Electrochemical fingerprinting and phylogenetic analysis of Inula species

Abstract

This study presents a groundbreaking approach in the chemotaxonomic classification of Inula species through electrochemical fingerprinting and multivariate data analysis. Focusing on 14 different Inula species, the research utilized differential pulse voltammetry to analyze leaf extracts in varying pH conditions (acetate pH 4.5, phosphate pH 7.0, and Tris pH 9.0). The electrochemical profiles generated were distinctive and informative, revealing specific oxidation peaks associated with phytochemical compounds. Principal component analysis (PCA) efficiently captured 91.0 % of the variance in these profiles, effectively distinguishing between species. Hierarchical cluster analysis further corroborated these findings, accurately classifying each species into distinct clusters. The method proved exceptionally precise in identifying unknown Inula samples, achieving a 100 % success rate when matched against a reference library. This approach significantly enhances the rapid identification and quality assurance of medicinal herbs, offering a simpler, faster alternative to traditional chemotaxonomic methods.