直观推导式演进特征投影法在拖尾重叠色谱峰解析中的应用

直观推导式演进特征投影法(HELP)已成功应用于复杂体系的重叠色谱峰解析.当色谱峰拖尾时,演进特征投影图(ELPG)显示的直线段对应的区域中可能含有前面拖尾组分的信息,据此进行HELP解析可能得不到满意结果.选择ELPG上直线段的一部分,即拖尾组分末端,前面组分的信息已基本消失的区域作为选择性区域进行HELP解析.同时,提出一种新的定量方法:用主成分分析法(PCA)分解待测组分标准样品的二维数据,将得到的“标准”色谱引入HELP的定量过程,在色谱峰拖尾或解得谱峰不平滑时,得到更准确的结果.用HELP方法解析了依诺沙星、诺氟沙星和环丙沙星三组分实验体系,结果表明,加入上述措施的HELP可有效改善拖尾重叠色谱峰的解析结果.     

一种基于光谱分析的二元不完全重叠色谱峰的分离解析方法

基于二极管阵列检测器获得的色谱-光谱数据,建立了一种二元不完全重叠液相色谱峰的解析方法: 色谱数据经过去噪、归一化处理后,计算各时间点的光谱差异并进行系统聚类分析,提取特征光谱后,利用非负最小二乘法对色谱-光谱矩阵进行解析,得到基于特征光谱的流出曲线,进而得到分离后的色谱峰。将解析结果和纯标样的色谱峰进行比较,解析后的光谱图和纯标样的光谱图无显著差异,保留时间相差小于0.01 min。实验结果表明,该方法在二元不完全重叠液相色谱峰的解析方面能取得良好的效果。     

完全重叠色谱峰的二维微分色谱解析算法

利用完全重叠的色谱峰中同时消失的两组分的浓度变化速率差异，通过二维数据微分色谱法获取被掩盖组份的近似光谱，以解析完全重叠的色谱体系，将该法应用于维生素Ｃ和菸酸两组份完全重叠的二维色谱之分辨，结果令人满意，分辨光谱与标准光谱重合甚好。     

联用色谱数据的双窗口因子分析

利用组分光谱的特征信息,发展了一种能直接对联用色谱重叠峰中组分进行定性定量分析的新方法──双窗口因子分析（dualwindowfactoranalysis,DWPA）。该法可从多组分重叠峰中定性目标组分,且在未经其它组分的分辨下可直接对目标组分的光谱、色谱进行分辨。因此更适应于联用色谱对复杂体系中待测组分的定性定量分析。用该法成功地对4组分重叠峰进行了分析,实验结果令人满意。     

模差渐进投影法解析重叠色谱峰

提出了一种鉴别重叠色谱峰类型的化学计量学方法——模差渐进投影(MDEP)法。该方法利用二维色谱数据中相邻两个色谱流出点的光谱矢量模的和与该两个矢量和的模之差,建立模差-时间(dm-t)曲线判断非纯色谱峰的纯组分区,同时判定第二组分色谱流出点和倒数第二组分色谱结束点。分别以纯组分区的光谱矢量建立正交阵对该色谱峰进行投影运算,得到投影后转换色谱。该转换色谱消除了纯组分区所对应化合物的色谱和光谱信息。对转换色谱重复上述操作至整个色谱峰的模差-时间曲线均为0时终止,得到重叠色谱峰各组分的色谱流出点和结束点。利用上述结果,采用不包含待测组分光谱信息的该重叠峰二维色谱数据建立正交矩阵对该色谱峰进行投影运算,获得待测组分的相似色谱图。通过比对分析即可得到该组分在重叠色谱峰中的光谱和色谱信息。依次操作,即可获得重叠色谱峰中各组分的光谱和色谱信息。采用模差渐近投影法对4组分模拟重叠二维色谱峰及杜香挥发油GC-MS的重叠色谱峰进行了解析,方法简便、结果准确。     

径向基函数神经网络用于重叠色谱峰解析

 在高斯基径向基函数神经网络 (RBFNN)学习算法中引入了鲁棒性和随机全局寻优的两阶段遗传算法 :结构学习和参数优化。通过两阶段学习算法的交替使用 ,使网络具有结构自学习和参数优化的能力 ,而后将网络应用于组分数未知的重叠色谱峰解析。该方法具有不需人为干预 ,可自动确定网络结构即组分数的优点 ;并且解析精度较高 ,适用于多组分重叠色谱峰的解析 ;对完全重叠色谱峰也具有良好的解析能力。     

窗口因子分析技术用于重叠色谱峰的解析

采用窗口因子分析（ＷＦＡ）技术完成了稀土元素的高效液相色谱分析中重叠峰的解析。由３种分离条件下不同分离度的色谱数据矩阵解析得到了较好的单组分色谱图与吸收光谱曲线,并进行了定量分析。结果表明：在分离度较好时,ＷＦＡ定量结果与常规方法相近,但随着分离度的降低,ＷＦＡ的定量结果明显优于常规方法。     

子窗口分析法用于偶氮染料GC-MS重叠峰的解析

 将子窗口因子分析法 (SWFA)应用于GC MS联用检测数据分析 ,并以两种偶氮染料 3,3′ 二氯联苯胺和 4,4′ 次甲基 双 (2 氯苯胺 )重叠图谱为例进行了解析。结果表明 ,此方法可直接进行目标组分的质谱分辨 ,得到目标组分的质谱图 ,进而得到该组分的色谱图。其结果准确、可靠。与窗口因子分析相比 ,子窗口的选择更加容易 ,人工干预少 ,解析速度快。     

谱峰漂移校正技术结合三维平行因子分析方法用于分辨中药重叠高效液相色谱信号

谱峰漂移校正技术结合平行因子分析方法被应用于中药色谱重叠峰信号分辨. 谱峰漂移校正技术的使用, 使得数据的三线性得以加强, 更适合于平行因子分析方法的分辨. 本文通过对中药延胡索色谱数据分辨, 并与经典多元曲线分辨方法对比来验证谱峰漂移校正技术结合平行因子分析方法的正确性.     

完全未知混合体系的纯物种光谱辨析

基于因子分析的迭代目标转换算法,本文提出一种从完全未知混合物体系中获取纯物种光谱的解析方法。该法简单明了,不增加任何困难即可拓广至含n组份的混合体系,对光谱峰形状亦无任何附加限制要求。先采用计算机模拟技术对该法进行了校验,继用于紫外可见与荧光光谱的实际混合体系的解析,均获满意结果。     

Resolving co-eluting chromatographic patterns by means of dissimilarity analysis in iterative target transformation factor analysis

The initialization of concentration vector for iterative target transformation factor analysis (ITTFA) and identification of pure or key variables are the important issue in MCR. In this study, dissimilarity analysis and evolving factor analysis (EFA) are combined to find the selective or key variables and subsequently obtain initial estimates of the concentration vectors for resolution of gas chromatography/mass spectrometry (GC/MS) data by ITTFA. For systems containing components with highly similar mass spectra, a new constraint setting the elements out of elution window to 0 is used to improve convergence rate and accuracy of results. Tested by standard mixture of two wax esters and real GC/MS data of gasoline 97#, dissimilarity based ITTFA could obtain accurate results (average Dot product of concentration vectors, average deviation of peak area ratio and average similarity of mass spectra are 0.9929, 0.0228 and 981.0, respectively).     

气相色谱/质谱结合化学计量学解析方法用于植物精油成分分析

使用气相色谱/质谱(GC-MS)法对缬草精油和含有缬草精油的混配精油的化学成分进行了分析.采用直观推导式演进特征投影法(HELP)对二维数据中的色谱重叠峰进行了解析,得到两种精油的各个物质的纯色谱和纯质谱,同时利用交互移动窗口因子分析法(AMWFA)直接比较两种精油中的共有组分,提取出共有组分的纯质谱,通过与HELP法解析出的质谱进行比较,发现AMWFA法比HELP法能更快速鉴别出混配精油中的缬草精油.     

Calculation of equilibrium constants from multiwavelength spectroscopic data-IV Model-free least-squares refinement by use of evolving factor analysis

The newly developed algorithm of evolving factor analysis has been supplemented by iterative refinement. It allows the completely model-free calculation of concentration profiles and spectra from spectrophotometric and other spectroscopic data. Not even implicit use is made of the law of mass action. The results are practically identical with those based on a specific chemical model and classical least-squares refinement. Iterative evolving factor analysis is based on applying factor analysis successively to the set of the first 1,2 M spectra of a spectrometric titration. The analysis is repeated from the opposite end and the eigenvalues thus calculated are combined into “concentration profiles” of completely abstract “species”. These “concentration profiles” are iteratively refined by normalization, calculation of the absorption spectra from the normalized concentrations and recalculation of the concentration profiles from the absorption spectra. Evolving factor analysis is not restricted to spectrometric titrations, and can also be applied to peak resolution in chromatography using a multiwavelength (diode array) photometric or mass-spectrometric detection system, or to any other ordered set of multichannel data.     

Pressurized planar electrochromatography as a supporting tool for qualitative toxicological chemical analysis with thin-layer chromatography and UV–Vis spectrometry

ABSTRACT

Pressurized planar electrochromatography (PPEC) was applied to support qualitative toxicological chemical analysis performed with thin-layer chromatography (TLC) and UV–Vis spectrometry. Based on retention/migration distance data of substances obtained in TLC and PPEC systems and database of their wavelength maxima of remission UV–Vis spectra as well, a combined fit factor was calculated for substance identification. The involvement of PPEC, TLC, and UV–Vis spectral data together in calculation of the combined fit factor lead to its lower values for substances, which were not identical with reference, in comparison with those when the combined fit factor was calculated using TLC and spectral data only. The results evidence that involvement of PPEC data in qualitative toxicological chemical analysis performed with TLC and UV–Vis spectrometry enhances reliability of it.     

Determination of the Volatile Oil of Magnolia biondii Pamp by GC–MS Combined with Chemometric Techniques

An optimized temperature-programmed gas chromatography–mass spectrometry system combined with chemometric methods was firstly applied to analyze the volatile components of M. biondii Pamp. A total of 65 components were identified using similarity searches between mass spectra and MS database. This number was extended to 80 components with the help of chemometric techniques. The peak purity of two-way data was controlled by fixed size moving window evolving factor analysis, two dimensional-evolving latent projection graph and three dimensional-evolving latent projection graph. Then the overlapped peak clusters were resolved using heuristic evolving latent projection. The results prove that the reported approach is powerful for the analysis of complex herbal samples.     

Application of combined approach to analyze the constituents of essential oil from Dong quai

A combined approach of sub-window factor analysis and spectral correlative chromatography has been employed to analyze the constituents of essential oils of Dong quai. Essential oils are the main pharmacological active individuals of Dong quai. Some constituents in the main root of Dong quai have been identified by GC-MS with the help of sub-window factor analysis resolving two-dimensional original data into mass spectra and chromatograms. Correlative constituents in another part of the root fiber have been recognized by spectral correlative chromatography. Seventy six of 97 separated constituents in the essential oil of main root were identified and quantified, accounting for about 91.36% of the total content. Sixty seven correlative components in the essential oil of root fiber were recognized. The result proves that the combined approach is powerful enough for the analysis of complex herbal samples.     

Characterization of the Acid-Base Properties of Humic Substances by Chemometric Analysis of Synchronous Fluorescence and pH Potentiometric Data

Abstract

A procedure for the analysis of the acid-base characteristics of humic substances based on a self-modeling analysis of synchronous fluorescence spectra, collected at varying pH, and on a non-linear least squares adjustment of potentiometic pH data, is described. The data analysis methodology consists of two steps: first, the number of acid-base systems and the corresponding spectra and distribution diagrams are calculated by evolving factor analysis (EFA) with concentration constraints of the spectroscopic data; second, the potentiometric data is analyzed by a standard non-linear least square procedure using as fixed parameters the number of components and their pKas, determined in the first step of the analysis. As an example, for a sample of marine fulvic acids studied at pH between 2 and 11, four acid-base systems were found with average pKas: 3.1, 4.8, 8.0 and 10.0. The concentrations of the corresponding systems were: 2.55(5), 1.95(7), 0.14(4) and 1.8(3) meq/g.     

直观推导式演进特征投影法对酶催化反应的过程分析

以丁香酸(syringic acid)为模型化合物, 研究了漆酶(laccase)催化降解木质素(lignin)的复杂生化反应过程, 设计了一种反应过程动态量测系统, 该系统可以在5 s的时间间隔测定反应体系在190～800 nm波长范围内的实时光谱信息. 利用固定窗口因子分析-直观推导式演进特征投影法(FSMWEFA-HELP), 解析反应过程中测得的实时动力学光谱数据矩阵, 得到反应物和中间体的数目及其浓度的变化和纯物质的光谱曲线, 并推导出合理的反应机理. 将所得结果与多元曲线分辨-交替最小二乘(MCR-ALS)方法进行了比较.     

Characterization and determination of stability constants of copper(II)-l-histidine complexation system by using multivariate curve resolution method of visible spectra and two hard modeling methods in aqueous solutions

Multivariate curve resolution, alternating least-squares is applied to spectra data obtained in the study of Cu(II) complexation by l-histidine. The combination of several chemometric techniques based on factor analysis (FA), singular value decomposition (SVD), evolving factor analysis (EFA), and multivariate curve resolution with constrained alternating least-squares (ALS) is used to determine the number of species and their distribution diagram. This multivariate analysis data treatment simultaneously reveals the species Cu, CuL, CuLH, CuL₂, CuL₂H, and CuLOH, through the calculated concentration profiles and allows the assignment of numerically obtained pure individual spectra. Formation constants of these species were calculated by hard-modeling methods applied potentiometric and spectrophotometric measurements.     

Resolving batch chromatographic overlapping peaks of flavoring essence using stepwise key spectrum selection

Stepwise key spectrum selection (SKSS) was introduced to resolve batch overlapping peaks from gas chromatography-mass spectrometry (GC-MS) analysis of ten batch tobacco flavoring samples in different storage times. Resolution was implemented on a software platform that embedded the SKSS method. The data from GC-MS analysis of the samples were saved and prepared in ASCII files and then were inputted into the software platform for visual inspections. The data segment with overlapping peaks was precut for subsequent analysis. Spectral background in the data was removed using a linear fitting of the baseline. Four components in the overlapping peaks were automatically detected by the SKSS method. The resolution of the concentration profiles and spectra of the four components was conducted by setting only one parameter, the negative area ratio, as 0.01. The fixed size moving window evolving factor analysis and evolving factor analysis were applied to validate the resolved concentration profiles. The resolved mass spectra were validated by the searched standard through library search at the pure component regions revealed by the resolved concentration profiles. The results showed that the SKSS method could be a simple but powerful tool in resolving batch chromatographic overlapping peaks.