GMO detection using NIR and chemometrics

  • Fernández Pierna, J.A. , Baeten, V. , Vermeulen, P. , Buhigiro, T. , Berben, G. , Janssen, E. , Dardenne, P. & Fernández Pierna, J.A. (2007). GMO detection using NIR and chemometrics. Poster in: 13th International Conference on Near Infrared Spectroscopy, Umea - Sweden, 15-21 June 2007.
Type Poster
Year 2007
Title GMO detection using NIR and chemometrics
Event name 13th International Conference on Near Infrared Spectroscopy
Event location Umea - Sweden
Label U15-1039-fernandez-2007
Recnumber 332
Event date 15-21 June 2007
Endnote keywords imagerie spectrale
Endnote Keywords grain|kernel|GMO|NIR|NIR imaging|chemometrics|discriminant models|
Abstract The aim of this work is to produce a methodology in order to investigate the potential of NIR spectroscopy and NIR imaging together with chemometrics for GMO (Genetically modified organisms) detection. The initial model matrices to carry out this aim are kernels of soybean and barley coming from different origins and some being transgenic. In this work mainly a qualitative purpose is considered but both qualitative and also quantitative purposes could be taken into consideration. In the case of the qualitative approach, the aim is to define the ability of a discriminant equation to detect the presence of GM material in terms of kernels. For this, analysis of samples of three lots collected in the framework of the KeLDA project (Paoletti et al., 2006): 300 spectra of bulk soybeans were collected and 2870 spectra (1100-2500 nm) of single soybean kernels (with PCR results on single kernels performed in parallel to confirm the results). The data treatment of the spectral data collected corresponds to unsupervised (PCA) and supervised (PLS-DA) techniques. In all data sets the results have shown that a good discrimination could be performed according to the variety and the presence of GM, and from the pattern recognition point of view more interesting approaches in order to make estimations of the statistical properties based on the images combined with the spectral information can be studied. From the results obtained it appears that next to a merely a qualitative detection, there might be a potential to quantify the GM content in Roundup Ready soybean at the kernel level. There is at least a correlation but more work is being done to document this completely and to improve the correlation. This work is perfomed in the framework of the Co-Extra FP6 project (GM and non-GM supply chains: their CO-EXistence and TRAceability - Project number: 007158).
Author address Fernandez Pierna Juan Antonio, Quality Department of Agro-food Products, Walloon Agricultural Research Centre (CRA-W), Chaussée de Namur, 24, B-5030 Gembloux,
Fichier GMO detection using NIR and chemometrics
Caption U15-1039-fernandez-2007.pdf
Authors Fernández Pierna, J.A., Baeten, V., Vermeulen, P., Buhigiro, T., Berben, G., Janssen, E., Dardenne, P., Fernández Pierna, J.A.