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Current Analytical Chemistry

Editor-in-Chief

ISSN (Print): 1573-4110
ISSN (Online): 1875-6727

Current Methodology for Detection, Identification and Quantification of Genetically Modified Organisms

Author(s): Marta Hernandez, David Rodriguez-Lazaro and Alejandro Ferrando

Volume 1, Issue 2, 2005

Page: [203 - 221] Pages: 19

DOI: 10.2174/1573411054021574

Price: $65

Abstract

During recent years, arable land used for transgenic crops has undergone an exponential increase globally, and the tendency to augment not only the cultivated area but also the number of modified genetic traits is rather evident. However, public perception and confidence regarding genetically modified organisms (GMOs) have not paralleled this increase. Moreover, a general antipathy towards GMOs is nowadays detectable especially in Europe and there is an apparent lack of information for the consumer in many cases. To counterbalance the social alarm caused by the presence of GMO-derived ingredients in the commercial food chain, competent authorities have established appropriate regulations to guarantee the consumers right to information and choice. In this regard, several countries have established a strict labelling policy for products containing or derived from GMO. In order to achieve these labelling requirements different approaches have been taken with the aim of detection and quantification of the presence of GMO traces, using either protein- or DNA-based methods. In this paper we review the different methodologies that are being applied to GMO studies. We describe the state-of-the-art instrumentation and technologies currently used, as well as the most recent advances in analytical systems for the detection, identification and quantification of GMOs. In addition to methodological considerations, important practical aspects such as the implementation of the analytical system into the food and feed chains will be considered. Finally, the importance of standardised/validated methods and future technological trends in the field are discussed.

Keywords: gmo, pcr, detection, identification, quantification, real-time

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