Planta Med 2019; 85(18): 1436
DOI: 10.1055/s-0039-3399760
Main Congress Poster
Poster Session 1
© Georg Thieme Verlag KG Stuttgart · New York

Integrated approach for the extraction and quality assessment of fibre-type Cannabis sativa L. based on UPLC-PDA and HPTLC

PS Tzimas
,
EA Petrakis
,
A Angelis
,
M Halabalaki
,
LA Skaltsounis
Further Information

Publication History

Publication Date:
20 December 2019 (online)

 

Recent research has emphasised the promising therapeutic potential of fibre-type Cannabis sativa L. (hemp) and related phytocannabinoids [1]. Among the most abundant and valuable non-psychoactive cannabinoids are cannabidiol (CBD) and cannabidiolic acid (CBDA), both exhibiting a wide spectrum of pharmacological activities [2]. Efficient analytical methodologies for cannabinoids determination are thus crucial for hemp quality testing and utilisation [3]. In this context, the present study aimed to develop an integrated procedure for the effective extraction and quantitative analysis of the major cannabinoids in hemp.

Ultrasound-assisted extraction (UAE), microwave-assisted extraction (MAE) and dynamic maceration (DM) were examined using EtOH as reference solvent [4]. UAE displayed superior performance and was further optimised through Design of Experiments (DoE), maximising the recovery of cannabinoids. Rapid and reliable quantification of principal cannabinoids was achieved by means of UPLC-PDA. The method was developed and validated utilising highly-pure cannabinoids isolated by centrifugal partition chromatography (CPC) [5]. Several extraction solvents were also evaluated using the optimised UAE protocol and UPLC-PDA. HPTLC densitometry combined with chemometrics was implemented for classification of the extracts obtained with different solvent types to ensure a broad range of bioactive compounds.

In this work, a highly-efficient UPLC-PDA method coupled with a simplified UAE-based extraction protocol is presented for the quantification of the principal cannabinoids in hemp. The proposed HPTLC methodology enables the rapid and cost-effective fingerprint analysis for solvent selection.

 
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