Pyrolysis GC-MS-based metabolite fingerprinting for quality evaluation of commercial Angelica acutiloba roots

• Published in: Journal of bioscience and bioengineering Vol. 109; no. 1; pp. 89 - 93
• Main Authors: Tianniam, Sukanda, Bamba, Takeshi, Fukusaki, Eiichiro
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.01.2010; Elsevier
• Subjects: ANGELICA; Angelica - chemistry; Angelica acutiloba; Biological and medical sciences; Biotechnology; CALIDAD; Discriminant Analysis; Fundamental and applied biological sciences. Psychology; Gas Chromatography-Mass Spectrometry - methods; http://www.fao.org/aos/agrovoc#c_4770; http://www.fao.org/aos/agrovoc#c_6400; http://www.fao.org/aos/agrovoc#c_6651; http://www.fao.org/aos/agrovoc#c_7377; http://www.fao.org/aos/agrovoc#c_8803; Least-Squares Analysis; Medicine, Chinese Traditional; METABOLITE; Metabolite fingerprinting; METABOLITES; METABOLITOS; Metabolomics - methods; METHODE STATISTIQUE; METODOS ESTADISTICOS; Multivariate analysis; Partial least square discriminant analysis; Pattern Recognition, Automated; Plant Extracts - chemistry; Plant Roots - chemistry; Principal Component Analysis; Pyrolyser gas chromatography mass spectrometer; QUALITE; QUALITY; Quality Control; RACINE; RAICES; ROOTS; STATISTICAL METHODS; Angelica acutiloba; Partial least square discriminant analysis; Pyrolyser gas chromatography mass spectrometer; Multivariate analysis; Metabolite fingerprinting; Principal component analysis; Root; Metabolite; Gas chromatography; Dicotyledones; Fingerprint method; Quality; Angiospermae; Angelica; Spermatophyta; Umbelliferae
• ISSN: 1389-1723; 1347-4421
• DOI: 10.1016/j.jbiosc.2009.06.025

Metabolite fingerprinting was applied in the attempt to evaluate the quality of Angelica acutiloba dried roots (Yamato-toki). A pyrolyser coupled to a gas chromatography mass spectrometer (PY-GC-MS) was used to obtain higher chemical universality by analyzing whole compounds including high molecular weight metabolites. The machine was relatively fast and easy to use, with no sample preparation procedure required. Multivariate pattern recognition methods, specifically principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA), were successful in discriminating various toki samples. In addition, an enhanced understanding of the dominant relationship of cultivation area to quality evaluation was conceptualized and therefore applied to the construction of a PLS-DA classification model which provided the basis for accurate and reliable predictivity.