Premium
Classification of six herbal bioactive compositions employing LAPV and PLS‐DA
Author(s) -
Górski Łukasz,
Kowalcze Mateusz,
Jakubowska Małgorzata
Publication year - 2019
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.3112
Subject(s) - linear discriminant analysis , partial least squares regression , chemometrics , artificial intelligence , multivariate statistics , pattern recognition (psychology) , mathematics , computer science , chemistry , statistics , machine learning
Numerous medical herbal products available on the market require development of fast and cheap strategies of authenticity control. Such method may be large amplitude pulse voltammetry (LAPV) with boron‐doped diamond electrode (BDDE), combined with chemometric supervised method—partial least squares discriminant analysis (PLS‐DA). The voltammetric method was used to gather the chemical profiles, required to prepare PLS‐DA multivariate classification model. The proposed methodology was successfully applied to classify six ethanol herbal compositions (with content analogous to the commercial products) and provided reliable classification model (without misclassifications).