The Role of Mass Spectrometry in the Cannabis Industry

Differentiation of Δ9-THC and CBD Using Silver-Ligand Ion Complexation and Electrospray Ionization Tandem Mass Spectrometry (ESI-MS/MS)

The 2018 Farm Bill defines marijuana as Cannabis sativa L. or any derivative thereof that contains greater than 0.3% Δ9-tetrahydrocannabinol (Δ9-THC) on a dry weight basis. The main cannabinoids present in Cannabis sativa L., Δ9-THC and cannabidiol (CBD), are structural isomers that cannot be differentiated using direct mass spectrometry with soft ionization techniques alone. Due to the classification of marijuana as a Schedule I controlled substance, the differentiation of Δ9-THC and CBD is crucial within the seized drug community. This study explores the use of Ag-ligand ion complexation and electrospray ionization tandem mass spectrometry (ESI-MS/MS) for the differentiation of Δ9-THC and CBD using six different Ag complexes. Differences between the binding affinities of Δ9-THC and CBD for [Ag(PPh3)(OTf)]2 lead to the formation of unique product ions at m/z 421/423, m/z 353/355, and m/z 231 for CBD, enabling the differentiation of CBD from Δ9-THC. When applied to the analysis of known Δ9-THC:CBD mixture ratios, the developed [Ag(PPh3)(OTf)]2 ion complexation method was able to differentiate Δ9-THC-rich and CBD-rich samples based on the average abundance of the product ions at m/z 421/423. The developed approach was then applied to methanolic extracts of 20 authentic cannabis samples with known Δ9-THC and CBD compositions, resulting in a 95% correct classification rate. Even though the developed Ag-ligand ion complexation method was only demonstrated for the qualitative differentiation of Δ9-THC-rich and CBD-rich cannabis, this study establishes a foundation for the use of Ag-ligand ion complexation that is essential for future quantitative approaches.

Molecularly imprinted polymers (MIP) combined with Raman spectroscopy for selective detection of Δ⁹-tetrahydrocannabinol (THC)

A proof-of-concept sensor is developed for the sensitive and selective detection of Trans-Δ⁹-tetrahydrocannabinol (THC) based on a molecularly imprinted polymer (MIP) synthesized with a THC template which was analyzed using Raman spectroscopy to perform label-free monitoring of THC based on a single identifying Raman peak. The MIP sensor produced a peak at 1614 cm-1 in the Raman spectrum originating from the THC target molecule, allowing for the selective quantification of bound THC with the lowest detection limit of 250 ppm. A higher sensitivity of the MIP to the THC target molecule was observed compared to the non-imprinted polymer (NIP) control which confirmed the presence of THC-specific recognition sites within the synthesized MIP sensing material. The selectivity of this MIP-based sensor was determined by measuring the Raman spectrum of MIP exposed to Cannabidiol (CBD), ethanol, and acetone.

Modeling a pesticide remediation strategy for preparative liquid chromatography using high-performance liquid chromatography

BACKGROUND

Cannabis sativa L. also known as industrial hemp, is primarily cultivated as source material for cannabinoids cannabidiol (CBD) and ∆9-tetrahydrocannabinol (∆9-THC). Pesticide contamination during plant growth is a common issue in the cannabis industry which can render plant biomass and products made from contaminated material unusable. Remediation strategies to ensure safety compliance are vital to the industry, and special consideration should be given to methods that are non-destructive to concomitant cannabinoids. Preparative liquid chromatography (PLC) is an attractive strategy for remediating pesticide contaminants while also facilitating targeted isolation cannabinoids in cannabis biomass.

METHODS

The present study evaluated the benchtop-scale suitability of pesticide remediation by liquid chromatographic eluent fractionation, by comparing retention times of 11 pesticides relative to 26 cannabinoids. The ten pesticides evaluated for retention times are clothianidin, imidacloprid, piperonyl butoxide, pyrethrins (I/II mixture), diuron, permethrin, boscalid, carbaryl, spinosyn A, and myclobutanil. Analytes were separated prior to quantification on an Agilent Infinity II 1260 high performance liquid chromatography with diode array detection (HPLC-DAD). The detection wavelengths used were 208, 220, 230, and 240 nm. Primary studies were performed using an Agilent InfinityLab Poroshell 120 EC-C18 3.0 × 50 mm column with 2.7 μm particle diameter, using a binary gradient. Preliminary studies on Phenomenex Luna 10 μm C18 PREP stationary phase were performed using a 150 × 4.6 mm column.

RESULTS

The retention times of standards and cannabis matrices were evaluated. The matrices used were raw cannabis flower, ethanol crude extract, CO₂ crude extract, distillate, distillation mother liquors, and distillation bottoms. The pesticides clothianidin, imidacloprid, carbaryl, diuron, spinosyn A, and myclobutanil eluted in the first 3.6 min, and all cannabinoids (except for 7-OH-CBD) eluted in the final 12.6 min of the 19-minute gradient for all matrices evaluated. The elution times of 7-OH-CBD and boscalid were 3.44 and 3.55 min, respectively.

DISCUSSION

7-OH-CBD is a metabolite of CBD and was not observed in the cannabis matrices evaluated. Thus, the present method is suitable for separating 7/11 pesticides and 25/26 cannabinoids tested in the six cannabis matrices tested. 7-OH-CBD, pyrethrins I and II (RT_A: 6.8 min, RT_B: 10.5 min), permethrin (RT_A: 11.9 min, RT_B: 12.2 min), and piperonyl butoxide (RT_A: 8.3 min, RT_B: 11.7 min), will require additional fractionation or purification steps.

CONCLUSIONS

The benchtop method was demonstrated have congruent elution profiles using preparative-scale stationary phase. The resolution of pesticides from cannabinoids in this method indicates that eluent fractionation is a highly attractive industrial solution for pesticide remediation of contaminated cannabis materials and targeted isolation of cannabinoids.

Comprehensive Controller for Super Sonic Molecular Beam Gas Chromatograph Mass Spectrometer

This paper presents a new, comprehensive digital circuit used for the control of a novel gas chromatograph mass spectrometer (GC-MS) interface that is based on supersonic molecular beam (SMB). The circuit includes a Texas Instruments 150 MHz digital signal controller (DSC), high voltage amplifiers for 8 independent channels and 4 independent channels of high resolution pulse width modulation (PWM). The circuit, along with a sophisticated embedded program and a custom made personal computer (PC) application, control all aspects of the interface: smart filament emission-current stabilization, static and scanning mass-dependent ion-source voltages, transfer-line heater proportional integral differential (PID) controls with thermocouple feedbacks, on/off valves, relays and several peripheral device controls that enable the full operation of a turbo-molecular vacuum pump, and of gas flow and pressure controllers. All aspects of this comprehensive controller were successfully tested. The signal for the 450 Th ion (C32H66) for example increased by 123% which is a significant increase. It is obvious that correctly tuned dynamic voltages can guarantee the optimal signal for each mass.

Development and Validation of the LC-MS/MS Method for Determination of 130 Natural and Synthetic Cannabinoids in Cannabis Oil

Dietary supplements are widely available products used by millions of people around the world. Unfortunately, the procedure of adding pharmaceutical and psychoactive substances has recently been observed, in order to increase the effectiveness of supplements in the form of hemp oils. For this reason, it is extremely important to develop analytical methods for the detection of substances prohibited in dietary supplements and food products. In the present study, using the LC-MS/MS technique, an innovative method for the detection and quantification of 117 synthetic cannabinoids and 13 natural cannabinoids in dietary supplements and food products in the form of oils during one 13-min chromatographic run was developed. Each method was fully validated by characterization of the following parameters: The limit of detection was set to 0.1 ng/mL (100 µg/g, 0.01%). The limit of quantification ranged from 0.05 ng/mL to 50 ng/mL. The criteria assumed for systematic error caused by methodological bias (±20%) resulting from the recovery of analytes after the extraction process, as well as the coefficient of variation (CV) (≤20%), were met for all 130 tested compounds. The positive results of the validation confirmed that the developed methods met the requirements related to the adequacy of their application in a given scope. Additionally, methods developed using the LC-MS/MS technique were verified via proficiency tests. The developed analytical procedure was successfully used in the analysis of hemp oils and capsules containing them in the studied dietary supplements.

Selective isolation of pesticides and cannabinoids using polymeric ionic liquid-based sorbent coatings in solid-phase microextraction coupled to high-performance liquid chromatography

The high abundance of cannabinoids within cannabis samples presents an issue for pesticide testing as cannabinoids are often co-extracted with pesticides using various sample preparation techniques. Cannabinoids may also chromatographically co-elute with moderate polarity pesticides and inhibit the ionization of pesticides when using mass spectrometry. To circumvent these issues, we have developed a new approach to isolate commonly regulated pesticides and cannabinoids from aqueous samples using tunable, crosslinked imidazolium polymeric ionic liquid (PIL)-based sorbent coatings for direct immersion solid-phase microextraction (DI-SPME). The selectivity of four PIL sorbent coatings towards 20 pesticides and six cannabinoids, including cannabidiol and Δ⁹-THC, was investigated and compared against a commercial PDMS/DVB fiber. Extraction and desorption conditions, including salt content, extraction temperature, pH, extraction time, desorption solvent, and desorption time, were optimized using high-performance liquid chromatography (HPLC) with ultraviolet (UV) detection. Under optimized conditions, the PIL fiber consisting of 1-vinylbenzyl-3-octylimidazolium bis[(trifluoromethyl)sulfonyl]imide ([VBIMC₈⁺][NTf₂^-]) and 1,12-di(3-vinylbenzylimidazolium)dodecane dibis[(trifluoromethyl)sulfonyl]imide ([(VBIM)₂C₁₂²⁺]2[NTf₂^-]) sorbent coating provided the best selectivity towards pesticides compared to other PILs and the PDMS/DVB fibers and was able to reach limits of detection (LODs) as low as 1 µg/L. When compared to a previously reported PIL-based SPME HPLC-UV method for pesticide analysis, the amount of cannabinoids extracted from the sample was decreased 9-fold while a 4-fold enhancement in the extraction of pesticides was achieved. Additionally, the PIL-based SPME method was applied to samples containing environmentally-relevant concentrations of pesticides and cannabinoids to assess its feasibility for Cannabis quality control testing. Relative recoveries between 95% and 141% were obtained using the PIL sorbent coating while recoveries ranging from 50% to 114% were obtained using the PDMS/DVB fiber.

Rapid In Situ Detection of THC and CBD in Cannabis sativa L. by 1064 nm Raman Spectroscopy

The need to find a rapid and worthwhile technique for the in situ detection of the content of delta-9-tetrahydrocannabinol (THC) and cannabidiol (CBD) in Cannabis sativa L. is an ever-increasing problem in the forensic field. Among all the techniques for the detection of cannabinoids, Raman spectroscopy can be identified as the most cost-effective, fast, noninvasive, and nondestructive. In this study, 42 different samples were analyzed using Raman spectroscopy with 1064 nm excitation wavelength. The use of an IR wavelength laser showed the possibility to clearly identify THC and CBD in fresh samples, without any further processing, knocking out the contribution of the fluorescence generated by visible and near-IR sources. The results allow assigning all the Raman features in THC- and CBD-rich natural samples. The multivariate analysis underlines the high reproducibility of the spectra and the possibility to distinguish immediately the Raman spectra of the two cannabinoid species. Furthermore, the ratio between the Raman bands at 1295/1440 and 1623/1663 cm^–1 is identified as an immediate test parameter to evaluate the THC content in the samples.

Direct In Vivo Analysis of CBD- and THC-Acid Cannabinoids and Classification of Cannabis Cultivars Using SpiderMass

In recent years, cannabis and hemp-based products have become increasingly popular for recreational use, edibles, beverages, health care products, and medicines. The rapid detection and differentiation of phytocannabinoids is, therefore, essential to assess the potency and the therapeutic and nutritional values of cannabis cultivars. Here, we implemented SpiderMass technology for in vivo detection of cannabidiolic acid (CBDA) and ∆9-tetrahydrocannabinolicacid (∆9-THCA), and other endogenous organic plant compounds, to access distribution gradients within the plants and differentiate between cultivars. The SpiderMass system is composed of an IR-laser handheld microsampling probe connected to a mass spectrometer through a transfer tube. The analysis was performed on different plant organs from freshly cultivated cannabis plants in only a few seconds. SpiderMass analysis easily discriminated the two acid phytocannabinoid isomers via MS/MS, and the built statistical models differentiated between four cannabis cultivars. Different abundancies of the two acid phytocannabinoids were found along the plant as well as between different cultivars. Overall, these results introduce direct analysis by SpiderMass as a compelling analytical alternative for rapid hemp analysis.

Analysis of cannabis seizures by non-targeted liquid chromatography-tandem mass spectrometry

Due to the popularity of recreational cannabis use, contamination of this drug with diverse classes of chemicals, including pesticides, mycotoxins, and synthetic cannabinoids, has been identified as major threat for public health. For the detection of these compounds in seized cannabis, a screening workflow involving non-targeted liquid chromatography-tandem mass spectrometry (LCMS/MS) was developed. A Quick, Easy, Cheap, Effective, Rugged and Safe (QuEChERS) method was used for the extraction of small bioorganic molecules from ground dried material. Instrumental analysis involved chromatographic separation of compounds and subsequent mass spectrometric detection. Collection of MS and MS/MS information was accomplished by data-dependent acquisition. Compound identification was primarily based on matching acquired MS/MS-spectra to several thousands of reference spectra stored in multiple libraries. Additionally, for selected cannabinoid and pesticide standards, a retention time library was developed. Performance of the workflow was evaluated for 182 pesticides. All tested pesticides were detectable at 5000 μg/kg, 94 % at 500 μg/kg, and 50 % at 50 μg/kg. The workflow was applied to the screening of seized cannabis samples. 41 out of 93 analysed samples (44 %) were tested positive for one or more contaminants impairing quality and/or safety of the material. The detected contaminants included a synthetic cannabinoid (5F-MDMB-PINACA), fifteen pesticide residues (boscalid, carbendazim, chlorantraniliprole, chlorpyrifos, chlorotoluron, cyprodinil, diflubenzuron, ethiofencarb sulfoxide, hexythiazox, iprodione, metalaxyl, pyrimethanil, terbutryn, thiophanate methyl, and trifloxystrobin), and a mycotoxin (sterigmatocystin).

Recent applications of mass spectrometry for the characterization of cannabis and hemp phytocannabinoids: From targeted to untargeted analysis

This review is a collection of recent applications of mass spectrometry studies for the characterization of phytocannabinoids in cannabis and hemp plant material and related products. The focus is mostly on recent applications using mass spectrometry as detector, in hyphenation to typical separation techniques (i.e., liquid chromatography or gas chromatography), but also with less common couplings or by simple direct analysis. The papers are described starting from the most common approach for targeted quantitative analysis, with applications using low-resolution mass spectrometry equipment, but also with the introduction of high-resolution mass analyzers as the detectors. This reflects a common trend in this field, and introduces the most recent applications using high-resolution mass spectrometry for untargeted analysis. The different approaches used for untargeted analysis are then described, from simple retrospective analysis of compounds without pure standards, through untargeted metabolomics strategies, and suspect screening methods, which are the ones currently allowing to achieve the most detailed qualitative characterization of the entire phytocannabinoid composition, including minor compounds which are usually overlooked in targeted studies and in potency evaluation. These approaches also represent powerful strategies to answer questions on biological and pharmacological activity of cannabis, and provide a sound technology for improved classification of cannabis varieties. Finally, open challenges are discussed for future directions in the detailed study of complex phytocannabinoid mixtures.

Revealing Unknown Controlled Substances and New Psychoactive Substances Using High-Resolution LC-MS/MS Machine Learning Models and the Hybrid Similarity Search Algorithm

High-resolution LC-MS/MS tandem mass spectra-based machine learning models are constructed to address the analytical challenge of identifying unknown controlled substances and new psychoactive substances (NPS's). Using a training set comprised of 770 LC-MS/MS barcode spectra (with binary entries 0 or 1) obtained generally by high-resolution mass spectrometers, three classification machine learning models were generated and evaluated. The three models are artificial neural network (ANN), support vector machine (SVM), and k-nearest neighbor (k-NN) models. In these models, controlled substances and NPS's were classified into 13 subgroups (benzylpiperazine, opiate, benzodiazepine, amphetamine, cocaine, methcathinone, classical cannabinoid, fentanyl, 2C series, indazole carbonyl compound, indole carbonyl compound, phencyclidine, and others). Using 193 LC-MS/MS barcode spectra as an external test set, accuracy of the ANN, SVM, and k-NN models were evaluated as 72.5%, 90.0%, and 94.3%, respectively. Also, the hybrid similarity search (HSS) algorithm was evaluated to examine whether this algorithm can successfully identify unknown controlled substances and NPS's whose data are unavailable in the database. When only 24 representative LC-MS/MS spectra of controlled substances and NPS's were selectively included in the database, it was found that HSS can successfully identify compounds with high reliability. The machine learning models and HSS algorithms are incorporated into our home-coded AI-SNPS (artificial intelligence screener for narcotic drugs and psychotropic substances) standalone software that is equipped with a graphic user interface. The use of this software allows unknown controlled substances and NPS's to be identified in a convenient manner.

Raman spectroscopy enables phenotyping and assessment of nutrition values of plants: a review

Our civilization has to enhance food production to feed world's expected population of 9.7 billion by 2050. These food demands can be met by implementation of innovative technologies in agriculture. This transformative agricultural concept, also known as digital farming, aims to maximize the crop yield without an increase in the field footprint while simultaneously minimizing environmental impact of farming. There is a growing body of evidence that Raman spectroscopy, a non-invasive, non-destructive, and laser-based analytical approach, can be used to: (i) detect plant diseases, (ii) abiotic stresses, and (iii) enable label-free phenotyping and digital selection of plants in breeding programs. In this review, we critically discuss the most recent reports on the use of Raman spectroscopy for confirmatory identification of plant species and their varieties, as well as Raman-based analysis of the nutrition value of seeds. We show that high selectivity and specificity of Raman makes this technique ideal for optical surveillance of fields, which can be used to improve agriculture around the world. We also discuss potential advances in synergetic use of RS and already established imaging and molecular techniques. This combinatorial approach can be used to reduce associated time and cost, as well as enhance the accuracy of diagnostics of biotic and abiotic stresses.

The Highs and Lows of P Supply in Medical Cannabis: Effects on Cannabinoids, the Ionome, and Morpho-Physiology

Environmental conditions, including the availability of mineral nutrients, affect secondary metabolism in plants. Therefore, growing conditions have significant pharmaceutical and economic importance for Cannabis sativa. Phosphorous is an essential macronutrient that affects central biosynthesis pathways. In this study, we evaluated the hypothesis that P uptake, distribution and availability in the plant affect the biosynthesis of cannabinoids. Two genotypes of medical "drug-type" cannabis plants were grown under five P concentrations of 5, 15, 30, 60, and 90 mg L-1 (ppm) in controlled environmental conditions. The results reveal several dose-dependent effects of P nutrition on the cannabinoid profile of both genotypes, as well as on the ionome and plant functional physiology, thus supporting the hypothesis: (i) P concentrations ≤15 mg L-1 were insufficient to support optimal plant function and reduced photosynthesis, transpiration, stomatal conductance and growth; (ii) 30-90 mg L-1 P was within the optimal range for plant development and function, and 30 mg L-1 P was sufficient for producing 80% of the maximum yield; (iii) Ionome: about 80% of the plant P accumulated in the unfertilized inflorescences; (iv) Cannabinoids: P supply higher than 5 mg L-1 reduced Δ9-tetrahydrocannabinolic acid (THCA) and cannabidiolic acid (CBDA) concentrations in the inflorescences by up to 25%. Cannabinoid concentrations decreased linearly with increasing yield, consistent with a yield dilution effect, but the total cannabinoid content per plant increased with increasing P supply. These results reveal contrasting trends for effects of P supply on cannabinoid concentrations that were highest under <30 mg L-1 P, vs. inflorescence biomass that was highest under 30-90 mg L-1 P. Thus, the P regime should be adjusted to reflect production goals. The results demonstrate the potential of mineral nutrition to regulate cannabinoid metabolism and optimize pharmacological quality.

Cannabis and its cannabinoids analysis by gas chromatography-mass spectrometry with Cold EI

Cannabis extracts and products were analyzed by gas chromatography-mass spectrometry (GC-MS) with Cold EI for their full content including terpenes, sesquiterpenes, sesquiterpinols, fatty acids, delta 9-tetrahydrocannabinol (THC), cannabidiol (CBD), other cannabinoids, hydrocarbons, sterols, diglycerides, triglycerides, and impurities. GC-MS with Cold EI is based on interfacing GC and MS with supersonic molecular beams (SMB) along with electron ionization of vibrationally cold sample compounds in the SMB in a fly-through ion source (hence the name Cold EI). GC-MS with Cold EI improves all the performance aspects of GC-MS, enables the analysis of Cannabinoids with OH groups without derivatization, while providing enhanced molecular ions for improved identification, and enables internal quantitation without calibration. We found over 50 cannabinoid compounds including a new one with a Cold EI mass spectrum very similar to delta 9-THC as well as relatively large cannabinoids with molecular weight above m/z = 400. Because the analysis was universal in full scan and not targeted, we found impurities such as bromo CBD and fluticasone propionate and could monitor the formation of oxidized CBD during decarboxylation. In addition, GC-MS with Cold EI enabled nontargeted full analysis of terpenes, sesquiterpenes, and sesquiterpinols in cannabis extracts with good internal quantitation. GC-MS with Cold EI further served with very good sensitivity for the concentration determination of delta 9-THC in CBD-related products. Finally, cannabis drugs such as EP-1 used in Israel for treatment of epilepsy and for children with autism spectrum disorder (ASD) were analyzed for their full cannabinoids content for learning on the entourage effect and for drug activity optimization.

Analysis of the California list of pesticides, mycotoxins, and cannabinoids in chocolate using liquid chromatography and low-pressure gas chromatography-based platforms

Cannabis legalization has led to the development of a variety of cannabis-infused products with edibles being one of the most popular. The state of California has implemented comprehensive cannabis testing regulations requiring the analysis of cannabinoids (potency) and contaminants, such as pesticides and mycotoxins, in any type of cannabis good. In this work, we propose an analytical workflow for the quantification of the California list of pesticides and mycotoxins, as well as six cannabinoids, in chocolate, using 3 mL of solvent for the extraction. For the analysis of pesticides and mycotoxins, clean-up steps employing a C18 solid-phase extraction cartridge and dispersive solid-phase extraction sorbents were implemented. Gas chromatography amenable pesticides were analyzed using low-pressure gas chromatography coupled to tandem mass spectrometry which allowed for a total method run of 12 min. Both liquid chromatography and gas chromatography instrumental methods had the same analysis time, ensuring satisfactory sample throughput. For the determination of cannabinoids, a dilution of the original organic extract collected for pesticides and mycotoxins analysis (and prior to any clean-up step) was used. Excellent results in terms of analytical figures of merit were obtained for all target analytes.

Discrimination of CBD-, THC- and CBC-type acid cannabinoids through diagnostic ions by UHPLC-HR-MS/MS in negative ion mode

The interest in industrial hemp-based products and by-products to be utilized in food and nutraceutical sector is strictly linked to the demand for improved analytical methods to rapidly discriminate acid phytocannabinoid isomers. Indeed, the differentiation of acid phytocannabinoids, also named pre-cannabinoids, is not properly exploited and valued until now, and it is challenging. Herein, using high-resolution MS/MS, the most common pre-cannabinoids with the resorcinol core linked to the alkyl five carbons chain were deeply investigated in terms of their reactivity to collision-induced dissociation, gaining key data on the integrated energy framework of their dissociation pathway. In fact, CBD-, THC- and CBC-type pre-cannabinoids could be discriminated based on the base peak identity, and the intensity of common fragment ions, when collision energy fragmented precursor ions by 70-75 %. In particular, energy-resolved CID mass spectra highlighted that fragmentation occurs, unrelatedly to alkyl chain length, at phenolic and monoterpenic moieties levels. Accordingly, this tool is effective for further differentiating pre-cannabinoid homologues, from methyl- up to heptyl-homologues, getting new insight in acid cannabinoids heritage of hemp and its products.

Raman-Based Diagnostics of Biotic and Abiotic Stresses in Plants. A Review

Digital farming is a novel agricultural philosophy that aims to maximize a crop yield with the minimal environmental impact. Digital farming requires the development of technologies that can work directly in the field providing information about a plant health. Raman spectroscopy (RS) is an emerging analytical technique that can be used for non-invasive, non-destructive, and confirmatory diagnostics of diseases, as well as the nutrient deficiencies in plants. RS is also capable of probing nutritional content of grains, as well as highly accurate identification plant species and their varieties. This allows for Raman-based phenotyping and digital selection of plants. These pieces of evidence suggest that RS can be used for chemical-free surveillance of plant health directly in the field. High selectivity and specificity of this technique show that RS may transform the agriculture in the US. This review critically discusses the most recent research articles that demonstrate the use of RS in diagnostics of abiotic and abiotic stresses in plants, as well as the identification of plant species and their nutritional analysis.

Regulatory sampling of industrial hemp plant samples (Cannabis sativa L.) using UPLC-MS/MS method for detection and quantification of twelve cannabinoids

Background

In 2018, the Farm Bill mandated the United States Department of Agriculture to develop regulations governing the cultivation, processing, and marketing of industrial hemp. Industrial hemp is defined as Cannabis sativa L. with a total Δ-9-tetrahydrocannabinol (Δ-9-THC) content ≤0.3%. Therefore, for hemp to become an agricultural commodity, it is important to regulate production by developing standard methods for sampling and testing of the plant material.

Methods

An ultra-performance liquid chromatography-tandem mass spectrometry analytical method for the quantification of twelve cannabinoids was developed. The method was applied to a regulatory sampling trial of three hemp varieties cultivated for cannabidiol (CBD) production. Two samples were taken from 28 plants with one sample being flower only while the other was a composite sample that included flowers, leaves, and stems.

Results

The assay method was validated for specificity, range, repeatability, reproducibility, and recovery in accordance with all applicable standards for analytical methods. The results of the regulatory study indicated a significant decrease in the concentration of total Δ-9-THC and total CBD of 0.09% and 1.32%, respectively, between a flower only and a composite sample.

Conclusions

There are many factors that may influence reported total Δ-9-THC content in industrial hemp. A robust analytical method was developed to analyze hemp samples in a trial regulatory study. The results indicate that the way hemp is sampled and analyzed may influence the legality of a crop, which could have negative economic and legal consequences.

Relationship among subjective responses, flavor, and chemical composition across more than 800 commercial cannabis varieties

BACKGROUND

Widespread commercialization of cannabis has led to the introduction of brand names based on users' subjective experience of psychological effects and flavors, but this process has occurred in the absence of agreed standards. The objective of this work was to leverage information extracted from large databases to evaluate the consistency and validity of these subjective reports, and to determine their correlation with the reported cultivars and with estimates of their chemical composition (delta-9-THC, CBD, terpenes).

METHODS

We analyzed a large publicly available dataset extracted from Leafly.com where users freely reported their experiences with cannabis cultivars, including different subjective effects and flavour associations. This analysis was complemented with information on the chemical composition of a subset of the cultivars extracted from Psilabs.org . The structure of this dataset was investigated using network analysis applied to the pairwise similarities between reported subjective effects and/or chemical compositions. Random forest classifiers were used to evaluate whether reports of flavours and subjective effects could identify the labelled species cultivar. We applied Natural Language Processing (NLP) tools to free narratives written by the users to validate the subjective effect and flavour tags. Finally, we explored the relationship between terpenoid content, cannabinoid composition and subjective reports in a subset of the cultivars.

RESULTS

Machine learning classifiers distinguished between species tags given by "Cannabis sativa" and "Cannabis indica" based on the reported flavours:  = 0.828 ± 0.002 (p < 0.001); and effects:  = 0.9965 ± 0.0002 (p < 0.001). A significant relationship between terpene and cannabinoid content was suggested by positive correlations between subjective effect and flavour tags (p < 0.05, False-Discovery-rate (FDR)-corrected); these correlations clustered the reported effects into three groups that represented unpleasant, stimulant and soothing effects. The use of predefined tags was validated by applying latent semantic analysis tools to unstructured written reviews, also providing breed-specific topics consistent with their purported subjective effects. Terpene profiles matched the perceptual characterizations made by the users, particularly for the terpene-flavours graph (Q = 0.324).

CONCLUSIONS

Our work represents the first data-driven synthesis of self-reported and chemical information in a large number of cannabis cultivars. Since terpene content is robustly inherited and less influenced by environmental factors, flavour perception could represent a reliable marker to indirectly characterize the psychoactive effects of cannabis. Our novel methodology helps meet demands for reliable cultivar characterization in the context of an ever-growing market for medicinal and recreational cannabis.

Review of Health Consequences of Electronic Cigarettes and the Outbreak of Electronic Cigarette, or Vaping, Product Use-Associated Lung Injury

Electronic cigarettes (e-cigarettes) are battery-operated devices to insufflate nicotine or other psychoactive e-liquid aerosols. Despite initial claims of e-cigarettes as a nicotine-cessation device, aggressive marketing of e-cigarettes has led to an explosion in adolescents' and young adults' use over the last few years. Coupled with a lack of adequate investigation and regulation of e-cigarettes, the USA is facing an outbreak of e-cigarette, or vaping, product use-associated lung injury (EVALI) starting in mid-2019. While little long-term health hazard data are available, the components and constituents of e-cigarettes may adversely impact health. Propylene glycol and glycerin are humectants (water-retaining excipients) that generate pulmonary irritants and carcinogenic carbonyl compounds (e.g., formaldehyde, acetaldehyde, and acrolein) when heated in e-cigarettes. Metals contained in heating coils and cartridge casings may leach metals such as aluminum, chromium, iron, lead, manganese, nickel, and tin. Flavoring agents are considered safe for ingestion but lack safety data for inhalational exposures. Diacetyl, a common buttery flavoring agent, has known pulmonary toxicity with inhalational exposures leading to bronchiolitis obliterans. In 2019, clusters of lung injury associated with e-cigarette use were identified in Wisconsin and Illinois. Patients with EVALI present with a constellation of respiratory, gastrointestinal, and constitutional symptoms. Radiographically, patients have bilateral ground glass opacifications. As of February 18, 2020, the Centers for Disease Control has identified 2807 hospitalized patients diagnosed with either "confirmed" or "probable" EVALI in the US. Currently, vitamin E acetate (VEA) used as a diluent in tetrahydrocannabinol vape cartridges is implicated in EVALI. VEA cuts tetrahydrocannabinol oil without changing the appearance or viscosity. When inhaled, pulmonary tissue lacks the mechanism to metabolize and absorb VEA, which may lead to its accumulation. While most EVALI patients were hospitalized, treatment remains largely supportive, and use of corticosteroids has been associated with clinical improvement. The outbreak of EVALI highlights the need for regulation of e-cigarette devices and e-liquids. Clinicians need to be aware of the health hazards of e-cigarettes and be vigilant in asking about vaping.

Interpol review of controlled substances 2016-2019

This review paper covers the forensic-relevant literature in controlled substances from 2016 to 2019 as a part of the 19th Interpol International Forensic Science Managers Symposium. The review papers are also available at the Interpol website at: https://www.interpol.int/content/download/14458/file/Interpol%20Review%20Papers%202019.pdf.

Raman-Based Differentiation of Hemp, Cannabidiol-Rich Hemp, and Cannabis

Hemp (Cannabis sativa) has been used to treat pain as far back as 2900 B.C. Its pharmacological effects originate from a large variety of cannabinols. Although more than 100 different cannabinoids have been isolated from Cannabis plants, clear physiological effects of only a few of them have been determined, including delta-9 tetrahydrocannabinol (THC), cannabidiol (CBD), and cannabigerol (CBG). While THC is an illicit drug, CBD and CBG are legal substances that have a variety of unique pharmacological properties such as the reduction of chronic pain, inflammation, anxiety, and depression. Over the past decade, substantial efforts have been made to develop Cannabis varieties that would produce large amounts of CBD and CBG. Ideally, such plant varieties should produce very little (below 0.3%) if any THC to make their cultivation legal. The amount of cannabinoids in the plant material can be determined using high performance liquid chromatography (HPLC). This analysis, however, is nonportable, destructive, and time and labor consuming. Our group recently proposed to use Raman spectroscopy (RS) for confirmatory, noninvasive, and nondestructive differentiation between hemp and cannabis. The question to ask is whether RS can be used to detect CBD and CBG in hemp, as well as enable confirmatory differentiation between hemp, cannabis, and CBD-rich hemp. In this manuscript, we show that RS can be used to differentiate between cannabis, CBD-rich plants, and regular hemp. We also report spectroscopic signatures of CBG, cannabigerolic acid (CBGA), THC, delta-9-tetrahydrocannabinolic acid (THCA), CBD, and cannabidiolic acid (CBDA) that can be used for Raman-based quantitative diagnostics of these cannabinoids in plant material.

Confirmatory non-invasive and non-destructive differentiation between hemp and cannabis using a hand-held Raman spectrometer

Cannabis is a generic term that is used to denote hemp plants (Cannabis sativa) that produce delta-9-tetrahydrocannabinolic acid (THCA) in amounts higher than industrial hemp. While THCA itself is not considered psychoactive, it is the source of the psychoactive delta-9 tetrahydrocannabinol (THC) that forms from its oxidation. About 147 million people, which is around 2.5% of the world population, consume cannabis. This makes cannabis by far the most widely cultivated and trafficked illicit drug in the world. Such enormous popularity of cannabis requires substantial effort by border control and law enforcement agencies to control illegal trafficking and distribution. Confirmatory diagnostics of cannabis is currently done by high pressure liquid chromatography (HPLC), which requires sample transportation to a certified laboratory, making THC diagnostics extremely time and labor consuming. This catalyzed a push towards development of a portable, confirmatory, non-invasive and non-destructive approach for cannabis diagnostics that could be performed by a police officer directly in the field to verify illicit drug possession or transport. Raman spectroscopy (RS) is a modern analytical technique that meets all these strict expectations. In this manuscript, we show that RS can be used to determine whether plant material is hemp or cannabis with 100% accuracy. We also demonstrate that RS can be used to probe the content of THCA in the analyzed samples. These findings suggest that a hand-held Raman spectrometer can be an ideal tool for police officers and hemp breeders to enable highly accurate diagnostics of THCA content in plants.

Cannabis is a generic term that is used to denote hemp plants (Cannabis sativa) that produce delta-9-tetrahydrocannabinolic acid (THCA) in amounts higher than industrial hemp.