Issue 13, 2019

Identification and quantification of seven sesquiterpene lactones in Inula britannica by HPLC-DAD-MS

Abstract

Inula britannica is a traditional Chinese medicinal herb. To identify and evaluate the quality of the main sesquiterpene lactones in Inula britannica from China, a high-performance liquid chromatography-diode-array detection-mass spectrometry (HPLC-DAD-MS) method was developed and validated. The method was successfully applied for the simultaneous characterization and quantification of the seven main sesquiterpene lactones in Inula britannica collected from six different cultivation regions in China. Under the optimal conditions, analysis was performed on a Luna C18 column using a mobile phase gradient of acetonitrile and 0.2% (v/v) acetic acid–water at a flow rate of 1.0 mL min−1 and the detection wavelength was set at 210 nm. For identification purposes, a HPLC-MS was equipped with a turbo ion spray source in the positive mode. The calibration curve showed satisfactory linearity (R2> 0.9993) and limits of detection (LOD) and quantification (LOQ). The relative intra- and inter-day standard deviations were less than 2.7% with accuracies between 99.66% and 100.22%. The RSDs of repeatability and stability were less than 2.45%. The recoveries of the seven analytes were between 98.12% and 101.39% with RSDs of less than 1.70%, a satisfactory level. The content variation of seven compounds was analyzed by a chemometric method (hierarchical cluster analysis). The proposed method could serve as a prerequisite for simultaneous and quantitative analysis of sesquiterpene lactones in Inula britannica materials and products.

Graphical abstract: Identification and quantification of seven sesquiterpene lactones in Inula britannica by HPLC-DAD-MS

Supplementary files

Article information

Article type
Paper
Submitted
16 Jan 2019
Accepted
20 Feb 2019
First published
26 Feb 2019

Anal. Methods, 2019,11, 1822-1833

Identification and quantification of seven sesquiterpene lactones in Inula britannica by HPLC-DAD-MS

T. Wang, S. Guo, S. Zhang, W. Yue, C. Ho and N. Bai, Anal. Methods, 2019, 11, 1822 DOI: 10.1039/C9AY00118B

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