Abstract

‘Giant Green’ is one of the Syzygium samarangense cultivars planted throughout Malaysia because it has great potential for benefitting human health. However, its variation in chemical compounds, especially in the leaves at different maturity stages, cannot be systematically discriminated. Hence, Fourier transform infrared spectroscopy (FTIR) and gas chromatography–mass spectrometry (GCMS) coupled with chemometric tools were applied to discriminate between the different stages of leaves, namely, young, mature, and old leaves. The chemical variability among the samples was evaluated by using principal component analysis (PCA) and hierarchical clustering analysis (HCA) techniques. For discrimination, partial least squares discrimination analysis (PLS-DA) was applied, and then partial least squares (PLS) was used to determine the correlation between biological activities (antioxidant and alpha-glucosidase inhibitory assay) and maturity stages of ‘Giant Green’ leaves. As a result, the PCA, HCA, and PLS-DA of the FTIR and GC-MS data showed the separation between clusters for the different maturity stages of the leaves. Additionally, the PLS result demonstrated that the young leaves showed a strong correlation between metabolite quantities and biological activities. The findings of this study revealed that FTIR and GC-MS coupled with chemometric analyses can be used as a rapid method for the discrimination of bioactive structural functions in relation to their biological activity.

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