Application of multivariate statistical analysis and thinking in quality control of Chinese medicine

2014 ◽  
Keyword(s):  
Quality Control ◽  
Statistical Analysis ◽  
Chinese Medicine ◽  
Multivariate Statistical Analysis ◽  
Multivariate Statistical

Quality control of herbal medicines by using spectroscopic techniques and multivariate statistical analysis

2009 ◽  
Vol 48 (2) ◽  
pp. 134-141 ◽  
Author(s):  
Sunil Kumar Singh ◽  
Sunil Kumar Jha ◽  
Anand Chaudhary ◽  
R. D. S. Yadava ◽  
S. B. Rai
Keyword(s):  
Quality Control ◽  
Statistical Analysis ◽  
Multivariate Statistical Analysis ◽  
Herbal Medicines ◽  
Spectroscopic Techniques ◽  
Multivariate Statistical

scholarly journals Phytochemical analysis of trifoliate orange during fermentation by HPLC–DAD–ESI–MS/MS coupled with multivariate statistical analysis

2020 ◽  
Author(s):  
Dan Gao ◽  
Chong Woon Cho ◽  
Le Ba Vinh ◽  
Jin Hyeok Kim ◽  
Young Ho Kim ◽  
...  
Keyword(s):  
Quality Control ◽  
Statistical Analysis ◽  
Multivariate Statistical Analysis ◽  
Partial Least Square ◽  
Array Detector ◽  
Phytochemical Analysis ◽  
Chemical Compositions ◽  
Trifoliate Orange ◽  
Multivariate Statistical ◽  
Esi Ms

AbstractDuring the process of fermentation, the chemical compositions of trifoliate orange (Poncirus trifoliate (L). Raf) changed greatly. To provide a completely phytochemical profile, high-performance liquid chromatography-diode array detector-hyphenated with tandem mass spectrometry (HPLC–DAD–ESI-MS/MS) has been successfully applied to screen and identify the unknown constituents of trifoliate orange during fermentation, which make it available for the quality control of fermented products. Multivariate statistical analysis was performed to classify the trifoliate oranges based on the status of fermentation. A total of 8 components were identified among the samples. Hierarchical Clustering Analysis (HCA) and Principal Component Analysis (PCA) demonstrated the fermented and unfermented trifoliate oranges were obviously different, an effective and reliable Partial Least Square Discriminate Analysis (PLS-DA) technique was more suitable to provide accurate discrimination of test samples based their different chemical patterns. Furthermore, a permutation validated the reliability of PLS-DA and variable importance plot revealed that the characterized syringing, naringin, and poncirin showed the high ability to distinguish the trifoliate oranges during fermentation. The present investigation could provide detailed information for the quality control and evaluation of trifoliate oranges during the fermentation process.

Difference of Chemical Compositions in Fu Zheng Fang with Different Dosage Forms Based on HPLC-Q-Exactive Orbitrap/MS Combined with Multivariate Statistical Analysis

2020 ◽  
Vol 16 ◽  
Author(s):  
Yujiao Hua ◽  
Fen Xie ◽  
Shijun Zhou
Keyword(s):  
Statistical Analysis ◽  
Chinese Medicine ◽  
Multivariate Statistical Analysis ◽  
Chemical Compositions ◽  
Multivariate Statistical ◽  
Clear Cut ◽  
Medicine Prescription ◽  
Positive Mode ◽  
Q Exactive ◽  
Orbitrap Ms

Background: Fu Zheng Fang (FZF) is an important Chinese medicine prescription for tumor treatment in our hospital, which has two different types, traditional Chinese medicine (TCM) decoction pieces and TCM formula granules. Objective: To determine the effective composition of the drug FZF. Methods: In this research, FZF decoction pieces and FZF formula granules were collected and their composition determined by HPLC-Q-Exactive Orbitrap/MS, multivariate statistical analysis was applied to distinguish differential metabolite patterns between two groups. Results: A clear cut difference in the composition of the two groups was observed. 124 differential chemical compositions could be identified in positive mode, while 59 differential chemical compositions could be identified in negative mode. The differential chemical compositions were mainly concentrated in flavonoids, organic acids, fatty acids, amino acids compounds, and presenting different change rules, mainly involved in the flavonoid biosynthesis, flavone and flavonol biosynthesis two metabolic pathways. Conclusion: This study provides basic information that may be of use in the formulation of the drug of different dosages and their efficacy.

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