Affiliations 

  • 1 Faculty of Pharmacy, Universitas Ahmad Dahlan, Yogyakarta 55281, Indonesia
  • 2 Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia
  • 3 Research Division for Natural Product Technology (BPTBA), National Research and Innovation Agency (BRIN), Yogyakarta 55861, Indonesia
  • 4 Division of Pharmaceutical Analysis and Medicinal Chemistry, Faculty of Pharmacy, Universitas Sanata Dharma, Yogyakarta 55282, Indonesia
  • 5 International Institute for Halal Research and Training (INHART), International Islamic University Malaysia (IIUM), Kuala Lumpur 50728, Malaysia
  • 6 Department of Chemistry, Faculty of Mathematics and Natural Sciences, IPB University, Bogor 16680, Indonesia
Molecules, 2021 Dec 16;26(24).
PMID: 34946709 DOI: 10.3390/molecules26247626

Abstract

Curcuma longa, Curcuma xanthorrhiza, and Curcuma manga have been widely used for herbal or traditional medicine purposes. It was reported that turmeric plants provided several biological activities such as antioxidant, anti-inflammatory, hepatoprotector, cardioprotector, and anticancer activities. Authentication of the Curcuma species is important to ensure its authenticity and to avoid adulteration practices. Plants from different origins will have different metabolite compositions because metabolites are affected by soil nutrition, climate, temperature, and humidity. 1H-NMR spectroscopy, principal component analysis (PCA), and orthogonal projections to latent structures-discriminant analysis (OPLS-DA) were used for authentication of C. longa, C. xanthorrhiza, and C. manga from seven different origins in Indonesia. From the 1H-NMR analysis it was obtained that 14 metabolites were responsible for generating classification model such as curcumin, demethoxycurcumin, alanine, methionine, threonine, lysine, alpha-glucose, beta-glucose, sucrose, alpha-fructose, beta-fructose, fumaric acid, tyrosine, and formate. Both PCA and OPLS-DA model demonstrated goodness of fit (R2 value more than 0.8) and good predictivity (Q2 value more than 0.45). All OPLS-DA models were validated by assessing the permutation test results with high value of original R2 and Q2. It can be concluded that metabolite fingerprinting using 1H-NMR spectroscopy and chemometrics provide a powerful tool for authentication of herbal and medicinal plants.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.