At present, the methods used to detect GMOs are all chemical in nature. They test the chemical makeup of certain proteins, or in most cases, the sequence of chemical bases in DNA. This project, on the other hand, aims to investigate the potential of near infrared imaging, a physical method, to tell whether or not soybeans and barley grains are GMOs.
The technology used in this project is called near infrared (NIR) imaging. The instrument used to look at grains and determine their NIR fluorescence profiles consists of a camera that overlaps an image of the grain with the wavelengths of light being emitted from any given point in the image (spectrophotometer). Therefore, you see not only an image, but you also have a profile of the molecules present at each spot in the picture.
To do this, an image is created with receptiveness at various wavelengths of light. Starting at 900 nanometres, images are taken at increments of 10 nanometres all the way up to 1700 nanometres. The images at each of the wavelenths are overlapped to give a composite picture of the overall chemical makeup of the grain. Each kernel has to be measured twice (both sides of the kernel) to get as much information as possible.
Principal Component Analysis (PCA) can be performed on the data. PCA is used to reduce the data dimensionality.
In total, more than 640 spectra were collected from different varieties of soybean and barley, some of them transgenic. Preliminary results have shown that there is, in fact, a slight difference in the spectra collected between GM and conventional grains for both soybean and the barley. The fact that larger differences were not detected may have a lot to do with the challenge of statistically interpreting the data. As is to be expected, the sheer quantity of data input made for considerable noise coming from factors that have nothing to do with the GM status of the test material.
Presentation: Non-PCR based methods for GM detection
Public Deliverables of the Co-Extra project
|NAME / ORGANISATION||CONTACT INFORMATION|
Centre Wallon de Recherches Agronomiques (CRA-W), Belgium
Iowa State University, USA