FINGERPRINT ANALYSIS OF Stevia rebaudiana USING HIERACHIAL CLUSTER ANALYSIS (HCA) AND PRINCIPAL COMPONENT ANALYSIS (PCA)

• Main Authors: Yohanes Martono, Sugeng Riyanto, Sudibyo Martono, Abdul Rohman
• Format: Article
• Language: English
• Published: Universitas Gadjah Mada 2016-04-01
• Series: Majalah Obat Tradisional
• Subjects: Stevia rebaudiana, Hierachial Cluster Analysis (HCA), Principal Component Analysis (PCA)
• Online Access: https://jurnal.ugm.ac.id/TradMedJ/article/view/10722

Bioactivity herbal plant is influenced by its active compounds and consistency. Stevia rebaudiana contains bioactive compounds, diterpene glycosides which have antidiabetes activity. The goal of this study was to develop fingerprints analysis of S. rebaudiana based on High Performance Liquid Chromatography (HPLC) chromatogram. S. rebaudina leaves were taken from different planting area, leave ages, and seeds source. S. rebaudiana leaves were analyzed using isocratic Reversed Phase High Performance Liquid Chromatography (RP-HPLC). Fingerprints analysis of S. rebaudiana was done using chemometrics of Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA). Peak marker “common peak” were identify using Cluster Observation in HCA analysis at each peaks retention time formed in chromatogram. Retention times giving similarity value more than 0,90 were identified as “common peak”. HCA analysis resulted in 5 “common peak” identification as peaks marker particularly at peak no 1, 2, 4, 6 and 7. HCA analysis was also clustered samples into 3 main cluster. PCA analysis was optimized by calculated peak area whose N > 2000 particularly peak no 4, 6, and 7. PCA analysis result can be used to classify chromatogram based on original seeds, planting area and leave ages. Fingerprints analysis developed can be used an alternative method for quality control of S. rebaudiana herbal plants based on its bioactive compounds systemic characteristics.