Nondestructive determination of herbicide-resistant genetically modified soybean seeds using near-infrared reflectance spectroscopy

The objective of this study was to evaluate the potential of near-infrared reflectance spectroscopy (NIRS) to differentiate the herbicide-resistant genetically modified (GM) and non-GM soybean seeds. Principal component analysis (PCA) and partial least squares discriminant analysis (PLSDA) were used to classify soybeans with different genes into two groups: genetically modified organisms (GMO) and non-GMO. Calibrations were developed using PLSDA regression with cross-validation. Differences between GM and non-GM soybeans do exist, and excellent classification can be obtained after optimising spectral pretreatment. The PLSDA model using the second derivative pretreatment of the raw spectra had the best calibration and prediction abilities, with 97% accuracy. The results of the present study show that NIRS, together with chemometrics techniques, can be used to identify GM soybeans, thus circumventing time-consuming, costly and laborious chemical and sensory analyses.