Aerial parts containing cannabidiol can be purchased in a legal way but cannabis used as recreational drug is illegal in most European countries. Δ9‐tetrahydrocannabinol is one of the main cannabinoids responsible for the psychotropic effect. European Union countries and Switzerland authorize a concentration of THC of 0.2 % and 1.0 % w/w, respectively, for smoking products and industrial hemp. Public health inspectors and law enforcement officers need to check the legality of samples. Therefore there is a need for innovative approaches, allowing quality control of these products in an easy way and preferably on site. In many countries, cultivation of industrial hemp is permitted if the THC content does not exceed 0.2 % w/w. A portable equipment could be a useful measuring tool for farmers to check for the THC content at regular time. In this work, 189 samples were analysed with a benchtop and a handheld NIR device in order to create two classification methods according to European and Swiss laws. All samples were also analysed by GC‐FID to determine their THC concentration. Supervised analysis was applied in order to establish the best model. For the first classification, the accuracy was 91% for the test set with the benchtop data and 93 % for the test set with the handheld data. For the second classification, the accuracies were respectively 91 % and 95 %. The obtained models, hyphenating spectroscopic techniques and chemometrics, enable to discriminate legal and illegal cannabis samples according to European and Swiss laws.
Coffee is a beverage widely consumed in the world. The coffee species most commercialized worldwide are Arabica (Coffea arabica) and Robusta (Coffea canephora). Roasted coffee beans are the most used, but coffee leaves are also consumed as infusion in several countries for traditional medicinal purposes. They contain several interesting phenolic antioxidant compounds mainly belonging to chlorogenic acids (CGAs). In the present work, a liquid chromatography-electrochemical detection (LC-EC) method was developed for the determination of three main chlorogenic acid isomers, namely 3-, 4-, and 5-caffeoylquinic acids (CQA), in coffee leaves aqueous extracts. Samples from eight coffee species, namely; Coffea arabica, Coffea canephora, Coffea liberica, Coffea humilis, Coffea mannii, Coffea charrieriana, Coffea anthonyi, and Coffea liberica var. liberica, were grown and collected in tropical greenhouses. Linearity of the calibration graphs was observed in the range from the limit of quantification to 1.0 × 10−5 M, with R2 equal to 99.9% in all cases. High sensitivity was achieved with a limit of detection of 1.0 × 10−8 M for 3-CQA and 5-CQA (i.e., 3.5 µg/L) and 2.0 × 10−8 M for 4-CQA (i.e., 7.1 µg/L). The chromatographic profile of the samples harvested for each Coffea species was studied comparatively. Obtained raw data were pretreated for baseline variations and shifts in retention times between the chromatographic profiles. Principal Component Analysis (PCA) was applied to the pretreated data. According to the results, three clusters of Coffea species were found. In the water sample extracts, 5-CQA appeared to be the major isomer, and some species contained a very low amount of CQAs. Fluctuations were observed depending on the Coffea species and harvesting period. Significant differences between January and July were noticed regarding CQAs content. The species with the best CQAs/caffeine ratio was identified. The LC-EC data were validated by liquid chromatography-high resolution mass spectrometry (LC-HRMS).
More and more events, such as the summer music festivals, are considering the possibilities for implementing on‐site testing of psychoactive drugs in the context of prevention and harm reduction. Although the on‐site identification is already implemented by plenty of drug checking services, the required rapid quantitative dosing of the composition of illicit substances is still a missing aspect for a successful harm reduction strategy at events. In this paper, an approach is presented to identify white powders as amphetamine, cocaine, ketamine or others and to estimate the purity of the amphetamine, cocaine and ketamine samples using spectroscopic techniques hyphenated with partial least squares (PLS) modelling. For identification purposes, it was observed that mid‐infrared spectroscopy hyphenated with PLS‐discriminant analysis allowed the distinction between amphetamine, cocaine, ketamine and other samples and this with a correct classification rate of 93.1% for an external test set. For quantitative estimation, near‐infrared spectroscopy was more performant and allowed the estimation of the dosage/purity of the amphetamine, cocaine and ketamine samples with an error of more or less 10% w/w. An easily applicable, practical and cost‐effective approach for on‐site characterisation of the majority of the psychoactive samples encountered in Belgian nightlife settings based on IR spectroscopy was proposed.
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