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Characteristic Fingerprint Based on Low Polar Constituents for Discrimination of Wolfiporia extensa according to Geographical Origin Using UV Spectroscopy and Chemometrics Methods.

Li Y, Zhang J, Zhao Y, Li Z, Li T, Wang Y - J Anal Methods Chem (2014)

Bottom Line: The results showed that W. extensa samples were well classified according to their geographical origins.The proposed method can fully utilize diversified fingerprint characteristics of sclerotium of W. extensa and requires low-cost equipment and short-time analysis in comparison with other techniques.Meanwhile, this simple and efficient method may serve as a basis for the authentication of other medicinal fungi.

View Article: PubMed Central - PubMed

Affiliation: Institute of Medicinal Plants, Yunnan Academy of Agricultural Sciences, Kunming 650200, China ; College of Traditional Chinese Medicine, Yunnan University of Traditional Chinese Medicine, Kunming 650500, China.

ABSTRACT
The fungus species Wolfiporia extensa has a long history of medicinal usage and has also been commercially used to formulate nutraceuticals and functional foods in certain Asian countries. In the present study, a practical and promising method has been developed to discriminate the dried sclerotium of W. extensa collected from different geographical sites based on UV spectroscopy together with chemometrics methods. Characteristic fingerprint of low polar constituents of sample extracts that originated from chloroform has been obtained in the interval 250-400 nm. Chemometric pattern recognition methods such as partial least squares discriminant analysis (PLS-DA) and hierarchical cluster analysis (HCA) were applied to enhance the authenticity of discrimination of the specimens. The results showed that W. extensa samples were well classified according to their geographical origins. The proposed method can fully utilize diversified fingerprint characteristics of sclerotium of W. extensa and requires low-cost equipment and short-time analysis in comparison with other techniques. Meanwhile, this simple and efficient method may serve as a basis for the authentication of other medicinal fungi.

No MeSH data available.


Dendrogram resulting from hierarchical cluster analysis.
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Related In: Results  -  Collection


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fig9: Dendrogram resulting from hierarchical cluster analysis.

Mentions: HCA is an unsupervised pattern recognition method for clustering samples based on their similarities [54, 55]. To further explore the relationships among the W. extensa sclerotium specimens, HCA of the spectra data was performed. Table 3 is the agglomeration schedule that shows the detailed steps of HCA. The corresponding cluster dendrogram was generated by applying hclust function using average linkage clustering of the squared Euclidean distance based on the normalized data from the 23 test samples. As shown in Figure 9, all the specimens could be divided into three fractions when the distance of them is twenty, group I contains the samples of Chuxiong, and the other two groups are composed of the samples collected from Pu'er and Honghe, respectively. All samples were correctly classified according to their geographical origins without any misclassification. In addition, the results could verify the consequence of PLS-DA.


Characteristic Fingerprint Based on Low Polar Constituents for Discrimination of Wolfiporia extensa according to Geographical Origin Using UV Spectroscopy and Chemometrics Methods.

Li Y, Zhang J, Zhao Y, Li Z, Li T, Wang Y - J Anal Methods Chem (2014)

Dendrogram resulting from hierarchical cluster analysis.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4269309&req=5

fig9: Dendrogram resulting from hierarchical cluster analysis.
Mentions: HCA is an unsupervised pattern recognition method for clustering samples based on their similarities [54, 55]. To further explore the relationships among the W. extensa sclerotium specimens, HCA of the spectra data was performed. Table 3 is the agglomeration schedule that shows the detailed steps of HCA. The corresponding cluster dendrogram was generated by applying hclust function using average linkage clustering of the squared Euclidean distance based on the normalized data from the 23 test samples. As shown in Figure 9, all the specimens could be divided into three fractions when the distance of them is twenty, group I contains the samples of Chuxiong, and the other two groups are composed of the samples collected from Pu'er and Honghe, respectively. All samples were correctly classified according to their geographical origins without any misclassification. In addition, the results could verify the consequence of PLS-DA.

Bottom Line: The results showed that W. extensa samples were well classified according to their geographical origins.The proposed method can fully utilize diversified fingerprint characteristics of sclerotium of W. extensa and requires low-cost equipment and short-time analysis in comparison with other techniques.Meanwhile, this simple and efficient method may serve as a basis for the authentication of other medicinal fungi.

View Article: PubMed Central - PubMed

Affiliation: Institute of Medicinal Plants, Yunnan Academy of Agricultural Sciences, Kunming 650200, China ; College of Traditional Chinese Medicine, Yunnan University of Traditional Chinese Medicine, Kunming 650500, China.

ABSTRACT
The fungus species Wolfiporia extensa has a long history of medicinal usage and has also been commercially used to formulate nutraceuticals and functional foods in certain Asian countries. In the present study, a practical and promising method has been developed to discriminate the dried sclerotium of W. extensa collected from different geographical sites based on UV spectroscopy together with chemometrics methods. Characteristic fingerprint of low polar constituents of sample extracts that originated from chloroform has been obtained in the interval 250-400 nm. Chemometric pattern recognition methods such as partial least squares discriminant analysis (PLS-DA) and hierarchical cluster analysis (HCA) were applied to enhance the authenticity of discrimination of the specimens. The results showed that W. extensa samples were well classified according to their geographical origins. The proposed method can fully utilize diversified fingerprint characteristics of sclerotium of W. extensa and requires low-cost equipment and short-time analysis in comparison with other techniques. Meanwhile, this simple and efficient method may serve as a basis for the authentication of other medicinal fungi.

No MeSH data available.