Loading…

Pattern Recognition of the Herbal Drug, Magnoliae Flos According to their Essential Oil Components

This paper describes a pattern recognition method of Magnoliae flos based on a gas chromatographic/mass spectrometric (GC/MS) analysis of the essential oil components. The botanical drug is mainly comprised of the four magnolia species (M. denudata, M. biondii, M. kobus, and M. liliflora) in Korea,...

Full description

Saved in:
Bibliographic Details
Published in:Bulletin of the Korean Chemical Society 2009, 30(5), , pp.1121-1126
Main Authors: Eun Sook Jeong, Kyu-Yeol Choi, 김선춘, Su Youn Ahn, In Seop Son, Hwang Eui Cho, 우미희, 홍진태, 문동철
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper describes a pattern recognition method of Magnoliae flos based on a gas chromatographic/mass spectrometric (GC/MS) analysis of the essential oil components. The botanical drug is mainly comprised of the four magnolia species (M. denudata, M. biondii, M. kobus, and M. liliflora) in Korea, although some other species are also being dealt with the drug. The GC/MS separation of the volatile components, which was extracted by the simultaneous distillation and extraction (SDE), was performed on a carbowax column (supelcowax 10; 30 m × 0.25 mm × 0.25 μm) using temperature programming. Variance in the retention times for all peaks of interests was within RSD 2% for repeated analyses (n = 9). Of the 74 essential oil components identified from the magnolia species,approximately 10 major components, which is α-pinene, β-pinene, sabinene, myrcene, d-limonene, eucarlyptol (1,8-cineol), γ-terpinene, p-cymene, linalool, α-terpineol, were commonly present in the four species. For statistical analysis, the original dataset was reduced to the 13 variables by Fisher criterion and factor analysis (FA). The essential oil patterns were processed by means of the multivariate statistical analysis including hierarchical cluster analysis (HCA), principal component analysis (PCA) and discriminant analysis (DA). All samples were divided into four groups with three principal components by PCA and according to the plant origins by HCA. Thirty-three samples (23 training sets and 10 test samples to be assessed) were correctly classified into the four groups predicted by PCA. This method would provide a practical strategy for assessing the authenticity or quality of the well-known herbal drug, Magnoliae flos. KCI Citation Count: 5
ISSN:0253-2964
1229-5949
DOI:10.5012/bkcs.2009.30.5.1121