Kecombrang flower (Etlingera elatior) is widely used in traditional medicine and contains various metabolites. High-performance liquid chromatography (HPLC) fingerprinting can be employed as an analytical technique to comprehensively reveal the metabolite profile, while ultrasound-assisted extraction (UAE) was developed to optimize metabolite extraction. This study aims to determine the optimal extraction conditions for E. elatior and apply these conditions in HPLC fingerprinting. This study utilized central composite design (CCD) and response surface methodology (RSM) to optimize the extraction of E. elatior flowers, focusing on extraction time and the simplicia-to-solvent ratio. The optimal extraction results were applied to HPLC fingerprints of the flowers, leaves, and stems of E. elatior. The chromatograms were further analyzed using chemometric methods, namely principal component analysis (PCA), partial least squares discriminant analysis (PLSDA), and hierarchical cluster analysis (HCA) to classify and interpret the variability of metabolite profiles in different parts of E. elatior. The optimal UAE conditions were determined to be a time of 46 minutes and a simplicia-to-solvent ratio of 1:25 (g/mL). Chemometric analysis revealed that the samples were well clustered, which reflects the similarity of metabolites among them. The HCA further showed that the metabolite profile of E. elatior flowers is closely related to that of the stems.
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