Monitoring of cannabinoids in hemp flours by MicroNIR/Chemometrics

Fragmentation and Isomerization Pathways of Natural and Synthetic Cannabinoids Studied via Higher Collisional Energy Dissociation Profiles

Cannabinoid molecules are the family of molecules that bind to the cannabinoid receptors (CB1 and CB2) of the human body and cause changes in numerous biological functions including motor coordination, emotion, and pain reception. Cannabinoids occur either naturally in the Cannabis Sativa plant or can be produced synthetically in the laboratory. The need for accurate analytical methods for analyzing cannabinoid molecules is of considerable current importance due to demands for detecting illegal cannabinoids and for monitoring the manufacture of popular, non-illegal cannabinoid products. Mass spectrometry has been shown to be an optimum technique for identifying cannabinoids. In this work, we perform Higher Collisional Dissociation (HCD) mass spectrometric measurements on an Orbitrap Fusion Tribrid Mass Spectrometer to measure the collision-energy-dependent molecular fragmentation pathways of a group of key cannabinoids and their metabolites (cannabidiol, Δ9-Tetrahydrocannabinol, 11-Hydroxy-Δ9-tetrahydrocannabinol, 11-nor-9-Carboxy-Δ9-tetrahydrocannabinol, cannabidiolic acid, tetrahydrocannabinolic acid), along with two synthetic cannabinoids (JWH-018 and MDMB-FUBINACA). This is the first time that cannabinoid molecules have been studied using energy-resolved HCD methods. We identified a number of common, primary fragmentation pathways, including loss of water, loss of other small neutral molecule units (e.g., butene), and rupture of the central C-C bond that links the aromatic and alkyl ring groups. Quantum chemical calculations are presented to provide insights into preferred protonation sites and to characterize isomerization of protonated open-ring cannabinoids (e.g., [CBDA + H]+) into closed-ring analogues (e.g., [THCA + H]+). A key result to emerge from our study is that energy-resolved HCD measurements are particularly valuable in identifying isomerization, since the isobaric pairs of molecular ions studied here (e.g., [CBDA + H]+ and [THCA + H]+) are associated with identical HCD profiles indicating that isomerization of one structure into the other has occurred during the electrospray-mass spectrometry process. This is an important result as it will have general applicability to other tautomeric ions and thus demonstrates the application of energy-resolved HCD as a tool for identifying tautomerization proclivity.

Chromatographic and Spectroscopic Analyses of Cannabinoids: A Narrative Review Focused on Cannabis Herbs and Oily Products

Cannabis sativa L. is cultivated nowadays for agricultural, industrial, and medicinal applications and also for recreational use. The latter is due to the presence of delta-9-tetrahydrocannabinol, a psychoactive substance. Recreational cannabis policies vary between different countries, which has led to the lack of a clearly defined legal context for cannabis and also a diversity of products derived from or containing cannabis on the (il)legal market. These cannabis-derived products have regained attention, notably because of their cannabinoid content. This review aims to assess and present analytical methods developed to analyze phytocannabinoids with spectroscopic and chromatographic techniques in specific cannabis matrices: herbs and oily products. Published papers from 2018-November 2024 were searched for with precise criteria, analyzed, and summarized. In the studies, liquid and gas chromatographic techniques (>70% reviewed papers) were the most used and have been widely applied using similar methods, and most papers were focused on cannabis herbs (>75%). Techniques were also compared and future challenges were identified. A comparison of different specificities of chromatographic and spectroscopic techniques discussed in this current review has also been established and summarized.

Comparative chemometric modeling of fresh and dry cannabis inflorescences using FT-NIR spectroscopy: Quantification and classification insights

INTRODUCTION

Cannabis sativa L. inflorescences are rich in cannabinoids and terpenes. Traditional chemical analysis methods for cannabinoids and terpenes, such as liquid and gas chromatography (using UV or MS detectors), are expensive and time-consuming.

OBJECTIVES

This study explores the use of Fourier transform near-infrared (FT-NIR) spectroscopy combined with chemometric approaches for classifying cannabis chemovars and predicting cannabinoid and terpene concentrations for the first time in freshly harvested (wet) cannabis inflorescence. The study also compares the performance of FT-NIR spectroscopy on wet versus dry cannabis inflorescences.

MATERIALS AND METHODS

Spectral data from 187 samples across seven cannabis chemovars were analyzed using partial least squares-discriminant analysis (PLS-DA) and partial least squares-regression (PLS-R) models.

RESULTS

The PLS-DA models effectively classified chemovars and major classes using only two latent variables (LVs) with minimal overfitting risk, with sensitivity, specificity, and accuracy values approaching 1. Despite the high water content in wet cannabis inflorescence, the PLS-R models demonstrated good to excellent predictive capabilities for nine cannabinoids and eight terpenes using FT-NIR spectra for the first time, achieving cross-validation and prediction R-squared values greater than 0.7, ratio of performance to interquartile range (RPIQ) exceeding 2, and a RMSECV/RMSEC ratio below 1.24. However, the low-cannabidiolic acid submodel and (-)-Δ9-trans-tetrahydrocannabinol model showed poor predictive performance. Some cannabinoid and terpene prediction models in wet cannabis inflorescence exhibited lower predictive capabilities compared with previously published models for dry cannabis inflorescence.

CONCLUSIONS

These findings suggest that FT-NIR spectroscopy can be a viable rapid on-site analytical tool for growers during the inflorescence flowering stage.

Analytical Chemistry Strategies in the Use of Miniaturised NIR Instruments: An Overview

Miniaturized NIR instruments have been increasingly used in the last years, and they have become useful tools for many applications on a broad variety of samples. This review focuses on miniaturized NIR instruments from an analytical point of view, to give an overview of the analytical strategies used in order to help the reader to set up their own analytical methods, from the sampling to the data analysis. It highlights the uses of these instruments, providing a critical discussion including current and future trends.

Non-Destructive Near-Infrared Technology for Efficient Cannabinoid Analysis in Cannabis Inflorescences

In the evolving field of cannabis research, scholars are exploring innovative methods to quantify cannabinoids rapidly and non-destructively. This study evaluates the effectiveness of a hand-held near-infrared (NIR) device for quantifying total cannabidiol (total CBD), total delta-9-tetrahydrocannabinol (total THC), and total cannabigerol (total CBG) in whole cannabis inflorescences. Employing pre-processing techniques, including standard normal variate (SNV) and Savitzky-Golay (SG) smoothing, we aim to optimize the portable NIR technology for rapid and non-destructive cannabinoid analysis. A partial least-squares regression (PLSR) model was utilized to predict cannabinoid concentration based on NIR spectra. The results indicated that SNV pre-processing exhibited superior performance in predicting total CBD concentration, yielding the lowest root mean square error of prediction (RMSEP) of 2.228 and the highest coefficient of determination for prediction (R2P) of 0.792. The ratio of performance to deviation (RPD) for total CBD was highest (2.195) with SNV. In contrast, raw data exhibited the least accurate predictions for total THC, with an R2P of 0.812, an RPD of 2.306, and an RMSEP of 1.651. Notably, total CBG prediction showed unique characteristics, with raw data yielding the highest R2P of 0.806. SNV pre-processing emerges as a robust method for precise total CBD quantification, offering valuable insights into the optimization of a hand-held NIR device for the rapid and non-destructive analysis of cannabinoid in whole inflorescence samples. These findings contribute to ongoing efforts in developing portable and efficient technologies for cannabinoid analysis, addressing the increasing demand for quick and accurate assessment methods in cannabis cultivation, pharmaceuticals, and regulatory compliance.

Portable NIR spectroscopy: the route to green analytical chemistry

There is a growing interest for cost-effective and nondestructive analytical techniques in both research and application fields. The growing approach by near-infrared spectroscopy (NIRs) pushes to develop handheld devices devoted to be easily applied for in situ determinations. Consequently, portable NIR spectrometers actually result definitively recognized as powerful instruments, able to perform nondestructive, online, or in situ analyses, and useful tools characterized by increasingly smaller size, lower cost, higher robustness, easy-to-use by operator, portable and with ergonomic profile. Chemometrics play a fundamental role to obtain useful and meaningful results from NIR spectra. In this review, portable NIRs applications, published in the period 2019-2022, have been selected to indicate starting references. These publications have been chosen among the many examples of the most recent applications to demonstrate the potential of this analytical approach which, not having the need for extraction processes or any other pre-treatment of the sample under examination, can be considered the "true green analytical chemistry" which allows the analysis where the sample to be characterized is located. In the case of industrial processes or plant or animal samples, it is even possible to follow the variation or evolution of fundamental parameters over time. Publications of specific applications in this field continuously appear in the literature, often in unfamiliar journal or in dedicated special issues. This review aims to give starting references, sometimes not easy to be found.

Novel fluorescence spectroscopy method coupled with N-PLS-R and PLS-DA models for the quantification of cannabinoids and the classification of cannabis cultivars

INTRODUCTION

Cannabis sativa L. inflorescences are rich in secondary metabolites, particularly cannabinoids. The most common techniques for elucidating cannabinoid composition are expensive technologies, such as high-pressure liquid chromatography (HPLC).

OBJECTIVES

We aimed to develop and evaluate the performance of a novel fluorescence spectroscopy-based method coupled with N-way partial least squares regression (N-PLS-R) and partial least squares discriminant analysis (PLS-DA) models to replace the expensive chromatographic methods for preharvest cannabinoid quantification.

METHODOLOGY

Fresh medicinal cannabis inflorescences were collected and ethanol extracts were prepared. Their excitation-emission spectra were measured using fluorescence spectroscopy and their cannabinoid contents were determined by HPLC-PDA. Subsequently, N-PLS-R and PLS-DA models were applied to the excitation-emission matrices (EEMs) for cannabinoid concentration prediction and cultivar classification, respectively.

RESULTS

The N-PLS-R model was based on a set of EEMs (n = 82) and provided good to excellent quantification of (-)-Δ9-trans-tetrahydrocannabinolic acid, cannabidiolic acid, cannabigerolic acid, cannabichromenic acid, and (-)-Δ9-trans-tetrahydrocannabinol (R² _CV and R² _pred  > 0.75; RPD > 2.3 and RPIQ > 3.5; RMSECV/RMSEC ratio < 1.4). The PLS-DA model enabled a clear distinction between the four major classes studied (sensitivity, specificity, and accuracy of the prediction sets were all ≥0.9).

CONCLUSIONS

The fluorescence spectral region (excitation 220-400 nm, emission 280-550 nm) harbors sufficient information for accurate prediction of cannabinoid contents and accurate classification using a relatively small data set.

Microencapsulation by a Spray Drying Approach to Produce Innovative Probiotics-Based Products Extending the Shelf-Life in Non-Refrigerated Conditions

Recently, there has been a growing interest in producing functional foods containing encapsulated probiotic bacteria due to their positive effects on human health. According to their perceived health benefits, probiotics have been incorporated into a range of dairy products, but the current major challenge is to market new, multicomponent probiotic foods and supplements. Nevertheless, only a few products containing encapsulated probiotic cells can be found as non-refrigerated products. In this work, spray drying technology was investigated in order to produce an innovative nutraceutical formulation based on lactic acid bacteria (LAB), and was able to ensure a good storage stability of probiotics (no less than 109 CFU/cps) in non-refrigerated conditions. Probiotic-loaded microparticles from spray drying experiments were produced under different conditions and compared by thermogravimetric analysis (TGA), scanning electron microscopy (SEM), and the enumeration of the number of viable cells in order to identify the formulation exhibiting the most promising characteristics. Results from the dissolution test revealed that the optimized formulation provides a suitable amount of living cells after digestion of microparticles stored for 12 months at room temperature and confirmed that the microencapsulation process by spray drying ensures a good protection of probiotics for nutraceutical purposes.

On-Line Thermally Induced Evolved Gas Analysis: An Update-Part 2: EGA-FTIR

The on-line thermally induced evolved gas analysis (OLTI-EGA) is widely applied in many different fields. Aimed to update the applications, our group has systematically collected and published examples of EGA characterizations. Following the recently published review on EGA-MS applications, this second part reviews the latest applications of Evolved Gas Analysis performed by on-line coupling heating devices to infrared spectrometers (EGA-FTIR). The selected 2019, 2020, 2021 and early 2022 references are collected and briefly described in this review; these are useful to help researchers to easily find applications that are sometimes difficult to locate.

Use of near-infrared spectroscopy for the classification of medicinal cannabis cultivars and the prediction of their cannabinoid and terpene contents

Cannabis sativa L. is used to treat a wide variety of medical conditions, in light of its beneficial pharmacological properties of its cannabinoids and terpenes. At present, the quantitative chemical analysis of these active compounds is achieved through the use of laborious, expensive, and time-consuming technologies, such as high-pressure liquid-chromatography- photodiode arrays, mass spectrometer detectors (HPLC-PDA or MS), or gas chromatography-mass spectroscopy (GC-MS). Hence, we aimed to develop a simple, accurate, fast, and cheap technique for the quantification of major cannabinoids and terpenes using Fourier transform near infra-red spectroscopy (FT-NIRS). FT-NIRS was coupled with multivariate classification and regression models, namely partial least square-discriminant analysis (PLS-DA) and partial least squares regression (PLS-R) models. The PLS-DA model yielded an absolute major class separation (high-THC, high-CBD, hybrid, and high-CBG) and perfect class prediction. Using only three latent variables (LVs), the cross-validation and prediction model errors indicated a low probability of over-fitting the data. In addition, the PLS-DA model enabled the classification of chemovars with genetic-chemical similarities. The classification of high-THCA chemovars was more sensitive and more specific than the classifications of the remaining chemovars. The prediction of cannabinoid and terpene concentrations by PLS-R yielded 11 robust models with high predictive capabilities (R2CV and R2pred > 0.8, RPD >2.5 and RPIQ >3, RMSECV/RMSEC ratio <1.2) and additional 15 models whose performance was acceptable for initial screening purposes (R2CV > 0.7 and R2pred < 0.8, RPD >2 and RPIQ <3, 1.2 < RMSECV/RMSEC ratio <2). Our results confirm that there is sufficient information in the FT-NIRS to develop cannabinoid and terpene prediction models and major-cultivar classification models.

On-site forensic analysis of colored seized materials: Detection of brown heroin and MDMA-tablets by a portable NIR spectrometer

The increasing workload for forensic laboratories and the expanding complexity of the drug market necessitates efficient approaches to detect drugs of abuse. Identification directly at the scene of crime enables investigative forces to make rapid decisions. Additionally, on-site identification of the material also leads to considerable efficiency and cost benefits. As such, paperwork, transportation, and time-consuming analysis in a laboratory may be avoided. Near-infrared (NIR) spectroscopy is an analysis technique suitable for rapid drug testing using portable equipment. A possible limitation of spectroscopic analysis concerns the complexity of seized materials. NIR measurements represent composite spectra for mixtures and diagnostic spectral features can be obscured by excipients such as colorants. Herein, a NIR-based (1300-2600 nm) detection of heroin and MDMA in colored casework (i.e., brown powders and ecstasy tablets) using a portable analyzer is presented. The application includes a multistage data analysis model based on the net analyte signal (NAS) approach. This identification model was specifically designed for mixture analysis and requires a limited set of pure reference spectra only. Consequently, model calibration efforts are reduced to a minimum. A total of 549 forensic samples was tested comprising brown heroine samples and a variety of colored tablets with different active ingredients. This investigation led to a >99% true negative and >93% true positive rate for heroin and MDMA. These results show that accurate on-site detection in colored casework is possible using NIR spectroscopy combined with an efficient data analysis model. These findings may eventually help in the transition of routine forensic laboratories from laboratory-based techniques to portable equipment operated on scene.

NMR Spectroscopy Applied to the Metabolic Analysis of Natural Extracts of Cannabis sativa

Cannabis sativa is a herbaceous multiple-use species commonly employed to produce fiber, oil, and medicine. It is now becoming popular for the high nutritional properties of its seed oil and for the pharmacological activity of its cannabinoid fraction in inflorescences. The present study aims to apply nuclear magnetic resonance (NMR) spectroscopy to provide useful qualitative and quantitative information on the chemical composition of seed and flower Cannabis extracts obtained by ultra-sound-assisted extraction, and to evaluate NMR as an alternative to the official procedure for the quantification of cannabinoids. The estimation of the optimal ω-6/ω-3 ratio from the 1H NMR spectrum for the seed extracts of the Futura 75 variety and the quantitative results from the 1H and 13C NMR spectra for the inflorescence extracts of the Tiborszallasi and Kompolti varieties demonstrate that NMR technology represents a good alternative to classical chromatography, supplying sufficiently precise, sensitive, rapid, and informative data without any sample pre-treatment. In addition, different extraction procedures were tested and evaluated to compare the elaboration of spectral data with the principal component analysis (PCA) statistical method and the quantitative NMR results: the extracts obtained with higher polarity solvents (acetone or ethanol) were poor in psychotropic agents (THC < LOD) but had an appreciable percentage of both cannabinoids and triacylgliceroles (TAGs). These bioactive-rich extracts could be used in the food and pharmaceutical industries, opening new pathways for the production of functional foods and supplements.

Chemometrics in forensic science: approaches and applications

Forensic investigations are often reliant on physical evidence to reconstruct events surrounding a crime. However, there remains a need for more objective approaches to evidential interpretation, along with rigorously validated procedures for handling, storage and analysis. Chemometrics has been recognised as a powerful tool within forensic science for interpretation and optimisation of analytical procedures. However, careful consideration must be given to factors such as sampling, validation and underpinning study design. This tutorial review aims to provide an accessible overview of chemometric methods within the context of forensic science. The review begins with an overview of selected chemometric techniques, followed by a broad review of studies demonstrating the utility of chemometrics across various forensic disciplines. The tutorial review ends with the discussion of the challenges and emerging trends in this rapidly growing field.

Emerging challenges in the extraction, analysis and bioanalysis of cannabidiol and related compounds

Cannabidiol (CBD) is a bioactive terpenophenolic compound isolated from Cannabis sativa L. It is known to possess several properties of pharmaceutical interest, such as antioxidant, anti-inflammatory, anti-microbial, neuroprotective and anti-convulsant, being it active as a multi-target compound. From a therapeutic point of view, CBD is most commonly used for seizure disorder in children. CBD is present in both medical and fiber-type C. sativa plants, but, unlike Δ⁹-tetrahydrocannabinol (THC), it is a non-psychoactive compound. Non-psychoactive or fiber-type C. sativa (also known as hemp) differs from the medical one, since it contains only low levels of THC and high levels of CBD and related non-psychoactive cannabinoids. In addition to medical Cannabis, which is used for many different therapeutic purposes, a great expansion of the market of hemp plant material and related products has been observed in recent years, due to its usage in many fields, including food, cosmetics and electronic cigarettes liquids (commonly known as e-liquids). In this view, this work is focused on recent advances on sample preparation strategies and analytical methods for the chemical analysis of CBD and related compounds in both C. sativa plant material, its derived products and biological samples. Since sample preparation is considered to be a crucial step in the development of reliable analytical methods for the determination of natural compounds in complex matrices, different extraction methods are discussed. As regards the analysis of CBD and related compounds, the application of both separation and non-separation methods is discussed in detail. The advantages, disadvantages and applicability of the different methodologies currently available are evaluated. The scientific interest in the development of portable devices for the reliable analysis of CBD in vegetable and biological samples is also highlighted.