ABSTRACT
We have built an online tool with a user-friendly and browser-based interface to facilitate the processing of high resolution and precision oil mass spectrometry data. DropMS does not require software installations. Mass spectra are sent and processed by the server using various algorithms reported in the literature, such as S/N ratio filters, recalibrations, chemical formula assimilations, and data visualization using graphs and diagrams popularly known in mass spectrometry as Van Krevelen and Kendrick diagrams and DBE vs C#. To validate the algorithms used and the processing results, the same mass spectrum of a typical Brazilian oil sample was analyzed by ESI(+)-FT-ICR/MS and processed using Sierra Analytics DropMS and Composer to obtain good agreement between the heteroatomic classes found and the number of compounds assigned. The MS has chemical information spread over the entire spectrum. The PLS multivariate regression has the main objective of decomposing the most important information into latent variables in order to quantify the most evaluated properties. Finally, 12 processed petroleum FT-ICR MS spectra were used for a partial least-squares regression with seven latent variables for R2 = 0.971 and RMSEC of 0.997 for API density property with a reference value range of 21-42.
ABSTRACT
Marijuana, a drug derived from the Cannabis sativa L. plant, is the world's most consumed illicit drug. In this paper, a total of 156 marijuana samples seized in the state of Espírito Santo (ES), Brazil were studied and analysed by proton nuclear magnetic resonance (1H NMR) spectroscopy to identify the major cannabinoids present. A crude extract of all samples was purified using high performance liquid chromatography so that these compounds could serve as reference substances. Nine fractions were obtained and analysed by 1H NMR and gas chromatography-mass spectrometry (GC-MS), with five presented cannabinoids. ∆9-THC (Δ9-trans-tetrahydrocannabinol), ∆9-THCA (∆9-tetrahydrocannabinolic acid), ∆8-THC (∆8-tetrahydrocannabinol), 11-hydroxycannabinol, CBV (cannabivarin), and CBN (cannabinol) were found, and their chemical structures were confirmed by GC-MS. The latter compound was obtained with high purity (≈100%), while the others were obtained as less complex mixtures with purity higher than 75% (except for Δ8-THC). Principal component analysis (PCA) was used on the 1H NMR spectra of the 156 samples, and it was found that the samples were grouped according to the months, differentiating into two groups (from July 2014 to January 2015 and from February 2015 to July 2015), where non-grouping was observed from four macro-regions of the ES state (North, Central, Metropolitan, and South). The chemical profile of the seized samples was correlated to the 1H NMR spectrum of an isolated CBN sub-fraction, in which the group formed by samples seized in the year 2015 presented lower CBN content in the chemical composition. From the PCA score plot, two groups of samples were confirmed using the partial least squares discriminant analysis and orthogonal projections to latent structures classification methods.