Issue 5, 2015

A hierarchical cluster analysis of ten index constituents based on microwave-assisted extraction by UHPLC-MS/MS for the evaluation and quality control of Cortex Juglandis Mandshuricae

Abstract

A novel and rapid microwave-assisted extraction (MAE) was optimized and compared with that of ultrasound-assisted extraction and heat reflux extraction for the quality control of ten index constituents in Cortex Juglandis Mandshuricae (CJM) based on a developed ultra-high performance liquid chromatography-tandem mass spectrometry method. The operation of MAE optimized through orthogonal array design experiments was performed at 70 °C for 8 min with ethanol–water (70 : 30, v/v) as the extracting solvent. The chromatographic separation was completed in a Waters ACQUITY UPLC® BEH Phenyl column (50 mm × 2.1 mm, 1.7 μm) with a gradient elution of acetonitrile and 0.1% (v/v) aqueous formic acid at a flow rate of 0.2 mL min−1. The method developed was validated with acceptable linearity (r > 0.999), intra- and inter-day precision, reproducibility, and extraction recoveries, and was applied successfully to analyzing 15 batches of CJM obtained from different regions of Northern China. The results were differentiated and classified by hierarchical cluster analysis (HCA), which indicated that the influence of CJM cultivation regions on the contents of index constituents was very obvious. The developed procedure is a promising analytical tool for the overall quality control of CJM.

Graphical abstract: A hierarchical cluster analysis of ten index constituents based on microwave-assisted extraction by UHPLC-MS/MS for the evaluation and quality control of Cortex Juglandis Mandshuricae

Article information

Article type
Paper
Submitted
15 Oct 2014
Accepted
02 Jan 2015
First published
05 Jan 2015

Anal. Methods, 2015,7, 1816-1824

Author version available

A hierarchical cluster analysis of ten index constituents based on microwave-assisted extraction by UHPLC-MS/MS for the evaluation and quality control of Cortex Juglandis Mandshuricae

P. Zhao, L. Zhao, C. Qi, G. Wang and X. Hou, Anal. Methods, 2015, 7, 1816 DOI: 10.1039/C4AY02451F

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