Quality evaluation of Angelica acutiloba Kitagawa roots by 1H NMR-based metabolic fingerprinting.
The prices of Angelica acutiloba Kitagawa (yamato-toki) and A. acutiloba Kitagawa var. sukiyamae Hikino (hokkai-toki) are now mainly determined according to the sensory quality determined by experts in addition to the physical properties. This method provides a low reliability result for differentiating and qualifying their qualities. In addition, the quality in terms of pharmacological efficiency is not taken into account for consideration in the ordinary sensory method. A combination of a 1H NMR technique and a multivariate analysis was preliminarily applied for the quality evaluation of both toki roots with regard to their geographical and variety differences. A broad range of metabolites was detected by a single-run 1H NMR spectrometry. Partial least-squares discrimination analysis (PLS-DA), a pattern recognition method, was applied to the 1H NMR spectra of aqueous extracts of toki samples having different sensory qualities. The PLS-DA result showed a clear clustering corresponding to the cultivation area between toki samples cultivated in Hokkaido (Japan) and those cultivated in the southern part of China and the Nara prefecture (Japan), while there was no separation corresponding to the toki's variety and sensory qualities, indicating the inconsistency of the sensory evaluation result. The chemical metabolites contributing to the discrimination of toki samples in relation to pharmacological and sensory properties were reported for the first time. A reliable multivariate calibration model used to predict the sensory quality was successfully carried out by PLS regression.
Tarachiwin
Lucksanaporn
L
Nara Prefectural Small & Medium Sized Enterprises Support Corporation, Nara, Japan.
Katoh
Akira
A
Ute
Koichi
K
Fukusaki
Eiichiro
E
D029969:Angelica / Q000145:classification* / Q000378:metabolism*; D002138:Calibration; D002681:China; D007564:Japan; D016018:Least-Squares Analysis; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D015999:Multivariate Analysis; D010363:Pattern Recognition, Automated / Q000379:methods; D010936:Plant Extracts / Q000737:chemistry; D018517:Plant Roots / Q000378:metabolism*; D011786:Quality Control; D014867:Water / Q000737:chemistry
D010936:Plant Extracts; D014867:Water