Document Detail


Metabolic profiling of Angelica acutiloba roots utilizing gas chromatography-time-of-flight-mass spectrometry for quality assessment based on cultivation area and cultivar via multivariate pattern recognition.
MedLine Citation:
PMID:  18640606     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Gas chromatography time-of-flight mass spectrometry was applied to elucidate the profiling of primary metabolites and to evaluate the differences between quality differences in Angelica acutiloba (or Yamato-toki) roots through the utilization of multivariate pattern recognition-principal component analysis (PCA). Twenty-two metabolites consisting of sugars, amino and organic acids were identified. PCA analysis successfully discriminated the good, the moderate and the bad quality Yamato-toki roots in accordance to their cultivation areas. The results signified two reducing sugars, fructose and glucose being the most accumulated in the bad quality, whereas higher quantity of phosphoric acid, proline, malic acid and citric acid were found in the good and the moderate quality toki roots. PCA was also effective in discriminating samples derive from different cultivars. Yamato-toki roots with the moderate quality were compared by means of PCA, and the results illustrated good discrimination which was influenced most by malic acid. Overall, this study demonstrated that metabolomics technique is accurate and efficient in determining the quality differences in Yamato-toki roots, and has a potential to be a superior and suitable method to assess the quality of this medicinal plant.
Authors:
Sukanda Tianniam; Lucksanaporn Tarachiwin; Takeshi Bamba; Akio Kobayashi; Eiichiro Fukusaki
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Journal of bioscience and bioengineering     Volume:  105     ISSN:  1347-4421     ISO Abbreviation:  J. Biosci. Bioeng.     Publication Date:  2008 Jun 
Date Detail:
Created Date:  2008-07-21     Completed Date:  2008-09-10     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  100888800     Medline TA:  J Biosci Bioeng     Country:  Japan    
Other Details:
Languages:  eng     Pagination:  655-9     Citation Subset:  IM    
Affiliation:
Department of Biotechnology, Graduate School of Engineering, Osaka University, Suita, Osaka, Japan.
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Amino Acids / analysis,  chemistry*
Angelica / metabolism*
Artificial Intelligence
Carbohydrates / analysis,  chemistry*
Gas Chromatography-Mass Spectrometry / methods*
Gene Expression Profiling / methods*
Multivariate Analysis
Organic Chemicals / analysis,  chemistry
Pattern Recognition, Automated / methods*
Plant Roots / metabolism*
Principal Component Analysis
Quality Control
Chemical
Reg. No./Substance:
0/Amino Acids; 0/Carbohydrates; 0/Organic Chemicals

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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