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In addition to the nutritional and therapeutic benefits, Argan oil is praised for its unique bio-ecological and botanic interest. It has been used for centuries to treat cardiovascular issues, diabetes, and skin infections, as well as for its anti-inflammatory and antiproliferative properties. Argan oil is widely commercialized as a result of these characteristics. However, falsifiers deliberately blend Argan oil with cheaper vegetable oils to make economic profits. This reduces the quality and might result in health issues for consumers. Analytical techniques that are rapid, precise, and accurate are employed to monitor its quality, safety, and authenticity. This review provides a comprehensive overview of studies on the quality assessment of Moroccan Argan oil using both untargeted and targeted approaches. To extract relevant information on quality and adulteration, the analytical data are coupled with chemometric techniques.

Herbal products for smoking containing cannabidiol (CBD) are available as "low-tetrahydrocannabinol cannabis products" in most EU countries. In Belgium, Δ9-tetrahydrocannabinol (THC) content of these products must be less than 0.2% w/w, which is also the limit for agricultural hemp. For agricultural hemp, the official and only valid method for European regulators is gas-chromatography coupled to flame ionization detector (GC-FID). There is no such method, for smoking products. Many of these herbal for smoking products are analyzed as part of their quality control and have certificate of analysis. During surveillance by official labs, discrepancies were seen between the official results and the certificate of analysis. In this study, a GC-FID method based on the European method and an ultra-high-performance liquid chromatography coupled to diode array detection (UHPLC-DAD) method were validated and applied for samples analysis in order to investigate these discrepancies. The GC-FID method shows better results for the validation parameters; notably, it has β-expectation tolerance limits within 10% with a β value of 95% while the validated UHPLC-DAD method has β-expectation tolerance limits within 15% with a β value of 90%. Furthermore, the other parameters evaluated are generally better with the GC-FID method. The statistic t test shows that the difference between both methods was significantly different for total-THC, but not significantly different for the total-CBD. The authors state that, as for agricultural hemp, the GC-FID method is to be preferred for the analysis of THC and CBD in products for smoking.

A classical quantitative analysis in liquid chromatography is performed using either a one-point calibration or a calibration line, prepared using a reference standard of the compound(s) of interest. However, in some cases, adequate reference standards may be very expensive, rare to obtain, or have limited shelf-life properties. Also, in herbal matrices, multiple compounds could be necessary to be quantified, needing a whole series of different (related) reference standards. In these cases, the use of relative response (sometimes called relative correction factors) factors (RRFs) towards reference standards, different of the compound to be quantified, gained attraction. This study performed a comparison of the use of RRFs and linear relative response factor models (LRRFM) for the quantification of targeted low-dosed compounds using an alternative standard, since it is known that classical RRFs often fail in lower concentration ranges. For this purpose, the determination of the total Δ9-tetrahydrocannabinol (Δ9-THC + Δ9-THC-A) content in dried cannabis flowers, using UHPLC-DAD, was used as a case study. A chromatographic method was implemented and validated, and the use of classical calibration lines, classical RRF, and the LRRFM was applied and compared, with special focus on the concentration around 0.2% (w/w) total Δ9-THC, the legal limit (in most European countries) in these products. Results showed that the newly presented and validated LRRFM approach outperformed the classical RRFs, especially in the low-concentration ranges and that concentrations obtained with the LRRFM were in accordance with the interpolation results obtained with a calibration line.

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.

Quality control of CBD oils on the Belgium market showed that the CBD content not always corresponds to the label claim. There is a pressing need to develop new analytical methods specifically developed to the assay of such oily samples. Analytical issues are, however, encountered for routine analyses due to the matrix complexity, high cost of cannabinoid standards and low Δ9-THC concentrations. An oily matrix could cause technical damages to analytical instruments and reduce the lifetime of the chromatographic columns. This paper proposes a procedure combining a sample cleanup by QuEChERS, removing the oily matrix, followed by a validated MRM GC-MS/MS method for the routine analysis of CBD oil samples. Eighteen CBD samples were selected on the Belgium market for analysis. This method allows the quantification of CBD, the legality check for the Δ9-THC content by a CBN standard and the screening of seven other cannabinoids namely CBN, CBDV, CBT, CBC, Δ8-THC, THCV and CBG. The method was validated at three concentration levels (0.5–1–2% (w/v)) for CBD and (0.05–0.1–0.2% (w/v)) for CBN. The detection limits for CBT, CBD, CBC, Δ8-THC, CBN and for the other cannabinoids of interest, were 10 and 14 ng/mL respectively. The accuracy profile values for CBD and CBN showed that the β-expectation tolerance intervals did not exceed the acceptance limits of ± 20%, meaning that 90% of future measurements will be included within this error range.

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., info:eu-repo/semantics/published

The threats of substandard and falsified (SF) antimicrobials, posed to public health, include serious adverse drug effects, treatment failures and even development of antimicrobial resistance. Next to these issues, it has no doubt that efficient methods for on-site screening are required to avoid that SF antimicrobials reach the patient or even infiltrate the legal supply chain. This study aims to develop a fast on-site screening method for SF antimicrobials using spectroscopic techniques (mid infrared, benchtop near infrared, portable near infrared and Raman spectroscopy) combined with chemometrics. 58 real-life illegal antimicrobials (claiming 18 different antimicrobials and one beta-lactamase inhibitor) confiscated by the Belgian Federal Agency for Medicines and Health Products (FAMHP) and 14 genuine antimicrobials were analyzed and used to build and validate models.Two types of models were developed and validated using supervised chemometric tools. One was used for the identification of the active pharmaceutical ingredients (APIs) by applying partial least squares-discriminant analysis (PLS-DA) and another one was used for the detection of non-compliant (overdosed or underdosed) samples by applying PLS-DA, k-nearest neighbors (k-NN) and soft independent modelling by class analogy (SIMCA). The best model capable of identifying amoxicillin and clavulanic acid (co-amoxiclav), azithromycin, co-trimoxazole and amoxicillin was based on the mid-infrared spectra with a correct classification rate (ccr) of 100%. The optimal model capable of detecting non-compliant samples within the combined group of amoxicillin and co-amoxiclav via SIMCA showed a ccr for the test set of 88% (7/8) using mid infrared or benchtop near infrared spectroscopy. The best model for detecting non-compliant samples within the group of amoxicillin via SIMCA was obtained using mid-infrared or Raman spectra, resulting in a ccr of 80% for the test set (4/5) and a ccr for calibration of 100%. For the group of co-amoxiclav, the optimal models showed a ccr of 100% for the detection of non-compliant samples by applying mid-infrared, benchtop near infrared or portable near infrared spectroscopy. Taken together, the obtained models, hyphenating spectroscopic techniques and chemometrics, enable to easily identify suspected SF antimicrobials and to differentiate non-compliant samples from compliant ones., info:eu-repo/semantics/published

In the quality control of medicines and the fight against the phenomenon of poor quality medicines, there is an urgent need for rapid and broad spectrum methods for screening these types of medicines. In the present work, we have used near infrared spectroscopy combined with multivariate data analysis to develop chemometric models for the classification and quantification of metronidazole in Burkina Faso pharmaceutical formulations. For this purpose, drug samples were collected in drugstores located in different Burkina Faso border zones. Four product classes were defined based on the national nomenclature: 3 classes for the generic drugs (C1, C3, and C4) and one class for the reference (C2) drugs. The exploratory analysis using PCA identified two clusters of drugs within class C1. Discrimination was confirmed by the developed and optimised DD-SIMCA model, with only one target class. The quality control of the samples from product class C1 was proven to be very satisfactory with specificities and sensitivities of 100%. The quantification models developed with the PLS-R method were successfully applied for the determination of the active ingredient content in the samples, with acceptable relative bias between 0.15 and 12.7 % with respect to the dose determined by the HPLC method. The RMSEC was estimated at 13.57 (R2, 0.9937), the RMSECV at 18.07 (R2, 0.9888) and the RMSEP at 13.69 (R2, 0.9941).The models developed and the results obtained are promising for routine quality control of similar formulations of metronidazole.

Ethoxyquin (EQ) is an antioxidant widely used in the food industry. Some concerns for human health have been reported since its utilization in animal feed may lead to residues in human food such as salmon samples. This work aimed to investigate the electrochemical behavior of EQ and its major oxidation products namely a dimer of EQ (EQDM) and ethoxyquin quinone imine (EQI) by cyclic voltammetry (CV) at a carbon screen printed electrode (cSPE). The stability of these products and their reactivity against glutathione (GSH) were also studied. Oxidized products and thiol adducts were identified by a microelectrolysis of an EQ solution onto a cSPE in the absence and in the presence of GSH. The products were analyzed off-line, by liquid chromatography coupled to a mass spectrometer (LC-MS). One of the generated product (EQI) was shown to be highly reactive towards GSH. Based on the redox pattern of EQ, a flow injection analysis with a dual cSPE was developed in order to detect in a rapid manner EQ in salmon samples. Since matrix effects were observed, matrix-matched calibration curves with spiked samples were built. A linear response was obtained between 20–100 μM and a limit of detection (LOD) of 7.5 μM (8.2 mg/kg of salmon). Trueness was assessed with recovery assays at three levels of concentration. The recovery was close to 100 %. Precision was determined as RSD (%) with values lower than 6 % in all cases.

Abundant literature has been devoted to coffee beans (green or roasted) chemical description but relatively few studies have been devoted to coffee leaves. Given the fact that coffee leaves are used for food and medicinal consumption, it was of interest to develop a rapid screening method in order to identify coffee leaves taxa. Investigation by Fourier - Transform near infrared spectroscopy (FT-NIRS) was performed on nine Coffea taxa leaves harvested over one year in a tropical greenhouse of the Botanic Garden Meise (Belgium). The only process after leaves harvesting was an effective drying and a homogeneous leaves grinding. FT-NIRS with SIMCA analysis allowed to discriminate the spectral profiles across taxon, aging stage (mature and senescence coffee leaves) and harvest period. This study showed that it was possible (i) to classify the different taxa, (ii) to identify their aging stage and (iii) to identify the harvest period for the mature stage with a correct classification rate of 99%, 100% and 90%, respectively.