Pattern Recognition for Varieties of Malaysian Herb, Ficus deltoidea Jack through Chemometric Applications from GC-MS Fingerprinting

Pattern based approach has been used for quality control for identification and authentication of herbal medicines including plant that having varietal issue, Ficus deltoidea Jack (FD). Chemical fingerprinting of FD varieties were profiled by Gas Chromatography-Mass Spectrometry (GC-MS). The aim was to profile and classify the untargeted volatile compounds which commonly occur in FD varieties for pattern recognition purpose. Chromatographic data from GC-MS fingerprint of FD varieties were analyzed using chemometric applications; principal component analysis (PCA), hierarchical cluster analysis (HCA) and discriminant analysis (DA). Twenty-two major volatile compounds found were commonly occurred and stable in FD varieties. PCA give out total variance of 33.13%, while HCA generated three clusters. However, DA confirmed FD varieties only grouped into two groups, which suggested that the unidentified compounds at tR: 8.85, 14.80, 16.25, 16.55 and 29.06 were the most significant parameters (p < 0.05) to discriminate both grouping. This finding indicates that 22 volatile compounds that commonly occur in FD varieties do not contribute to the discrimination and var. bilobata revealed to have specific volatile compounds that distinguish it from other varieties. The use of GC-MS fingerprinting and chemometric techniques provides useful and promising information for authentication and quality control of herbal medicines.