Spectroscopy and Spectral Analysis, Volume. 37, Issue 2, 618(2017)
Discrimination of GMOs Using Terahertz Spectroscopy and CS-SVM
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 02 and 12 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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CHEN Tao, LI Zhi, HU Fang-rong, YIN Xian-hua, XU Chuan-pei. Discrimination of GMOs Using Terahertz Spectroscopy and CS-SVM[J]. Spectroscopy and Spectral Analysis, 2017, 37(2): 618
Received: Mar. 23, 2016
Accepted: --
Published Online: Jun. 20, 2017
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