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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.


Distance to model in X-space (DModX) of all the specimens.
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Related In: Results  -  Collection


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fig5: Distance to model in X-space (DModX) of all the specimens.

Mentions: PLS-DA, a supervised method, is a variation of PLS analysis. It is considered as a pair comparison analysis and is built to classify a group of samples as belonging or not belonging to a specific class [51, 52]. This method, as a representative technique, was applied to construct and validate a statistical model to find difference in low polar constituents among the W. extensa sclerotium samples according to their geographical origins. Figure 5 reports the distance to model in X-space (DModX) of all the samples. The values of DModX of all samples are under 1.45 and a value of P < 0.05 is considered statistically significant. It revealed that the results of PLS-DA were reasonable.


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)

Distance to model in X-space (DModX) of all the specimens.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

fig5: Distance to model in X-space (DModX) of all the specimens.
Mentions: PLS-DA, a supervised method, is a variation of PLS analysis. It is considered as a pair comparison analysis and is built to classify a group of samples as belonging or not belonging to a specific class [51, 52]. This method, as a representative technique, was applied to construct and validate a statistical model to find difference in low polar constituents among the W. extensa sclerotium samples according to their geographical origins. Figure 5 reports the distance to model in X-space (DModX) of all the samples. The values of DModX of all samples are under 1.45 and a value of P < 0.05 is considered statistically significant. It revealed that the results of PLS-DA were reasonable.

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.