Partomuan Simanjuntak
Research Center for Biotechnology, Indonesian Institute of Sciences (LIPI), Jl. Raya Bogor Km 46, Cibinong 16911, Indonesia

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FTIR and HPLC-Based Metabolomics of Yacon Leaves Extracts (Smallanthus sonchifolius [Poepp & Endl.] H. Robinson) from Two Locations in Indonesia Zulhelmi Aziz; Nancy Dewi Yuliana; Partomuan Simanjuntak; Mohamad Rafi; Syamsudin Abdillah
Indonesian Journal of Chemistry Vol 20, No 3 (2020)
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (17.372 KB) | DOI: 10.22146/ijc.43453

Abstract

Smallanthus sonchifolius [Poepp. & Endl.] H. Robinson (Asteraceae) also known as Yacon or insulin plant, is traditionally used for treating diabetes. Varying geographical origins and postharvest handling, however, seem to affect quantitative and qualitative metabolites in the leaves of Smallanthus sonchifolius [Poepp. & Endl.] H. Robinson (Yacon). The study was conducted to compare and differentiate metabolites profile/fingerprint of Yacon leaves which were grown and obtained from different locations in Pulau Jawa i.e. Lembang (Jawa Barat) and Wonosobo (Jawa Tengah). Three different solvents (95% ethanol, 50% ethanol and water) were used to synthesize Yacon leaves extracts, in order to determine the suitable solvent to produce discernable differentiation through FTIR and HPLC-based metabolomics. Principal Component Analysis (PCA) of FTIR data (4000–400 cm1 wavenumber) indicated that Yacon leaves extracted with ethanol at 95%, had a distinctive FTIR fingerprint profile when compared to others. However, the FTIR-based PCA could not differentiate the extracts based on their geographical origins, although PCA analysis of HPLC-data successfully differentiated the extracts based on their geographical origins. Furthermore, the prominent peak for the leaves extract from Lembang and Wonosobo as regards retention time, was observed at 21.59–25.10 min and 20.69–21.695 min respectively. Notably, R2Y and Q2 value obtained by cross-validation and permutation tests showed all multivariate models were statistically reliable. Overall, there is the need to conduct further research using a more sophisticated tool such as LC-MS, to identify which metabolites represented by the aforementioned FTIR and HPLC data.