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How to detect GMO with near-infrared spectroscopy?
Objective : L’Identification and isolation of genetically modified grains (GMO) is a daunting challenge for grain handling systems worldwide. A quick and inexpensive test to distinguish GMO from non-GMO grain for inbound deliveries is required. Iowa State University (IA, USA) wanted to develop an alternative solution to the usual time-consuming and expensive methods (PCR, ELISA). The aim was to develop a non-destructive, real-time and cost-effective method based on near-infrared transmittance (NIT) spectroscopy protocol.
Our solutions: Several multivariate discrimination methods, based on linear, local or non-linear algorithms (such PLS-DA, LWR-DA and Artificial Neural Networks) were tested on large databases (more than 8 000 samples). The best chemometrics method was able to differentiate between Roundup Ready Soybeans (GMO grain) and conventional Soybeans (non-GMO grain) with only 8% of error !
Customer benefits: Thus, the Iowa State University demonstrated that near-Infrared spectrometers can detect pure bulk samples of GM-beans. Every American grain elevator is already equipped with this kind of device. It is thus much easier to set up non-GM grain handing systems to satisfy specific market needs.
Innovation and pragmatism: The implementation of cutting-edge multivariate data analysis methods (Artificial Neural Networks, local modeling) extended the capabilities of existing spectrometers. This provided the grain growers with new detection and quantification capabilities.