基于经验模态分解的两种混合氨基酸太赫兹光谱分析研究  

Terahertz Spectrum Analysis for Binary Amino Acids Mixture Based on Empirical Mode Decomposition

作　　者：刘婧[1] 刘海顺[2] 左剑[2] 张存林[1,2] 赵跃进[1] 梁美彦 LIU Jing;LIU Hai-shun;ZUO Jian;ZHANG Cun-lin;ZHAO Yue-jin;LIANG Mei-yan(School of Optoelectronics,Beijing Institute of Technology,Beijing 100081,China;Key Laboratory of Terahertz Optoelectronics,Ministry of Education,Capital Normal University,Beijing 100048,China;Department of Electronic Information Engineering,Shanxi University,Taiyuan 030013,China)

机构地区：[1]北京理工大学,北京100081 [2]首都师范大学,北京100048 [3]山西大学,山西太原030013

出　　处：《光谱学与光谱分析》2020年第10期3061-3065,共5页Spectroscopy and Spectral Analysis

基　　金：北京成像理论与技术高精尖创新中心项目(19530012003);国家重大仪器专项基金项目(2012YQ140005-09-01);国家自然科学基金青年科学基金项目(11804209)资助。

摘　　要：L-苯丙氨酸和L-酪氨酸在合成神经递质和激素的过程中起到了重要的作用。这两种氨基酸具有极为相似的分子结构,但在生物功能上却具有明显区别。前人的研究表明,这两种氨基酸在低频振动上存在显著差异。近年来,太赫兹(THz)光谱学技术作为研究生物分子低频动力学的有效手段被广泛应用,通过太赫兹光谱对氨基酸进行研究,对进一步了解蛋白质和相关生物活性具有重要意义。多变量校准方法已成功应用于太赫兹多组分光谱数据定量分析研究中。然而,传统校准技术由于仅在光谱和目标之间建立单个模型预测未知样品,其预测性能有时仍不尽人意。因此,具有更好精度的集成建模方法(ensemble modeling method)应运而生。集成建模的基本概念是组合多个单独模型的优势以产生更好的预测结果。由黄锷博士提出的经验模态分解(EMD)的方法,可以将信号自适应地分解为一系列的本征模式函数(IMF),成功地应用于信号和光谱处理中。基于该方法的信号分析也已在太赫兹波段开始使用。然而,在对物质进行定量分析的过程中,目前还没有报道基于EMD方法的太赫兹光谱偏最小二乘(PLS)回归的相关工作。提出了一种基于PLS的EMD分析,并对不同浓度氨基酸混合物的太赫兹光谱进行了定量研究。具体而言,原始的太赫兹时域信号首先通过EMD手段在不同频段被分解为一系列的IMF和一个残差函数。随后,将前几个IMF相加作为一个整体(此处研究了前两、三、四和五个IMF叠加的结果),对其进行吸收光谱的重建。最后,建立PLS回归模型,用于进一步的物质定量分析。预测结果表明,与原始吸收光谱及其他分解后重组光谱的PLS结果相比,基于前四个IMF信号之和的吸收谱具有更高的R(0.9961)和最小的RMSEP(0.0198)。由此可知,EMD-PLS法可以在太赫兹波段对两种氨基酸混合物进行有效地定量分析,实现�L-Phenylalanine and L-Tyrosineplay essential roles in synthesizing neurotransmitters and hormones.The two amino acids have similar structures which lead to an obviously functional distinction between the two amino acids.Previous studies have shown that there are remarkable differences between the two amino acids on low-frequency vibrations.Recently,terahertz(THz)spectroscopy has been proven to be a useful technique on studying low-frequency dynamic of biologic molecules.Many multivariate calibration methods have been successfully applied to quantitative analysis multi-components spectra data due to the linear behaviors revealed by terahertz absorption spectra.However,the predictive performances of traditional calibration techniques are sometimes unsatisfied as only a single model is built between spectra and targets to predict the unknown samples.Thus,the ensemble modeling method with better accuracy came into being.The empirical mode decomposition(EMD)method,firstly proposed by Dr.Huang in 1998,is used to decompose the signal into a set of intrinsic mode functions(IMF)self-adaptively,which is widely applied in signal and spectra processing.We proposed an empirical mode decomposition(EMD)based partial least squares(PLS)method for terahertz spectra quantitative analysis on amino acids mixture with various concentrations.The terahertz time signals were decomposed into a series of intrinsic mode functions(IMF)with different frequencies by the EMD method.The several top IMFs(from 2 to 5)based absorption spectra were obtained for quantitative analysis by employing PLS.The predicted results indicated that the top four IMFs based absorption spectra acquired higher R(0.9961)and lowered RMSEP(0.0198)compared tothe single PLS regression and theother top several IMFs’results.Thus,the successful application with EMD-PLS method manifests the effectiveness in quantitative analysis of binary mixtures within the THz region.

关 键 词：太赫兹 经验模态分析 偏最小二乘法回归 氨基酸 

分 类 号：O434.3[机械工程—光学工程]