Sensor for Rapid In-Field Classification of Cannabis Samples Based on Near-Infrared Spectroscopy.

A rugged handheld sensor for rapid in-field classification of cannabis samples based on their THC content using ultra-compact near-infrared spectrometer technology is presented. The device is designed for use by the Austrian authorities to discriminate between legal and illegal cannabis samples directly at the place of intervention. Hence, the sensor allows direct measurement through commonly encountered transparent plastic packaging made from polypropylene or polyethylene without any sample preparation. The measurement time is below 20 s. Measured spectral data are evaluated using partial least squares discriminant analysis directly on the device's hardware, eliminating the need for internet connectivity for cloud computing. The classification result is visually indicated directly on the sensor via a colored LED. Validation of the sensor is performed on an independent data set acquired by non-expert users after a short introduction. Despite the challenging setting, the achieved classification accuracy is higher than 80%. Therefore, the handheld sensor has the potential to reduce the number of unnecessarily confiscated legal cannabis samples, which would lead to significant monetary savings for the authorities.

The genetics of Cannabis-genomic variations of key synthases and their effect on cannabinoid content.

Despite being a controversial crop, Cannabis sativa L. has a long history of cultivation throughout the world. Following recent legalization in Canada, Cannabis is emerging as an important plant for both medicinal and recreational purposes. Recent progress in genome sequencing of both cannabis and hemp varieties allow for systematic analysis of genes coding for enzymes involved in the cannabinoid biosynthesis pathway. Single-nucleotide polymorphisms in the coding regions of cannabinoid synthases play an important role in determining plant chemotype. Deep understanding of how these variants affect enzyme activity and accumulation of cannabinoids will allow breeding of novel cultivars with desirable cannabinoid profiles. Here we present a short overview of the major cannabinoid synthases and present the data on the analysis of their genetic variants and their effect on cannabinoid content using several in-house sequenced Cannabis cultivars.

Evaluation of the trnK-matK-trnK, ycf3, and accD-psal chloroplast regions to differentiate crop type and biogeographical origin of Cannabis sativa.

Cannabis sativa (marijuana and hemp) is one of the most controversial crops worldwide. In the USA, the state-specific legalization of marijuana and recently legalized hemp pose a problem for law enforcement. This study seeks to utilize chloroplast hSTRs, INDEL, and SNPs markers to develop genotyping methods to aid in the differentiation of legal hemp from illicit marijuana and also for tracking the flow of trafficked marijuana. Three polymorphic regions: trnK-matK-trnK, ycf3, and accD-psal, of the C. sativa chloroplast genome were evaluated in order to distinguish crop type and biogeographic origin. A total of nine polymorphic sites were genotyped from five distinct populations (hemp from the USA and Canada, marijuana from Chile and USA-Mexico, and medical marijuana from Chile) with a custom fragment and SNaPshotTM assay. The study also combined genotype results from the same sample set using 21 additional polymorphic markers from previous studies. The effectiveness of these multi-locus assays to distinguish sample groups was assessed using haplotype analysis, phylogenetic analysis, pairwise comparisons, and principal component analysis. Results indicated a clear separation of Canadian hemp using only the nine polymorphic sites developed in this study. The additional 21 markers were able to separate US hemp from both marijuana groups to a significant level (p < 0.05) when assessing average Fixation Indices (FST). This study demonstrated the applicability of these organelle markers for the determination of crop type and biogeographic origin of C. sativa. However, a more extensive database is needed to evaluate the true discriminatory power of these markers.

Essential Oil of Cannabis sativa L: Comparison of Yield and Chemical Composition of 11 Hemp Genotypes.

Cannabis sativa L. is an annual species cultivated since antiquity for different purposes. While, in the past, hemp inflorescences were considered crop residues, at present, they are regarded as valuable raw materials with different applications, among which extraction of the essential oil (EO) has gained increasing interest in many fields. The aim of the present study is the evaluation of the yield and the chemical composition of the EO obtained by hydrodistillation from eleven hemp genotypes, cultivated in the same location for two consecutive growing seasons. The composition of the EOs was analyzed by GC-MS, and then subjected to multivariate statistical analysis. Sesquiterpenes represented the main class of compounds in all the EOs, both in their hydrocarbon and oxygenated forms, with relative abundances ranging from 47.1 to 78.5%; the only exception was the Felina 32 sample collected in 2019, in which cannabinoids predominated. Cannabinoids were the second most abundant class of compounds, of which cannabidiol was the main one, with relative abundances between 11.8 and 51.5%. The statistical distribution of the samples, performed on the complete chemical composition of the EOs, evidenced a partition based on the year of cultivation, rather than on the genotype, with the exception of Uso-31. Regarding the extraction yield, a significant variation was evidenced among both the genotypes and the years of cultivation.

Therapeutic Potential for Cannabinoids in Sports Medicine: Current Literature Review.

ABSTRACT: Cannabidiol and other cannabinoids are being used more frequently for sports medicine-related conditions. This review will help sports medicine clinicians answer questions that their athletes and active patients have about the potential effectiveness of cannabinoids on common sports medicine conditions. In the article, the authors compare cannabidiol and delta-9-tetrahydrocannabinol effects, noting the difference on the endocannabinoid and nonendocannabinoid receptors. The theoretical benefits of these two compounds and the current legality in the United States surrounding cannabidiol and delta-9-tetrahydrocannabinol use also are addressed.

In-Depth Cannabis Multiclass Metabolite Profiling Using Sorptive Extraction and Multidimensional Gas Chromatography with Low- and High-Resolution Mass Spectrometry.

The present research reports on the development of a methodology to unravel the complex phytochemistry of cannabis. Specifically, cannabis inflorescences were considered and stir bar sorptive extraction (SBSE) was used for the preconcentration of the metabolites. Analytes were thermally desorbed into a comprehensive two-dimensional (2D) gas chromatography (GC × GC) system coupled with low- and high-resolution mass spectrometry (MS). Particular attention was devoted to the optimization of the extraction conditions, to extend the analytes' coverage, and the chromatographic separation, to obtain a robust data set for further untargeted analysis. Monoterpenes, sesquiterpenes, hydrocarbons, cannabinoids, other terpenoids, and fatty acids were considered to optimize the extraction conditions. The response of selected ions for each chemical class, delimited in specific 2D chromatographic regions, enabled an accurate and fast evaluation of the extraction variables (i.e., time, temperature, solvent, salt addition), which were then selected to have a wide analyte selection and good reproducibility. Under optimized SBSE conditions, eight different cannabis inflorescences and a quality control sample were analyzed and processed following an untargeted and unsupervised approach. Principal component analysis on all detected metabolites revealed chemical differences among the sample types which could be associated with the plant subspecies. With the same SBSE-GC × GC-MS methodology, a quantitative targeted analysis was performed on three common cannabinoids, namely, Δ9-tetrahydrocannabinol, cannabidiol, and cannabinol. The method was validated, giving correlation factors over 0.98 and <20% reproducibility (relative standard deviation). The high-resolution MS acquisition allowed for high-confidence identification and post-targeted analysis, confirming the presence of two pesticides, a plasticizer, and a cannabidiol degradation product in some of the samples.

Characterising heterogeneity in the use of different cannabis products: latent class analysis with 55 000 people who use cannabis and associations with severity of cannabis dependence.

BACKGROUND: As new cannabis products and administration methods proliferate, patterns of use are becoming increasingly heterogeneous. However, few studies have explored different profiles of cannabis use and their association with problematic use. METHODS: Latent class analysis (LCA) was used to identify subgroups of past-year cannabis users endorsing distinct patterns of use from a large international sample (n = 55 240). Past-12-months use of six different cannabis types (sinsemilla, herbal, hashish, concentrates, kief, edibles) were used as latent class indicators. Participants also reported the frequency and amount of cannabis used, whether they had ever received a mental health disorder diagnosis and their cannabis dependence severity via the Severity of Dependence Scale (SDS). RESULTS: LCA identified seven distinct classes of cannabis use, characterised by high probabilities of using: sinsemilla & herbal (30.3% of the sample); sinsemilla, herbal & hashish (20.4%); herbal (18.4%); hashish & herbal (18.8%); all types (5.7%); edibles & herbal (4.6%) and concentrates & sinsemilla (1.7%). Relative to the herbal class, classes characterised by sinsemilla and/or hashish use had increased dependence severity. By contrast, the classes characterised by concentrates use did not show strong associations with cannabis dependence but reported greater rates of ever receiving a mental health disorder diagnosis. CONCLUSIONS: The identification of these distinct classes underscores heterogeneity among cannabis use behaviours and provides novel insight into their different associations with addiction and mental health.

Noninteger Root Transformations for Preprocessing Nanoelectrospray Ionization High-Resolution Mass Spectra for the Classification of Cannabis.

Typically, for measurements with a high dynamic range, the range is reduced by using the square root transform. By using noninteger roots coupled with systematic experimental design, improvements to the measurements may be obtained. The effect of using noninteger root transformation was evaluated using high-resolution mass spectrometry (HRMS) combined with nanoelectrospray ionization (Nano-ESI) to differentiate 23 samples of Cannabis. The mass spectra were evaluated and classified using different mass resolving powers and noninteger root transformations. Classification was achieved by super partial least-squares discriminant analysis (sPLS-DA), support vector machine (SVM), and SVM classification tree type entropy (SVMTreeH). The 2.5 root transformation gave the best overall performance at different resolving powers for chemical profiling from a multilevel factorial experimental design using 2 factors and more than 4 levels. Response surface modeling using a cubic polynomial model of the bootstrapped sPLS-DA average prediction accuracies yielded optima at 0.005 for resolving power and 2.3 for the root transformation. Root transformation is an important spectral preprocessing tool for decreasing the dynamic range so that the relative variance of smaller but more important features may be inflated. For the classification of Cannabis using Nano-ESI, the optimal ranges of root and resolution were broad. The chasing-the-optimum method has been introduced for refining the polynomial response surface model.

Pipeline for High-Throughput Modeling of Marijuana and Hemp Extracts.

Authentication of Cannabis products is important for assuring the quality of manufacturing, with the increasing consumption and regulation. In this report, a two-stage pipeline was developed for high-throughput screening and chemotyping the spectra from two sets of botanical extracts from the Cannabis genus. The first set contains different marijuana samples with higher concentrations of tetrahydrocannabinol (THC). The other set includes samples from hemp, a variety of Cannabis sativa with the THC concentration below 0.3%. The first stage applies the technique of class modeling to determine whether spectra belong to marijuana or hemp and reject novel spectra that may be neither marijuana nor hemp. An automatic soft independent modeling of class analogy (aSIMCA) that self-optimizes the number of principal components and the decision threshold is utilized in the first pipeline process to achieve excellent efficiency and efficacy. Once these spectra are recognized by aSIMCA as marijuana or hemp, they are then routed to the appropriate classifiers in the second stage for chemotyping the spectra, i.e., identifying these spectra into different chemotypes so that the pharmacological properties and cultivars of the spectra can be recognized. Three multivariate classifiers, a fuzzy rule building expert system (FuRES), super partial least-squares-discriminant analysis (sPLS-DA), and support vector machine tree type entropy (SVMtreeH), are employed for chemotyping. The discriminant ability of the pipeline was evaluated with different spectral data sets of these two groups of botanical samples, including proton nuclear magnetic resonance, mass, and ultraviolet spectra. All evaluations gave good results with accuracies greater than 95%, which demonstrated promising application of the pipeline for automated high-throughput screening and chemotyping marijuana and hemp, as well as other botanical products.

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

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. Graphical abstract.

New trends in cannabis potency in USA and Europe during the last decade (2008-2017).

Through the potency monitoring program at the University of Mississippi supported by National Institute on Drug Abuse (NIDA), a total of 18108 samples of cannabis preparations have been analyzed over the last decade, using a validated GC/FID method. The samples are classified as sinsemilla, marijuana, ditchweed, hashish, and hash oil (now referred to as cannabis concentrate). The number of samples received over the last 5 years has decreased dramatically due to the legalization of marijuana either for medical or for recreational purposes in many US states. The results showed that the mean Δ9-THC concentration has increased dramatically over the last 10 years, from 8.9% in 2008 to 17.1% in 2017. The mean Δ9-THC:CBD ratio also rose substantially from 23 in 2008 to 104 in 2017. There was also marked increase in the proportion of hash oil samples (concentrates) seized (0.5-4.7%) and their mean Δ9-THC concentration (6.7-55.7%) from 2008 to 2017. Other potency monitoring programs are also present in several European countries such as The Netherlands, United Kingdom, France, and Italy. These programs have also documented increases in Δ9-THC concentrations and Δ9-THC:CBD ratios in cannabis. These trends in the last decade suggest that cannabis is becoming an increasingly harmful product in the USA and Europe.

The Terroir of Cannabis: Terpene Metabolomics as a Tool to Understand Cannabis sativa Selections.

The phytochemical diversity of Cannabis chemovars is not well understood, and many chemovars were created in informal breeding programs without records of parentage or the criteria for selection. Key criteria for selection sometimes included aroma notes and visual cues, which some breeders associated with pharmacological activity. We hypothesized that the process of selection for scents believed to be related to specific tetrahydrocannabinol levels has resulted in modified terpene biosynthesis in these chemovars. Thirty-two cannabinoids, 29 monoterpenes and 38 sesquiterpenes were measured in 33 chemovars from 5 licensed producers. A classification system based on cannabinoid content was used with targeted metabolomic tools to determine relationships in the phytochemistry. Three monoterpenes, limonene, ß-myrcene, and α-pinene, and two sesquiterpenes, caryophyllene and humulene, were abundant in the majority of chemovars. Nine terpenes were present in tetrahydrocannabinol-dominant chemovars. Three monoterpenes and four sesquiterpenes were predominantly found in cannabidiol-containing chemovars. Low abundance terpenes may have been the aromatic cues identified by breeders. The medicinal activity of some of the terpenes is likely to contribute to the pharmacological effect of specific chemovars. Together, these data demonstrate the synergy of compounds in Cannabis chemovars and point to the need for additional research to understand the phytochemical complexity.

The Surprising Reach of FDA Regulation of Cannabis, Even After Descheduling.

As more states legalize cannabis, the push to "deschedule" it from the Controlled Substances Act is gaining momentum. At the same time, the Food and Drug Administration (FDA) recently approved the first conventional drug containing a cannabinoid derived from cannabis­cannabidiol (CBD) for two rare seizure disorders. This would all seem to bode well for proponents of full federal legalization of medical cannabis. But some traditional providers are wary of drug companies pulling medical cannabis into the regular small molecule drug development system. The FDA's focus on precise analytical characterization and on individual active and inactive ingredients may be fundamentally inconsistent with the "entourage effects" theory of medical cannabis. Traditional providers may believe that descheduling cannabis would free them to promote and distribute their products free of federal intervention, both locally and nationally. Other producers appear to assume that descheduling would facilitate a robust market in cannabis-based edibles and dietary supplements. In fact, neither of these things is true. If cannabis were descheduled, the FDA's complex and comprehensive regulatory framework governing foods, drugs, and dietary supplements would preclude much of this anticipated commerce. For example, any medical claims about cannabis would require the seller to complete the rigorous new drug approval process, the cost of which will be prohibitive for most current traditional providers. Likely also unexpected to some, there is no pathway forward for conventional foods containing cannabis constituents, with the (probably exclusive) exception of certain hemp seed ingredients, if those foods cross state lines. And it will certainly come as a shock to many that federal law already prohibits the sale of dietary supplements containing CBD--including those already on the market as well as those made from "hemp," which has recently been descheduled under the 2018 Farm Bill. This Article describes in detail the surprising reach of the FDA and then outlines three modest, but legal, pathways forward for cannabis-based products in a world where cannabis has been descheduled.

The New Cannabis Policy Taxonomy on APIS: Making Sense of the Cannabis Policy Universe.

The National Institute on Alcohol Abuse and Alcoholism's Alcohol Policy Information System (APIS) is, for the first time, adding legal data pertaining to recreational cannabis use to its current offerings on alcohol policy. Now that Colorado, Washington, Oregon, Alaska, and the District of Columbia have legalized aspects of recreational cannabis, and more states are considering it, there is an urgency to provide high-quality, multi-dimensional legal data to the public health community. This article introduces the Cannabis Policy Taxonomy recently posted on APIS, and explores its theoretical and empirical contributions to the substance abuse literature and its potential for use in policy research. We also present results of interviews with public health experts in alcohol and cannabis policy, which sought to determine the most important variables to address in the initial release of cannabis policy data. From this process, we found that pricing controls emerged as the variable singled out by the largest number of experts. This analysis points to a host of vital policies that are of increasing importance to public health policy scholars and their current and future research.