Fingerprint analysis of unfractionated Piper plant extracts by HPLC-UV-DAD coupled with chemometric methods

Abstract

23 crude ethanolic extracts of Piper plants were analyzed by combining HPLC fingerprints and chemometric methods including principal component analysis (PCA), hierarchical clustering analysis (HCA) and parallel factor analysis (PARAFAC). All statistical analysis were carried out both with and without previous preprocessing by counting with alignment of the fingerprints by correlation optimized warping (COW) and several normalization methods. Normalization processes of autoscaling, range scaling and vast scaling resulted to be the better offering the most relevant information. Both direct two-way methods (PCA and HCA) and HCA after data minimization employing a three-way method (PARAFAC) were demonstrated to be useful in the establishment of chemical composition relationships among Piper samples, and resulting in agreement with phylogenic relationships previously reported in literature to some Piper species.