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Objective:To compare and evaluate the quality of wild and different cultivation methods of Sanghuang porus vaninii (Ljub.) L.W. Zhou & Y.C. Dai through analysis on UPLC characteristic atlas and multi-component content determination results. Methods:UPLC was used to establish the characteristic chromatogram and multi-component content determination method of Sanghuang porus vaninii (Ljub.) L.W. Zhou & Y.C. Dai, and clustering analysis, orthogonal partial least squares - discriminant analysis method were used for chemical pattern recognition analysis. Results:The results showed that there were 10 common peaks in 18 batches of Sanghuang porus vaninii (Ljub.) L.W. Zhou & Y.C. Dai. Five components were identified, erythrothioneine(peak 1), protocatechuic acid (peak 2), protocatechualdehyde (peak 3), caffeic acid (peak 4) and Hispidin (peak 5). HCA and OPLS-DA could distinguish Sanghuang porus vaninii (Ljub.) with different cultivation methods. Conclusion:Sanghuang porus vaninii (Ljub.) L.W. Zhou & Y.C. Dai in wood is closer to wild Sanghuang porus vaninii (Ljub.) L.W. Zhou & Y.C. Dai than in substitute cultivation. The UPLC characteristic atlas and multi-component content determination method established in this study can provide reference for the quality evaluation of Sanghuang porus vaninii (Ljub.) L.W. Zhou & Y.C. Dai.
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ObjectiveUncommon medicinal herbs are valuable medicinal resources, but their identification is a difficult problem in Chinese medicine due to their particularity and complexity. It is, therefore, urgent to establish a method for the identification of uncommon medicinal herbs. In this study, DNA signature sequence (DSS) tags were used to establish a specific polymerase chain reaction (PCR) identification method for Hibisci Cortex, the origin plant of Hibisci Cortex, and its adulterants. MethodThe candidate DSS tags were obtained from the chloroplast genome sequence analysis, and the DSS tags were verified by DNA sequencing. The specific identification primers for H. syriacus were designed based on the obtained reliable DSS tags. The PCR reaction conditions were optimized, and the tolerance and feasibility were investigated. ResultA DSS tag for identification of H. syriacus was obtained from the comparison of sequencing results of the amplified products with DSS, which revealed the distinguishing characteristics of Hibisci Cortex and its adulterants. A pair of specific primers for H. syriacus was designed according to the DSS tag. After PCR amplification and gel electrophoresis with the primers, a single bright band of about 270 bp was observed from H. syriacus, which did not appear in the four adulterants. ConclusionA DSS tag obtained in this study can be used to identify H. syriacus. The specific primers designed based on this DSS tag can accurately and simply identify the original plant of Hibisci Cortex and its adulterants, which provides a new method and idea for the molecular identification of genuine and counterfeit products of Hibisci Cortex.
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Objective:To establish the fingerprint and stoichiometric analysis mode of Ultra Performance Liquid Chromatography Tandem Quadrupole Time-of-Flight Mass Spectrometry (UPLC-Q-TOF-MS) of Fritillaria anhuiensis Bulbus, so as to provide reference for its quality evaluation and standard formulation. Methods:By setting the CORTECS C18 column at 4.6 mm×150 mm, 2.7 μm with the mobile phases of acetonitrile-0.1% formic acid and 10 mmol/L aqueous ammonium formate for gradient elution at a flow rate of 0.4 ml/min and an injection volume of 2.0 μl. The TCM fingerprint similarity evaluation system (2012 version) was used to evaluate 9 batches of Fritillaria anhuiensis Bulbus samples. By using Liquid Chromatography-Mass Spectrometry (LC-MS) technique to make quantity analysis and by combining cluster analysis, principal component analysis and orthogonal least squares-discriminant analysis to make overall quality evaluation. Results:The fingerprint profiles of different batches of Fritillaria anhuiensis Bulbus were established and 21 common peaks were identified, and 12 of them were initially identified. Cluster analysis, principal component analysis and orthogonal least squares-discriminant analysis were used to cluster the nine batches of Fritillaria anhuiensis Bulbus into three categories. Conclusion:The fingerprint established in this study combined with the chemical pattern recognition method are highly sensitive and specific, which could reflect the overall characteristics and differences of Fritillaria anhuiensis Bulbus, providing reference for the quality evaluation of Fritillaria anhuiensis Bulbus and standardization of it.