PubMed: Non-psychoactive cannabinoids identification by linear retention index approach applied to a hand-portable capillary liquid chromatography platform
Anal Bioanal Chem. 2022 Jan 5. doi: 10.1007/s00216-021-03871-x. Online ahead of print.
The aim of the present research was the application of the linear retention index (LRI) system for the identification of non-psychoactive cannabinoids using a portable LC instrument. The miniaturization, viz. the use of very low quantities of mobile phase, enabled the development of a compact mobile system to be used for in situ analysis, also according to a green and cost-saving approach. In particular, new capillary LC (cap-LC) methods coupled with UV detection were developed for the analysis of extracts of Cannabis sativa L. Two setups were explored to achieve the efficient separation of twenty-four cannabinoids: a single column setup which exploited a sub-2 µm packing to increase the chromatographic resolution, and a dual-column setup based on the serial connection of two different stationary phases, each coupled to an UV detector. The latter allowed the determination of two LRI values for each analyte, thus increasing the identification power. Moreover, since two different wavelengths were used on the LED-based UV detectors, the ratio of the absorbances measured on each chromatographic trace represented a third identification criterion, thus fulfilling the recommendations of the Scientific Working Group for The Analysis of Seized Drugs (SWDRUG) about the categories of analytical techniques to be used and the minimum number of parameters required for the unambiguous identification of drugs. The obtained results could be used for the development of a novel analytical method for fast and automatic in situ forensic investigations and hemp breeding programs, also minimizing the consumption of both sample and solvent.
#CBD #Hemp https://pubmed.ncbi.nlm.nih.gov/34985711/?utm_source=Chrome&utm_medium=rss&utm_campaign=None&utm_content=1jYCQzi_o_qLYr-oQfnMhShgOXkvGma3vcnBGJtrBhuJMOvEVJ&fc=None&ff=20220106055920&v=2.17.5 January 5, 2022 11:00 am