| 光谱学与光谱分析 |
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| Discrimination of GMOs Using Terahertz Spectroscopy and CS-SVM |
| CHEN Tao, LI Zhi, HU Fang-rong, YIN Xian-hua, XU Chuan-pei* |
| Guangxi Key Laboratory of Automatic Detecting Technology and Instruments, School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004, China |
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Abstract This paper develops an effective identification method to discriminate genetically modified (GM) and non-GM organisms. The method is proposed based on terahertz (THz) spectroscopy and support vector machines optimized by Cuckoo Search algorithm (CS-SVM). In this study, the THz spectra of three GM and non-GM soya seed samples were obtained by using terahertz time-domain spectroscopy (THz-TDS) system between 0.2 and 1.2 THz. Then, the SVM model is employed to distinguish GM and non-GM soya seeds, in which the two crucial parameters, including the penalty factor and kernel parameter, are optimized by CS algorithm. The experimental results show that THz spectroscopy combined with CS-SVM can provide a rapid, reliable and non-invasive method for GMOs and non-GMOs discrimination.
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Received: 2016-03-23
Accepted: 2016-07-01
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Corresponding Authors:
XU Chuan-pei
E-mail: xucp@guet.edu.cn
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