基于逆检索-非负最小二乘法的拉曼混合物分析方法研究
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摘要
拉曼光谱因它可以提供非常丰富的结构信息而被看作是一项"指纹"技术,因此拉曼光谱可以被用作物质的定性识别。并且拉曼光谱具有制样简单,不破坏样品,在几乎所有的环境下都可以采集。通常认为拉曼光谱只能提供纯物质的结构信息,故利用拉曼光谱分析混合物的成分是有难度的。在便携式拉曼光谱仪、光谱数据库和化学计量学的基础上,开发了一种快速的混合物鉴别方法。根据基于小波域的自动精确峰值检测拉曼光谱的特点,对经典的逆搜索过程进行了改进。匹配质量可以用计算混合物和数据库中相减光谱中的负比率(按最小比例计算反向匹配峰的比值),提出一种基于改进的逆搜索和非负最小二乘法(Reverse searching and non-negative least squares,RSearch-NNLS),用于混合物分析。方法包括以下步骤:1)通过Whittaker平滑、ariPLS基线校正以及连续小波变换建立纯物质的拉曼光谱库;2)通过逆检索法对采集到的混合物拉曼光谱进行定性分析;3)根据第2步的结果,使用非负最小二乘法对候选化合物进行比例估算。方法是一种鉴别混合物的方法,具有一定的应用前景。
Raman spectroscopy is called a "fingerprint" technology because it can provide rich structural information and can be used for qualitative identification of unknown compounds.A Raman spectrum can be acquired in almost every environment without special sample preparation or destruction of samples.It is generally regarded that Raman spectroscopy can provide structural information of pure substances and not suitable for composition analysis of mixture chemical products.In this study,a mixture identificationmethod was developed based on portable Raman spectrometer,spectral database and chemometrics.Classical reverse searching procedure based on automatic and accurate peak detection in the wavelet spaces has been modified according to the Raman spectrum features.The match quality can be calculated by counting the negative ratio in the subtractive spectrum between the mixture and database(scaled by the minimal ratio of the reversely matched peaks).According to the modified reverse searching and nonnegative least square(RSearch-NNLS),apractical method for mixture analysis has been proposed.This method consists of the following steps:1)building database by Whittaker smoother,airPLS baseline correction and continuous wavelet transform(CWT),2)qualitative analysis of collected mixture spectrum by RSearch-NNLS,3)according to the result of step 2,ratio estimation of the candidate compounds.The proposed RSearch-NNLS method may be a promising procedure for solving the mixture analysis problem of Raman spectra for some applications.
Raman spectroscopy is called a "fingerprint" technology because it can provide rich structural information and can be used for qualitative identification of unknown compounds.A Raman spectrum can be acquired in almost every environment without special sample preparation or destruction of samples.It is generally regarded that Raman spectroscopy can provide structural information of pure substances and not suitable for composition analysis of mixture chemical products.In this study,a mixture identificationmethod was developed based on portable Raman spectrometer,spectral database and chemometrics.Classical reverse searching procedure based on automatic and accurate peak detection in the wavelet spaces has been modified according to the Raman spectrum features.The match quality can be calculated by counting the negative ratio in the subtractive spectrum between the mixture and database(scaled by the minimal ratio of the reversely matched peaks).According to the modified reverse searching and nonnegative least square(RSearch-NNLS),apractical method for mixture analysis has been proposed.This method consists of the following steps:1)building database by Whittaker smoother,airPLS baseline correction and continuous wavelet transform(CWT),2)qualitative analysis of collected mixture spectrum by RSearch-NNLS,3)according to the result of step 2,ratio estimation of the candidate compounds.The proposed RSearch-NNLS method may be a promising procedure for solving the mixture analysis problem of Raman spectra for some applications.
引文
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[2]MAQUELIN K,CHOO-SMITH LP,VREESWIJK T V,et al.Raman spectroscopic method for identification of clinically relevant microorganisms growing on solid culture medium[J].Anal.Chem.,2000,72:12-19.
[3]CARRON K,COX R.Qualitative analysis and the answer box:a perspective on portable raman spectroscopy[J].Anal.Chem.,2010,82:3419-3425.
[4]CHOO-SMITH LP,EDWARDS H G M,ENDTZ H P,et al.Medical applications of Raman spectroscopy:from proof of principle to clinical implementation[J].Biopolymers,2002,67:1-9.
[5]FERRARO J R,NAKAMOTO K.Introductory Raman Spectroscopy[M].2nd ed.San Diego:Academic Press,2003.
[6]COOLEY J W,TUKEY J W.An algorithm for the machine calculation of complex Fourier Series[J].Math.Comput.,1965,19:297-307.
[7]FRIGO M,JOHNSON S G.The design and implementation of FFTW3[J].Proc.IEEE,2005,93:216-231.
[8]KOO I,ZHANG X,KIM S.Wavelet-and Fouriertransform-based spectrum similarity approaches to compound identification in gas chromatography/mass spectrometry[J].Anal.Chem.,2011,83:5631-5638.
[9]MALLAT S G.A theory for multiresolution signal decomposition:the wavelet representation[J].IEEE Trans.Pattern Anal.Mach.Intell.,1989,11:674-693.
[10]LEUNG A K M,CHAU F,GAO J,et al.Application of wavelet transform in infrared spectrometry:spectral compression and library search[J].Chemom.Intell.Lab.Syst.,1998,43:69-88.
[11]RODRIGUEZ J D,WESTENBERGER B J,BUHSE L F,et al.Quantitative evaluation of the sensitivity of library-based Raman spectral correlation methods[J].Anal.Chem.,2011,83:4061-4067.
[12]KHAN S S,MADDEN M G.New similarity metrics for Raman spectroscopy[J].Chemom.Intell.Lab.Syst.,2012,114:99-108.
[13]LEE S,LEE H,CHUNG H.New discrimination method combining hit quality index based spectral matching and voting[J].Anal.Chim.Acta.,2013,758:58-65.
[14]MALINOWSKI E R,MCCUE M.Qualitative and quantitative determination of suspected components in mixtures by target transformation factor analysis of their mass spectra[J].Anal.Chem.,1977,49:284-287.
[15]WINDIG W,GUILMENT J.Interactive self-modeling mixture analysis[J].Anal.Chem.,1991,63:1425-1432.
[16]SIN S Y,WIDJAJA E,YU L E,et al.Application of FT-Raman and FTIR measurements using a novel spectral reconstruction algorithm[J].J.Raman Spectrosc.,2003,34:795-805.
[17]ZHANG Z M,CHEN X Q,LU H M,et al.Mixture analysis using reverse searching and non-negative least squares[J].Chemometrics and Intelligent Laboratory Systems,2014,137:10-20.
[18]薛晓康,李晓宇,丁卯.激光拉曼光谱解谱和处理的方法研究[J].中国无机分析化学(Chinese Journal of Inorganic Analytical Chemistry),2018,8(2):66-70.
[19]EILERS P H C.A Perfect Smoother[J].Analytical Chemistry,2003,75:3631-3636.
[20]ZHANG Z M,CHEN S,LIANG Y Z.Baseline correction using adaptive iteratively reweighted penalized least squares[J].Analyst,2010,135:1138-1146.
[21]DU P,KIBBE W A,LIN S M.Improved peak detection in mass spectrum by incorporating continuous wavelet transform-based pattern matching[J].Bioinformatics,2006,22:2059-2065.