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2011•Lishizhen Medicine and Materia Medica ResearchRequires access

Chemical Pattern Recognition of Quality Assessment of Fructus Gardeniae

Jinxiang Zeng

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Abstract

Objective To establish a method of chemical pattern recognition on the quality assessment of Fructus Gardeniae by HPLC and cluster analysis. Methods The chromatographic seperation was performed on an Eclipse XDB-C_18 column with a mobile phase consisting of acetonitrile-0.1% phosphoric acid,gradient eluent.The UV detection was set at the maximum absorption wavelength at 238 nm for iridoid glycosides and at 440 nm for crocins. Results The result of principal component analysis(PCA) and cluster analysis showed that the 24 batches of Fructus Gardeniae were divided into three types. Conclusion The method can be used for the quality control and comprehensive evaluation of Fructus Gardeniae.

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What this paper is about

Objective To establish a method of chemical pattern recognition on the quality assessment of Fructus Gardeniae by HPLC and cluster analysis. Methods The chromatographic seperation was performed on an Eclipse XDB-C_18 column with a mobile phase consisting of acetonitrile-0.1% phosphoric acid,gradient eluent.The UV detection was set at the maximum absorption wavelength at 238 nm for iridoid glycosides and at 440 nm for crocins. Results The result of principal component analysis(PCA) and cluster analysis showed that the 24 batches of Fructus Gardeniae were divided into three types. Conclusion The method can be used for the quality control and comprehensive evaluation of Fructus Gardeniae.

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Available abstract

Objective To establish a method of chemical pattern recognition on the quality assessment of Fructus Gardeniae by HPLC and cluster analysis. Methods The chromatographic seperation was performed on an Eclipse XDB-C_18 column with a mobile phase consisting of acetonitrile-0.1% phosphoric acid,gradient eluent.The UV detection was set at the maximum absorption wavelength at 238 nm for iridoid glycosides and at 440 nm for crocins. Results The result of principal component analysis(PCA) and cluster analysis showed that the 24 batches of Fructus Gardeniae were divided into three types. Conclusion The method can be used for the quality control and comprehensive evaluation of Fructus Gardeniae.

Key concepts: Chromatography, Principal component analysis, Phosphoric acid, Chemistry, High-performance liquid chromatography, Quality assessment, Iridoid, Gradient elution

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