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Multivariate chromatographic fingerprint preparation and authentication of plant material from the genus Bauhinia
Author(s) -
Soares Patricia Kaori,
Scarminio Ieda Spacino
Publication year - 2007
Publication title -
phytochemical analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.574
H-Index - 72
eISSN - 1099-1565
pISSN - 0958-0344
DOI - 10.1002/pca.1020
Subject(s) - chemistry , chromatography , fingerprint (computing) , dichloromethane , principal component analysis , acetonitrile , solvent , multivariate statistics , high performance liquid chromatography , organic chemistry , statistics , computer security , mathematics , computer science , artificial intelligence
Multivariate analysis and statistical mixture designs were used for chromatographic fingerprint preparation and authentication of the plant material of three species of the genus Bauhinia . The extracts were analysed by reversed‐phase high‐performance liquid chromatography. Mixture design gave an optimum solvent composition for extracting components from the plants of 36% dichloromethane, 17% ethanol and 47% ethyl acetate (by volume), while an optimum mobile phase for chromatographic analyses was found to be 27% methanol, 27% acetonitrile and 46% of water (by volume). Results from principal component analysis, hierarchical analysis and soft independent modelling by class analogy showed that Bauhinia candicans cannot be synonymous with B. forficata Link. It was also possible to trace the metabolic profile without identifying its chemical constituents and to determine a chromatographic discriminating region. The characteristics responsible for discrimination between B. candicans and B. forficata were more polar substances that presented peaks with retention times around 1.65 and 1.81 min. Copyright © 2007 John Wiley & Sons, Ltd.