC-FID to generate their complex chemical profiles informative for plants clustering. Results showed that 45 cannabinoids and terpenoids were quantified in all plant samples, where 8 cannabinoids and 18 terpenoids were identified. Among organics, Δ9-THC, CBN (cannabinoids) and Fenchol (terpenoid) not only showed the highest levels overall contents, but also were the most important compounds for cannabis clustering. Among States, Washington, Oregon, California and Hawaii have the highest cannabis content. GC-FID data were subjected to PCA and HCA to find (1) the variations among cannabis chemical profiles as a result of growing environment, (2) to reveal the compounds that were responsible for grouping cultivars between clusters and (3) finally, to facilitate the future profile prediction and States clustering of unknown cannabis based on the chemical profile. The 23 cannabis USA States were grouped into three clusters based on only Δ9-THC, CBN, C1 and Fenchol content. Cannabis classification based on GCprofile will meet the practical needs of cannabis applications in clinical research, industrial production, patients’ self-production, and contribute to the standardization of commercially-available cannabis cultivars in USA.