DETECTION OF GENETICALLY MODIFIED SUGARCANE BY USING TERAHERTZ SPECTROSCOPY AND CHEMOMETRICS
Abstract
A methodology is proposed to identify genetically modified sugarcane from non-genetically modified sugarcane by using terahertz spectroscopy and chemometrics techniques, including linear discriminant analysis (LDA), support vector machine-discriminant analysis (SVM-DA), and partial least squares-discriminant analysis (PLS-DA). The classification rate of the above mentioned methods is compared, and different types of preprocessing are considered. According to the experimental results, the best option is PLS-DA, with an identification rate of 98%. The results indicated that THz spectroscopy and chemometrics techniques are a powerful tool to identify genetically modified and non-genetically modified sugarcane.
About the Authors
J. . Liu
College of Food Science, Southwest University; Guilin University of Electronic Technology
Russian Federation
Russian Federation
H. . Xie
School of Electrical Engineering, Jiujiang University
Russian Federation
Russian Federation
B. . Zha
School of Electrical Engineering, Jiujiang University
Russian Federation
Russian Federation
W. . Ding
School of Electrical Engineering, Jiujiang University
Russian Federation
Russian Federation
J. . Luo
School of Electrical Engineering, Jiujiang University
Russian Federation
Russian Federation
C. . Hu
Guilin University of Electronic Technology
Russian Federation
Russian Federation
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Review
For citations:
Liu J., Xie H., Zha B., Ding W., Luo J., Hu C. DETECTION OF GENETICALLY MODIFIED SUGARCANE BY USING TERAHERTZ SPECTROSCOPY AND CHEMOMETRICS. Zhurnal Prikladnoii Spektroskopii. 2018;85(1):129-134. (In Russ.)
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