Linear discriminant analysis based on gas chromatographic measurements for geographical prediction of USA medical domestic cannabis

Fifty four domestically produced cannabis samples obtained from different USA states were quantitatively assayed by GC-FID to detect 22 active components: 15 terpenoids and 7 cannabinoids. The profiles of the selected compounds were used as inputs for samples grouping to their geographical origins and for building a geographical prediction model using Linear Discriminant Analysis. The proposed sample extraction and chromatographic separation was satisfactory to select 22 active ingredients with a wide analytical range between 5.0 and 1,000 μg/mL. Analysis of GC-profiles by Principle Component Analysis retained three significant variables for grouping job (Δ9-THC, CBN, and CBC) and the modest discrimination of samples based on their geographical origin was reported. PCA was able to separate many samples of Oregon and Vermont while a mixed classification was observed for the rest of samples. By using LDA as a supervised classification method, excellent separation of cannabis samples was attained leading to a classification of new samples not being included in the model. Using two principal components and LDA with GC-FID profiles correctly predict the geographical of 100% Washington cannabis, 86% of both Oregon and Vermont samples, and finally, 71% of Ohio samples

Comprehensive chromatographic profiling of cannabis from 23 USA States marketed for medical purposes

In this research, cannabis varieties represent 23 USA States were assayed by GC-FID to generate their complex chemical profiles informative for plants clustering. Results showed that 45 cannabinoids and terpenoids were quantified in all plant samples, where 8 cannabinoids and 18 terpenoids were identified. Among organics, Δ9-THC, CBN (cannabinoids) and Fenchol (terpenoid) not only showed the highest levels overall contents, but also were the most important compounds for cannabis clustering. Among States, Washington, Oregon, California and Hawaii have the highest cannabis content. GC-FID data were subjected to PCA and HCA to find (1) the variations among cannabis chemical profiles as a result of growing environment, (2) to reveal the compounds that were responsible for grouping cultivars between clusters and (3) finally, to facilitate the future profile prediction and States clustering of unknown cannabis based on the chemical profile. The 23 cannabis USA States were grouped into three clusters based on only Δ9-THC, CBN, C1 and Fenchol content. Cannabis classification based on GC-profile will meet the practical needs of cannabis applications in clinical research, industrial production, patients’ self-production, and contribute to the standardization of commercially-available cannabis cultivars in USA

Supercritical Fluid Chromatography of Drugs: Parallel Factor Analysis for Column Testing in a Wide Range of Operational Conditions

Retention mechanisms involved in supercritical fluid chromatography (SFC) are influenced by interdependent parameters (temperature, pressure, chemistry of the mobile phase, and nature of the stationary phase), a complexity which makes the selection of a proper stationary phase for a given separation a challenging step. For the first time in SFC studies, Parallel Factor Analysis (PARAFAC) was employed to evaluate the chromatographic behavior of eight different stationary phases in a wide range of chromatographic conditions (temperature, pressure, and gradient elution composition). Design of Experiment was used to optimize experiments involving 14 pharmaceutical compounds present in biological and/or environmental samples and with dissimilar physicochemical properties. The results showed the superiority of PARAFAC for the analysis of the three-way (column × drug × condition) data array over unfolding the multiway array to matrices and performing several classical principal component analyses. Thanks to the PARAFAC components, similarity in columns’ function, chromatographic trend of drugs, and correlation between separation conditions could be simply depicted: columns were grouped according to their H-bonding forces, while gradient composition was dominating for condition classification. Also, the number of drugs could be efficiently reduced for columns classification as some of them exhibited a similar behavior, as shown by hierarchical clustering based on PARAFAC components

A study on removal characteristics of <i>o</i>-, <i>m</i>-, and <i>p</i>-nitrophenol from aqueous solutions by organically modified diatomaceous earth

<div><p></p><p>The natural diatomaceous earth (DAT) was modified with surfactant of hexadecyltrimethylammonium bromide (HDTMABr) to form organic-modified diatomaceous earth (DAT-HDTMABr). The DAT and DAT-HDTMABr were characterized by X-ray fluorescence, X-ray diffraction, FT-IR and DTA-TG. The surface area was determined using Brunauer, Emmett, and Teller adsorption method. Cation exchange capacity was estimated using an ethylenediamine complex of copper method, and the modifier loading was calculated from the total carbon analysis. The ability of raw and organomodified diatomaceous earth to remove <i>o</i>-nitrophenol (ONP), <i>m</i>-nitrophenol (MNP), and <i>p</i>-nitrophenol (PNP) from aqueous solutions has been carried out at predetermined equilibration time, adsorbent amount, pH, and temperatures using a batch technique. The removal of ONP, MNP, and PNP from aqueous solutions by modified clay seems to be more effective than unmodified sample. The experimental equilibrium adsorption data were analyzed by four widely used two parameters, Langmuir, Freundlich, Temkin, and Dubinin–Radushkevich (D–R) isotherm equations. Kinetic studies showed that pseudo-second-order described the adsorption experimental data better than the pseudo-first-order kinetic model. Based on the calculated thermodynamic parameters, such as enthalpy (Δ<i>H</i>), entropy (Δ<i>S</i>), and Gibb’s free energy changes (Δ<i>G</i>), it is noticeable that the adsorption of ONP, MNP, and PNP by DAT and DAT-HDTMABr adsorbents was carried out spontaneously, and the process was exothermic in nature.</p></div