Abstract
Identification of chemical composition of essential oils as raw materials is very important for ensuring the quality of finished herbal products. The objectives of the study were to determine the chemical composition of essential oils of the leaves of three Cinnamomum species (i.e. Cinnamomum mollissimum Hook.f., Cinnamomum porrectum (Roxb.) Kosterm. and Cinnamomum verum J.S. Presl.) and to characterise the essential oils constituents by using GC and multivariate data analysis. Hydro-distilled essential oils were evaluated using GC–FID and GC–MS techniques. The GC–FID chromatograms were further analysed by multivariate data analysis using principal component analysis (PCA) and hierarchical clustering analysis (HCA) methods. The major compound identified in the oil of C. mollissimum was benzyl benzoate (77.69%), whereas that for C. porrectum was safrole (93.19%) and C. verum was eugenol (93.08%). PCA score and HCA plots revealed that the leaf oils were classified into three separated clusters of C. verum (Cluster I), C. mollissimum (Cluster II) and C. porrectum (Cluster III) based on their characteristic chemical compositions. The combination of GC and multivariate data analysis may be used for identification and characterisation of essential oils from different Cinnamomum species that are to be used as raw materials of traditional herbal products.
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