Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 2 de 2
Filter
Add more filters











Database
Language
Publication year range
1.
Zhong Yao Cai ; 33(6): 874-8, 2010 Jun.
Article in Chinese | MEDLINE | ID: mdl-21049608

ABSTRACT

OBJECTIVE: To establish the quality standard of oil-processed Radix Angelica sinensis. METHODS: Combined traditional identification, TLC and fingerprints of wine-processed Radix Angelica sinensis to control quality of oil-processed Radix Angelica sinensis. And referring to China Pharmacopoeia of 2005 edition, water, ash, and extract were also detected. RESULTS: The content of water, total ash, extract representatively was 7.30%, 8.70% and 50.9%. Eleven fingerprint peaks were defined, The eleven common peaks were appointed as fingerprint peaks by analyzing 14 representative samples, all the fingerprint peaks were quantified grounded on the peak of Ferulic acid. and quantified rested on the peak of ferulic acid. CONCLUSION: A multicomponent quantitative method for oil-processed Radix Angelica sinensis is established. The established method is feasible. The quality control standards of the oil-processed Radix Angelica sinensis is normative, systematic and accurate.


Subject(s)
Angelica sinensis/chemistry , Coumaric Acids/analysis , Drugs, Chinese Herbal/chemistry , Plants, Medicinal/chemistry , Chromatography, High Pressure Liquid , Drugs, Chinese Herbal/analysis , Drugs, Chinese Herbal/standards , Plant Roots/chemistry , Quality Control , Reproducibility of Results , Technology, Pharmaceutical/methods , Water/analysis
2.
Yao Xue Xue Bao ; 45(9): 1155-9, 2010 Sep.
Article in Chinese | MEDLINE | ID: mdl-21351572

ABSTRACT

The paper reports the development of a quality evaluation method for Angelica different processed products. The data of high-performance liquid chromatography, water, total ash and extract were analyzed with SPSS Clementine 11.0 software. Discriminant analysis (DA) established the classification model and parameter for Angelica different processed products. Fish's discriminant functions of Angelica different processed products were generated using 8 predictor variables selected from 59 indexes. The correct rate of discriminating back substitution is 96.7%. Angelica different processed products can be accurately and reliably recognized and validated with DA of SPSS Clementine 11.0 software.


Subject(s)
Angelica/chemistry , Data Mining , Drugs, Chinese Herbal/analysis , Plants, Medicinal/chemistry , Chromatography, High Pressure Liquid/methods , Drugs, Chinese Herbal/standards , Plant Roots/chemistry , Quality Control , Software
SELECTION OF CITATIONS
SEARCH DETAIL