Multivariate Data Analysis of Plants

Abstract

Abstract When developing fingerprints of herbal samples, three steps should be considered, that is, the development, the validation, and the extraction of information from the multivariate fingerprint data. After an introduction concerning the tendency to shifting toward using fingerprints to evaluate herbal samples in various contexts and a brief description of the three steps when developing fingerprints, the major part of this chapter focuses on the multivariate data analysis of herbal fingerprints. This chapter also deals with the preprocessing of the multivariate data, and unsupervised and supervised data analysis techniques are described in short Finally, some case studies are presented, in which multivariate data analysis methods were applied to extract information on herbal samples from various types of fingerprints, such as spectroscopic, mass spectrometric, chromatographic fingerprints, and fingerprints developed using electrodriven techniques. Depending on the goal of the study, different multivariate data analysis methods were used.