alexa Gas Chromatographic Determination of Prochloraz in Ten Herbal Medicines
ISSN : 2153-2435

Pharmaceutica Analytica Acta
Open Access

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Research Article

Gas Chromatographic Determination of Prochloraz in Ten Herbal Medicines

Jialun Wu1*, Jing Zhao1, Tianyu Wang1, Aoran Chen1 and Jian Xue2

1Ministry of Agriculture Key Laboratory of Molecular Biology of Crop, Pathogens and Insects, Institute of Pesticide and Environmental Toxicology, Zhejiang University, Hangzhou 310029, China

2Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100193 China

*Corresponding Author:
Dr. Jialun Wu
Ministry of Agriculture Key Laboratory of Molecular Biology of Crop Pathogens and Insects
Institute of Pesticide and Environmental Toxicology
Zhejiang University, Hangzhou 310029, China
Tel: 0086 0571 86971221
Fax: 0086 0571 86971221
E-mail: [email protected]

Received date: May 25, 2011; Accepted date: July 19, 2011; Published date: July 21, 2011

Citation: Wu J, Zhao J, Wang T, Chen A, Xue J (2011) Gas Chromatographic Determination of Prochloraz in Ten Herbal Medicines. Pharm Anal Acta 2:128. doi: 10.4172/2153-2435.1000128

Copyright: © 2011 Wu J, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

 

Abstract

A method for determining prochloraz in ten herbal medicines is described. Pesticide standards were fortified into herbal medicines at 3 levels (0.005, 0.01 and 0.05mg/kg). Prochloraz reacts with pyridine hydrochloride and generates a hydrolysate, the 2,4,6-trichlorophenol which responded intensively in GC-ECD. The results showed average recoveries were between 76.6% and 105.1%. The method evidenced good accuracy and precision for monitoring prochloraz in ten herbal medicine samples. The limit of quantification (LOQ) was 0.005mg/kg. It is linear from 0.005 mg/L to 2.000mg/L. The regression equation is y=3816.1x-7.7835, R=0.9997.

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