The Spectrum-activity Integrated Fingerprint: A Effective Method for the Quality Evaluation of Herbal Medicines

In this study, a new method was developed for the comprehensive quality evaluation (QE) of Artemisia capillaris Thunb. (A. capillaris, named Yinchenhao in Chinese), which is one of the most commonly used herbal medicines (HMs). First, fingerprints of 31 batch samples of A. capillaris were determined by HPLC, the reference fingerprint was established, and the common peaks were assigned. Second, the components of common peaks in the HPLC fingerprints were identified by ultrafast liquid chromatography- (UFLC-) Q-TOF-MS/MS. Finally, the contents of the components unambiguously confirmed by reference substances were determined, and the correlation between the contents of chlorogenic acid and the contents of others was analyzed. The results showed that there were 20 common peaks in the HPLC fingerprints of 31 batch samples. The components of these 20 common peaks were identified as ten organic acids, eight flavonoids, and two others. Among nine organic acids such as 1-caffeoylquinic acid, neochlorogenic acid, chlorogenic acid, caffeic acid, cryptochlorogenic acid, 1,3-dicaffeoylquinic acid, 3,4-dicaffeoylquinic acid, 3,5-dicaffeoylquinic acid, and 4,5-dicaffeoylquinic acid, three flavonoids such as rutin, hyperoside, and isoquercetin, and one other p-hydroxyacetophenone, a total of 13 ones were unambiguously identified by comparison with reference substances; one caffeoylquinic acid glucoside and one flavone di-C-glucoside were detected in A. capillaris for the first time. There were some differences in the contents of 13 components in different samples; chlorogenic acid could be regarded as the quality marker of A. capillaris. The current established method in this study can be used for the comprehensive QE of A. capillaris and can also provide reference for the QE of the other HMs.

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ChemInform Abstract: The Plant Origins of Herbal Medicines and Their Quality Evaluation

ChemInform ◽

10.1002/chin.200242294 ◽

2010 ◽

Vol 33 (42) ◽

pp. no-no

Author(s):

Sansei Nishibe

Keyword(s):

Quality Evaluation ◽

Herbal Medicines

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Quality Evaluation of Phellodendri Chinensis Cortex by Fingerprint–Chemical Pattern Recognition

Molecules ◽

10.3390/molecules23092307 ◽

2018 ◽

Vol 23 (9) ◽

pp. 2307 ◽

Cited By ~ 9

Author(s):

Xuexiao Cao ◽

Lili Sun ◽

Di Li ◽

Guangjiao You ◽

Meng Wang ◽

...

Keyword(s):

Pattern Recognition ◽

Discriminant Analysis ◽

Least Squares ◽

Partial Least Squares ◽

High Performance ◽

Quality Evaluation ◽

Herbal Medicines ◽

Principal Component ◽

Hierarchical Cluster ◽

Maximum Thickness

Phellodendri Chinensis Cortex (PCC) and Phellodendri Amurensis Cortex (PAC) are increasingly being used as traditional herbal medicines, but they are often mistaken for each other. In this study, the fingerprints of PCC from six different geographical sources were obtained by high-performance liquid chromatography, and multivariate chemometric methods were used for comprehensive analysis. Two unsupervised pattern recognition models (principal component analysis and hierarchical cluster analysis) and a supervised pattern recognition model (partial least squares discriminant analysis) were established on the basis of the chemical composition and physical traits of PCC and PAC. PCC and PAC were found to be distinguishable by these methods. The PCC category was divisible into two categories, one with more crude cork and a maximum thickness of ~1.5 mm, and the other with less net crude cork and a maximum thickness of 0.5 mm. According to the model established by partial least squares discriminant analysis (PLS-DA), the important chemical marker berberine hydrochloride was obtained and analyzed quantitatively. From these results combined with chemometric and content analyses, the preliminary classification standards for phellodendron were established as three grades: superior, first-order and mixed. Compared with the traditional identification methods of thin layer chromatography identification and microscopic identification, our method for quality evaluation is relatively simple. It provides a basis and reference for identification of PCC and enables establishment of grade standards. It also could be applied in quality control for compound preparations containing PCC.

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