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Application of UV/VIS Spectrophotometry and Multivariate Analysis to Characterization of the Species of Solanum sect. Erythrotrichum Child
Author(s) -
Basílio Ionaldo José L. D.,
Moura Renata K. P.,
Bhattacharyya Jnanabrata,
de Fátima Agra Maria
Publication year - 2012
Publication title -
chemistry and biodiversity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.427
H-Index - 70
eISSN - 1612-1880
pISSN - 1612-1872
DOI - 10.1002/cbdv.201100302
Subject(s) - solanum , chemistry , sect , spectrophotometry , multivariate analysis , characterization (materials science) , multivariate statistics , botany , chromatography , statistics , biology , mathematics , physics , optics
Abstract The UV/VIS spectral characteristics of the standardized extracts of the leaves of 22 Solanum species of the Leptostemonum clade were investigated in the presence of shift reagents with the aid of multivariate analysis, to obtain data in support of the interspecific and subsectional delimitation proposed for Solanum sect. Erythrotrichum. Of these species, 20 belong to the section Erythrotrichum, S. paniculatum is assigned to the section Torva , and S. robustum is not attributed to a defined section. The results indicated characteristic λ max (absorbance maxima) for each species as well as the presence of phenolic compounds like flavonoids such as 5‐hydroxy flavonols. Hierarchical cluster analysis (HCA) of the data obtained by UV/VIS analysis of the extracts or the extracts with the added shift reagents AlCl 3 and HCl showed a cophenetic correlation coefficient above 0.92 and the classification of the data into three groups. The principal‐component analysis (PCA) revealed that the first three principal components accounted for over 98% of the total variance and showed results similar to those obtained by HCA. The present results supported the current proposal for interspecific delimitation of the studied species and partially supported the division of the section into two subsections. The UV/VIS spectral characteristics along with multivariate analysis appear to be a useful approach for distinguishing among species of the genus Solanum.