title: Discrimination of transgenic soybean seeds by terahertz spectroscopy.
abstract: Discrimination of genetically modified organisms is increasingly demanded by legislation and consumers worldwide. The feasibility of a non-destructive discrimination of glyphosate-resistant and conventional soybean seeds and their hybrid descendants was examined by terahertz time-domain spectroscopy system combined with chemometrics. Principal component analysis (PCA), least squares-support vector machines (LS-SVM) and PCA-back propagation neural network (PCA-BPNN) models with the first and second derivative and standard normal variate (SNV) transformation pre-treatments were applied to classify soybean seeds based on genotype. Results demonstrated clear differences among glyphosate-resistant, hybrid descendants and conventional non-transformed soybean seeds could easily be visualized with an excellent classification (accuracy was 88.33% in validation set) using the LS-SVM and the spectra with SNV pre-treatment. The results indicated that THz spectroscopy techniques together with chemometrics would be a promising technique to distinguish transgenic soybean seeds from non-transformed seeds with high efficiency and without any major sample preparation.
authors: School of Biotechnology and Food Engineering, Hefei University of Technology, Hefei 230009, China.|Intelligent Control and Compute Vision Lab, Hefei University, Hefei 230601, China.
authors: Wei
authors: W
authors: Liu
authors: School of Biotechnology and Food Engineering, Hefei University of Technology, Hefei 230009, China.
authors: Changhong
authors: C
authors: Liu
authors: Department of Food, Nutrition and Packaging Sciences, Clemson University, Clemson, SC 29634, United States.
authors: Feng
authors: F
authors: Chen
authors: Rice Research Institute, Anhui Academy of Agricultural Sciences, Hefei 230031, China.
authors: Jianbo
authors: J
authors: Yang
authors: School of Biotechnology and Food Engineering, Hefei University of Technology, Hefei 230009, China.|School of Medical Engineering, Hefei University of Technology, Hefei 230009, China.
authors: Lei
authors: L
authors: Zheng
mesh_terms: D016002:Discriminant Analysis; D016018:Least-Squares Analysis; D030821:Plants, Genetically Modified / Q000737:chemistry; D025341:Principal Component Analysis; D012639:Seeds / Q000737:chemistry; D013025:Glycine max / Q000737:chemistry* / Q000378:metabolism; D060388:Support Vector Machine; D055068:Terahertz Spectroscopy