Chemicals and Bioactivity Discrimination of Syconia of Seven Varieties of Ficus deltoidea Jack via ATR-IR Spectroscopic-Based Metabolomics

Introduction: Ficus deltoidea is one of the common Malaysian medicinal plants and currently commercialized as raw ingredients in some local food products. However, those products do not discriminate the varieties of Ficus deltoidea used. Methods: FTIR-based metabolomics coupled with chemometric technique was applied to discriminate chemical components in ethanolic extracts of syconia of seven varieties of Ficus deltoidea namely; var. deltoidea, var. trengganuensis, var. kunstleri, var. angustifolia, var. bilobata, var. intermedia and var. motleyana. Unsupervised multivariate data analysis (MVDA) including principal component analysis (PCA) was used as to evaluate chemical variability among the seven varieties. For discrimination, orthogonal partial least square discriminant analysis (OPLS-DA) was applied, while partial least square (PLS) was used to evaluate the relationship between the alpha-glucosidase inhibition, antioxidant activity and Ficus deltoidea varieties. Results: As a result, OPLS-DA successfully discriminated the seven varieties. The FTIR fingerprints which were responsible for the discrimination includes 1729, 1705, 1448, 1095, 453, 443 cm-1. In addition, PPLS model demonstrated the correlation between var. kunstleri, var. deltoidea and var. intermedia respective chemicals fingerprints and their bioactivity (DPPH, FRAP and α-glucosidase inhibition). Conclusion: The findings revealed that FTIR spectroscopy, in combination with MVDA, can be used for structural functional discrimination in relation to the sample bioactivity.