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International Journal of Analytical Chemistry
Volume 2017, Article ID 5125329, 7 pages
Research Article

Rapid Separation of Indole Glucosinolates in Roots of Chinese Cabbage (Brassica rapa Subsp. Pekinensis) by High-Performance Liquid Chromatography with Diode Array Detection

1Centre for the Research and Technology for Agro-Environment and Biological Sciences (CITAB), Universidade de Trás-os-Montes e Alto Douro (UTAD), Quinta de Prados, 5000-801 Vila Real, Portugal
2Agronomy Department, Universidade de Trás-os-Montes e Alto Douro (UTAD), Quinta de Prados, 5000-801 Vila Real, Portugal

Correspondence should be addressed to Alfredo Aires; tp.datu@aoderfla

Received 26 April 2017; Accepted 16 May 2017; Published 13 June 2017

Academic Editor: Mohamed Abdel-Rehim

Copyright © 2017 Alfredo Aires and Rosa Carvalho. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Glucosinolates are a class of sulphur-containing plant compounds with diverse biological properties. They have been found exclusively in the Brassicaceae family plants and studied exhaustively in biosynthetic and application perspectives. The aim of this current study is to present a simple and updated method to quantify indole glucosinolate content in hairy root cultures of Chinese cabbage by HPLC-DAD-UV/Vis. Method validation controls were performed and recovery experiments were assayed. The data was statically treated and compared with published works. The current method allowed a feasible identification of indole glucosinolates and it was possible to identify accurately three indole glucosinolate compounds (glucobrassicin, 4-methoxyglucobrassicin, and 1-methoxyglucobrassicin) in roots of Chinese cabbage. The method demonstrated a good linearity (), a good precision, and selectivity sensitivity. In conclusion, this protocol provides an accessible method to extract and quantify glucosinolates in plant samples. Thus, based on our results, the method is valid and can be extended to other plant or food matrices.