Characterisation of leaf essential oils of three Cinnamomum species from Malaysia by gas chromatography and multivariate data analysis

Siti Y M Subki, Jamia Azdina Jamal, Khairana Husain, Nurhuda Manshoor

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6 Citations (Scopus)

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 GCeFID and GCeMS techniques. The GCeFID 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. porrectumwas 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.

Original languageEnglish
Pages (from-to)22-29
Number of pages8
JournalPharmacognosy Journal
Volume5
Issue number1
DOIs
Publication statusPublished - 2013

Fingerprint

Cinnamomum
Malaysia
Volatile Oils
Gas Chromatography
Cinnamomum zeylanicum
Multivariate Analysis
Principal Component Analysis
Cluster Analysis
Oils
Safrole
Eugenol

Keywords

  • Cinnamomum spp.
  • Essential oils
  • Hierarchical cluster analysis
  • Principal component analysis

ASJC Scopus subject areas

  • Drug Discovery
  • Pharmacology

Cite this

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title = "Characterisation of leaf essential oils of three Cinnamomum species from Malaysia by gas chromatography and multivariate data analysis",
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 GCeFID and GCeMS techniques. The GCeFID 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. porrectumwas 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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AB - 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 GCeFID and GCeMS techniques. The GCeFID 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. porrectumwas 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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