Development and Distinction of <i>Rhizoma rodgersiae</i> with HPLC-DAD Fingerprint Analysis Combined with Chemical Pattern Recognition Techniques

Abstract

In this paper, the feasibility and advantages of employing high performance liquid chromatographic-photodiode array detection (HPLC-DAD) fingerprint combined with chemical pattern recognition for quality consistency evaluation of widely used Rhizoma rodgersiae (RR) were investigated and demonstrated for the first time. The Similarity Evaluation System was employed to evaluate the similarities of 10 batches of RR sample; moreover, hierarchical clustering analysis (HCA) and principal component analysis (PCA) were also successfully applied to discriminate RR samples of different regions and seasons. Our results indicated that the seasonal variation had some influence on the chemical fingerprints of this herbal drug. This approach allowed the discrimination of RR samples from different sources. The current study demonstrated that fingerprint profiling coupled with chemical pattern recognition offered a reliable and efficient way to comprehensively assess the quality consistency of the tested samples.

Varietal Discrimination of Pineapple (<i>Ananas comosus</i> L.) Using Chromatographic Fingerprints and Chemometrics

“…PCA has been implemented in many recent studies for authentication and classification in food [25][26][27][28]. It was also used in a recent study to determine the seasonal and regional variation in food authentication based on chromatographic fingerprinting [29]. The variation in the chromatographic fingerprints of each pineapple varieties analyzed by PCA ( Fig.…”