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Issue 13, 2019
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LDI and MALDI-FT-ICR imaging MS in Cannabis leaves: optimization and study of spatial distribution of cannabinoids

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Abstract

A matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) technique is considered a powerful analytical tool to determine the chemical identity and spatial distribution of several molecules in a single analysis, conserving its natural histology. However, there are no specific studies by MALDI IMS on the spatial distribution of cannabinoids in the extension of Cannabis leaves. Therefore, the LDI, MALDI MS, and IMS techniques have been employed to detect and determine the distribution of cannabinoid compounds on the surface of fresh and aged Cannabis leaves, evaluating the ionization efficiency of three matrices: α-cyano-4-hydroxycinnamic acid (CHCA), 2.5-dihydroxybenzoic acid (DHB), and 2-mercaptobenzothiazole (MBT), in different concentrations (from 0.1 to 25 mg mL−1). The results of MALDI(−) MS and IMS showed a better ionization efficiency of cannabinoids at low concentrations (0.1 and 0.5 mg mL−1) of the matrices. In the analyzes of whole Cannabis leaves, in comparison to LDI, MALDI provided a better detection and spatial distribution of the cannabinoids with an MBT matrix. The sensitivity of the IMS technique was also evaluated on the surface of the Jatropha curca L. leaves using different concentrations of cannabinol (CBN) standard (from 1.0 to 15.0 mg mL−1). The spatial distribution of CBN, m/z 309, on physic nut leaves proved the excellent sensitivity of the IMS technique (LOD < 1.0 mg mL−1).

Graphical abstract: LDI and MALDI-FT-ICR imaging MS in Cannabis leaves: optimization and study of spatial distribution of cannabinoids

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Supplementary files

Article information


Submitted
30 Jan 2019
Accepted
26 Feb 2019
First published
27 Feb 2019

Anal. Methods, 2019,11, 1757-1764
Article type
Paper

LDI and MALDI-FT-ICR imaging MS in Cannabis leaves: optimization and study of spatial distribution of cannabinoids

N. A. dos Santos, L. M. de Souza, F. E. Pinto, C. de J. Macrino, C. M. de Almeida, B. B. Merlo, P. R. Filgueiras, R. S. Ortiz, R. Mohana-Borges and W. Romão, Anal. Methods, 2019, 11, 1757
DOI: 10.1039/C9AY00226J

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