NATURAL PRODUCT RESEARCH AND DEVELOPMENT ›› 2018, Vol. 30 ›› Issue (6): 983-989. doi: 10.16333/j.1001-6880.2018.6.012

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Quality Analysis and Evaluation Indexes Determination of  Dendrobium officinale

ZHANG Jing-fang,HE Shu-min,XIE Qian,LI Ze-kun,YE Qing-hua,CHEN Qing-xi*   

  1. College of Horticulture,Fujian Agriculture and Forestry University,Fuzhou 350002,China
  • Online:2018-07-05 Published:2018-07-05

Abstract: In order to compare the quality difference in different areas and simplify the evaluation index of Dendrobium officinale quality,30 indicators of Dendrobium candidum introduced were used as test materials to measure 14 indexes such as pseudobulb length.The characters of Dendrobium candidum The correlation analysis to explore the relationship between indicators,combined with principal component analysis and cluster analysis of Dendrobium evaluation indicators to simplify.The results showed that among the 14 indicators of Dendrobium candidum,except the coefficient of variation of water content was the smallest,the coefficient of variation of the remaining 13 indicators were above 10%;the length of pseudobulb and the diameter of pseudobulb,number of segments,leaf width,pseudobulb diameter and section Leaf width,number of leaves and leaf width,leaf shape,pitch and leaf length,leaf width and leaf shape,pseudobulb posture and leaf tip shape were extremely significantly positive correlation,pitch and leaf shape had a significant negative correlation,Polysaccharides and water content were not significantly correlated with other indexes.The content of alcohol-soluble extract had only a significant positive correlation with leaf length.According to the principal component analysis and clustering analysis,the quality index of 13 Dendrobium candidums could be reduced to five,ie,the pseudobulb length(Or pseudobulb diameter),pseudobulb pose,pseudobulb color,alcohol-soluble extract content,and polysaccharide content.

Key words: Dendrobium officinale, quality evaluation, index simplification, principal component analysis, cluster analysis

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