Logo image
Back
Using a global diversity panel of Cannabis sativa L. to develop a near InfraRed-based chemometric application for cannabinoid quantification
Journal article   Open access   Peer reviewed

Using a global diversity panel of Cannabis sativa L. to develop a near InfraRed-based chemometric application for cannabinoid quantification

Francine Gloerfelt-Tarp, Amitha K Hewavitharana, Jos Mieog, William M Palmer, Felicity Fraser, Omid Ansari and Tobias Kretzschmar
Scientific reports, Vol.13, 2253
08/02/2023
DOI: https://doi.org/10.1038/s41598-023-29148-0
PMID: 36755037
pdf
Using a global diversity panel of Cannabis sativa L. to develop a near InfraRed-based chemometric application for cannabinoid quantification2.50 MBDownloadView
Published (Version of record)CC BY V4.0,  Open Access
url
Using a global diversity panel of Cannabis sativa L. to develop a near InfraRed-based chemometric application for cannabinoid quantificationView
Published (Version of record)CC BY V4.0,  Open

Related links

Metrics

217 File views/ downloads
63 Record Views
14 Times Cited - Web of Science

UN Sustainable Development Goals (SDGs)

This output has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

Source: InCites

Abstract

Cannabinoids - analysis Cannabis - chemistry Chemometrics Chromatography, High Pressure Liquid - methods Medical Marijuana
C. sativa has gained renewed interest as a cash crop for food, fibre and medicinal markets. Irrespective of the final product, rigorous quantitative testing for cannabinoids, the regulated biologically active constituents of C. sativa, is a legal prerequisite across the supply chains. Currently, the medicinal cannabis and industrial hemp industries depend on costly chromatographic analysis for cannabinoid quantification, limiting production, research and development. Combined with chemometrics, Near-InfraRed spectroscopy (NIRS) has potential as a rapid, accurate and economical alternative method for cannabinoid analysis. Using chromatographic data on 12 therapeutically relevant cannabinoids together with spectral output from a diffuse reflectance NIRS device, predictive chemometric models were built for major and minor cannabinoids using dried, homogenised C. sativa inflorescences from a diverse panel of 84 accessions. Coefficients of determination (r2) of the validation models for 10 of the 12 cannabinoids ranged from 0.8 to 0.95, with models for major cannabinoids showing best performance. NIRS was able to discriminate between neutral and acidic forms of cannabinoids as well as between C3-alkyl and C5-alkyl cannabinoids. The results show that NIRS, when used in conjunction with chemometrics, is a promising method to quantify cannabinoids in raw materials with good predictive results.

Details

Logo image