Chen Tao, Li Zhi, Yin Xianhua, Hu Fangrong, Hu Cong
Guangxi Key Laboratory of Automatic Detecting Technology and Instruments, School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin, Guangxi 541004, China.
Guangxi Key Laboratory of Automatic Detecting Technology and Instruments, School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin, Guangxi 541004, China.
Spectrochim Acta A Mol Biomol Spectrosc. 2016 Jan 15;153:586-90. doi: 10.1016/j.saa.2015.09.028. Epub 2015 Sep 30.
The objective of this paper was to apply terahertz (THz) spectroscopy combined with chemometrics techniques for discrimination of genetically modified (GM) and non-GM sugar beets. In this paper, the THz spectra of 84 sugar beet samples (36 GM sugar beets and 48 non-GM ones) were obtained by using terahertz time-domain spectroscopy (THz-TDS) system in the frequency range from 0.2 to 1.2 THz. Three chemometrics methods, principal component analysis (PCA), discriminant analysis (DA) and discriminant partial least squares (DPLS), were employed to classify sugar beet samples into two groups: genetically modified organisms (GMOs) and non-GMOs. The DPLS method yielded the best classification result, and the percentages of successful classification for GM and non-GM sugar beets were both 100%. Results of the present study demonstrate the usefulness of THz spectroscopy together with chemometrics methods as a powerful tool to distinguish GM and non-GM sugar beets.
本文的目的是应用太赫兹（THz）光谱结合化学计量学技术来鉴别转基因和非转基因甜菜。本文使用太赫兹时域光谱（THz-TDS）系统在0.2至1.2太赫兹的频率范围内获取了84个甜菜样本（36个转基因甜菜和48个非转基因甜菜）的太赫兹光谱。采用了三种化学计量学方法，即主成分分析（PCA）、判别分析（DA）和判别偏最小二乘法（DPLS），将甜菜样本分为两组：转基因生物（GMO）和非转基因生物（non-GMO）。DPLS方法产生了最佳分类结果，转基因和非转基因甜菜的成功分类率均为100%。本研究结果证明了太赫兹光谱与化学计量学方法相结合作为区分转基因和非转基因甜菜的有力工具的有效性。
