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- Author or Editor: Mirosław A. Hawrył x
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Two-dimensional thin layer chromatography of twelve flavonoids and three phenolic acids from Betula sp. leaves has been performed in normal-phase systems. Plots showing the dependence of RM on modifier concentration in some non-aqueous systems were used to optimize the chromatographic separation. RM values were correlated for all the chromatographic systems investigated and optimum pairs of systems were then selected for use in two-dimensional TLC separations. Complete separation of the compounds investigated was achieved by use of two optimum non-aqueous mobile phases on silica plates.
Seven different Scutellaria species were analyzed using the extraction procedure (Soxhlet apparatus, dichloromethane, and methanol as solvents) and thin-layer chromatography method. Selected standards of flavonoids and phenolic acids (caffeic acid, chlorogenic acid, ferulic acid, baicalein, wogonin, baicalin, chrysin, quercetin, scutellarin, hesperetin, hesperidin, apigenin, luteolin, rutin, and kaempferol) were separated using silica gel thin-layer chromatography (TLC) plates with the mobile phase consisting of ethyl acetate—toluene—formic acid (5:4.9:0.1, v/v) for dichloromethane and methanolic extracts. Dichloromethane extracts were also developed using cyanopropyl-bonded silica gel with the following mobile phases: propan-2-ol—n-heptane—formic acid (5:4.9:0.1, v/v) and methanol—water—formic acid (6:3.9:0.1, v/v), and after drying, they were sprayed using the anisaldehyde reagent. In the case of methanolic extracts, the same non-aqueous eluent was used and the aqueous eluent consisting of methanol—water—formic acid (4:5.9:0.1, v/v). The presence of selected standards in Scutellaria species was confirmed. The similarities between the obtained fingerprint chromatograms were performed using chemometric methods, the similarity coefficients (Pearson’s correlation coefficient, determination coefficient, and congruence coefficient), distance indices (Euclidean distance, Manhattan distance, and Chebyshev’s distance), and multi-scale structural similarity (MS-SSIM).
