Comprehensive classification of USA cannabis samples based on chemical profiles of major cannabinoids and terpenoids
Ramia Z. Al Bakain, Yahya S. Al-Degs, James V. Cizdziel and Mahmoud A. Elsohly
Journal of Liquid Chromatography & Related Technologies, 2019
Doi : 10.1080/10826076.2019.1701015
Different USA-origin cannabis samples were analyzed by GC-FID to quantify all possible cannabinoids and terpenoids prior to their clustering. Chromatographic analysis confirmed the presence of seven cannabinoids and sixteen terpenoids with variable levels. Among tested cannabinoids, D9-Tetrahydro-cannabinol D9-THC and cannabinol CBN were available in excess amounts (1.2–8.0 wt%) and (0.22–1.1 wt%), respectively. Fenchol was the most abundant terpenoid with a range of (0.03–1.0 wt%). The measured chemical profile was used to cluster 23 USA states and to group plant samples using different unsupervised multivariate statistical tools. Clustering of plant samples and states was sensitive to the selected cannabinoids/terpenoids. Principal component analysis (PCA) indicated the importance of D9 THC, CBN, CBG, CBC, THCV, D8-THC, CBL, and fenchol for samples clustering. D9-THC was significant to separate California-origin samples while CBN and fenchol were dominant to separate Oregon-origin samples away from the rest of cannabis samples. A special PCA analysis was performed on cannabinoids after excluding D9-THC (due to its high variability in the same plant) and CBN (as a degradation by-product for THC). Results indicated that CBL and D8-THC were necessary to separate Nevada and Washington samples, while, CBC was necessary to isolate Oregon and Illinois plant samples. PCA based on terpenoids content confirmed the significance of caryophyllene, guaiol, limonene, linalool, and fenchol for clustering target. Fenchol played a major role for clustering plant samples that originated from Washington and Nevada. k-means method was more flexible than PCA and generated three different classes; samples obtained from Oregon and California in comparison to the rest of other samples were obviously separated alone, which attributed to their unique chemical profile. Finally, both PCA and k-means were useful and quick guides for cannabis clustering based on their chemical profile.
Thus, less effort, time, and materials will be consumed in addition to decreasing operational conditions for cannabis clustering.
KEYWORDS : Cannabinoids; cannabis; k-means clustering; PCA; terpenoids; unsupervised analysis
The size of analytical data in natural products science has increased substantially over the last several years due to the application of advanced instruments and chemometrics. Such development has yielded a better understanding of the chemistry of natural products, particularly for those with medical applications. Recently, a great deal of attention has been paid to the analysis of natural products using sophisticated devices to identify more of their therapeutic potential. Cannabis is among these materials due to its widespread use and its diverse pharmacological properties. Cannabis is a chemically complex species containing a large number of active constituents.[2,3] Herbal cannabis (marijuana), cannabis resin (hashish), and extracts of cannabis resin (hashish oil) are still the most illicit drugs in the world. More than 8000 tons of cannabis are consumed in the USA every year where 11.5 million users purchasing around $10 billion of the drug each year. In addition to the USA, cannabis is very popular in Canada and North America.[2–4] In 2017, many USA states, including Washington, DC, have legalized
the medical use of cannabis, where, 38 licensed producers in Canada are authorized to produce and sell dried marijuana.[ 4] Overall, there has been a major increase in domestic production worldwide.
With the aid of advanced chromatographic instruments, a large number of active ingredients in cannabis samples including cannabinoids and terpenoids were identified.[4,5] Both terpenoids and cannabinoids are known for their variable biological activities. Terpenoids are of great interest because of their production by plants that are likely to consistently reflect the immediate environment and they are responsible for cannabis’ distinctive odor, whereas, cannabinoids would tend to reveal genetic relationships.