光谱学与光谱分析, 2017, 37 (2): 618, 网络出版: 2017-06-20
基于太赫兹光谱技术与CS-SVM的转基因产品鉴别
Discrimination of GMOs Using Terahertz Spectroscopy and CS-SVM
太赫兹光谱 转基因生物 支持向量机 布谷鸟搜索算法 Terahertz spectroscopy Genetically modified organisms Support vector machines Cuckoo Search algorithm
摘要
提出了一种基于太赫兹(THz)光谱技术以及布谷鸟搜索(CS)算法优化支持向量机(SVM)的有效的转基因产品鉴别方法(CS-SVM)。 实验采用太赫兹时域光谱(THz-TDS)系统测量了三种转基因大豆种子及其亲本样品在02~12 THz波段的THz光谱, 并采用SVM方法对转基因和非转基因大豆种子进行了分类鉴别研究, 其中SVM的两个重要参数(惩罚因子和核参数)采用CS算法进行优化。 实验结果表明, 应用THz光谱技术结合CS-SVM方法为转基因和非转基因生物的检测和识别提供了一种快速、 无损和可靠的分析方法。
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 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.
陈涛, 李智, 胡放荣, 殷贤华, 许川佩. 基于太赫兹光谱技术与CS-SVM的转基因产品鉴别[J]. 光谱学与光谱分析, 2017, 37(2): 618. 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.