2026/05/15 by Mostafa A. Elhendawy, Adam M. Gilmore, Mohamed M. Radwan +8 · 1 voice
Chemistry · Medicine · Pharmacology, Toxicology and Pharmaceutics · #Cannabis and Cannabinoid Research #Forensic Toxicology and Drug Analysis #Spectroscopy and Chemometric Analyses
paper · doi:10.1177/25785125261449640
openalex publication_date 2026/05/15 · openalex created_date 2026/05/17 · openalex updated_date 2026/07/22
Background: Cannabis plants ( Cannabis sativa ) contain a diverse group of terpenophenolic compounds known as phytocannabinoids, with 131 cannabinoids identified to date. Rapid and low-cost analytical approaches capable of quantifying both major and minor cannabinoids are increasingly important for research, quality control, and regulatory applications. This study evaluates the patented Absorbance–Transmittance Excitation–Emission Matrix (A-TEEM™) spectroscopic technique as a fast and reliable alternative to conventional chromatographic methods. A-TEEM integrates ultraviolet–visible absorbance and fluorescence measurements while correcting for absorbance-dependent inner-filter effects, enabling linear relationships between fluorescence intensity and analyte concentration. The primary objective was to calibrate and validate machine learning models using A-TEEM data for cannabinoid quantification, benchmarked against a validated high-performance liquid chromatography–photodiode array (HPLC-PDA) reference method. Materials and Methods: A total of 49 dry cannabis flower extracts were analyzed using the A-TEEM technique to quantify 14 cannabinoids. Spectral data generated by A-TEEM were directly compared with concentration data obtained from an established and validated HPLC-PDA method. Extreme gradient boosting regression models were developed using HPLC-PDA results as reference values to predict cannabinoid concentrations from A-TEEM spectral data and to evaluate quantitative performance. Results: The A-TEEM method demonstrated rapid, robust, and sensitive quantification of all 14 target cannabinoids. Model performance metrics, including coefficients of determination ( R 2 ) and limits of detection (LOD) and limits of quantification (LOQ), are scaled proportionally with the maximum cannabinoid concentrations present in the samples. For major cannabinoids exceeding 0.35% concentration, the mean combined cross-validation and validation R 2 reached 0.994 ± 0.005, with mean LOD and LOQ values of 0.0146% and 0.0442%, respectively. Cannabinoids present between 0.35% and 0.1% showed mean LOD/LOQ values of 0.00278% and 0.00842%, while minor cannabinoids below 0.1% exhibited even lower LOD/LOQ values of 0.0004% and 0.00128%, respectively. In addition, A-TEEM concentration profiles enabled clear qualitative and quantitative differentiation of three cannabis chemovars: tetrahydrocannabinol (THC)-dominant, cannabidiol (CBD)-dominant, and THC-CBD-intermediate hybrids. Conclusions: The A-TEEM technique provides a sensitive, rapid, and cost-effective approach for the qualitative and quantitative determination of both major and minor cannabinoids in solution. Its analytical performance is comparable to that of the reference HPLC-PDA method while offering substantial advantages in speed, simplicity, and suitability for high-throughput analysis.