一种新型交替迭代算法用于农药GC-MS信号快速分析

化学计量学算法为重叠GC-MS信号解析提供了有效手段. 免疫算法(IAs)可根据标准样品的信号(色谱或质谱)对重叠GC-MS信号进行解析并得到重叠信号中各组分的信息. 但是标样信号与实际测量信号之间的差别会造成解析结果出现偏差. 针对标样信号与测量信号不一致的问题, 作者提出了一种交替迭代算法用于重叠GC-MS测量信号的直接解析. 该方法在不提供标样信号的情况下可以解析出组分的质谱和色谱信息. 计算过程中, 采用随机产生的质谱作为初始输入, 利用最小二乘和IA算法交替计算质谱和色谱, 直到满足终止条件. 采用所建立的方法对40种组分的农药混合物进行了分析, 使用快速升温程序在10 min保留时间内得到了全部组分的色谱和质谱信息.     

熵最小算法解析中药挥发油GC-MS谱中同分异构体的研究

采用以熵最小算法为基本原理的化学计量学方法,结合气相色谱-质谱联用分析法,对玫瑰精油及茉莉花挥发油中的2对同分异构体重叠峰进行重建分析,并分别得到各组分的重建质谱,同时采用NIST数据库相似度检索、质谱碎片信息比对及程序升温指数对分析得到的各组分进行定性分析。通过分析,分别从玫瑰精油和茉莉花挥发油的GC-MS重叠峰中分离得到1对同分异构体。分析结果显示,采用熵最小算法可以成功地对重叠峰中的各组分进行定性分析。该研究为类似同分异构体混合物中各组分的测定提供了参考。     

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。     

气相色谱-质谱法与化学计量学分辨法分析当归须挥发油中化学成分

本文借助化学计量学分辨方法,建立了用气相色谱-质谱(GC-MS)联用法分析当归须挥发油成分的方法.对重叠色谱峰采用直观推导式演进特征投影算法进行分辨,从而获得每一组分的纯色谱和质谱,依靠每一组分纯质谱在NIST质谱库进行相似性检索而定性分析,用总体积积分法进行定量分析.在当归须挥发油中共分辨出86个色谱峰,通过质谱库检...     

用熵最小算法解析桂郁金挥发油GC-MS重叠谱

采用气相色谱-质谱(GC-MS)联用技术对桂郁金中提取的挥发油成分进行检测,同时用熵最小算法对其中的共流物色谱峰进行解析,并通过质谱库检索和程序升温保留指数相结合的方式对解析得到的各纯组分进行定性分析。将桂郁金挥发油各组分的质谱数据直接与美国国家标准及技术研究所(NIST)数据库进行比对,鉴定出38个化合物;在挥发油的色谱图中,存在一些因分离不完全而导致的共流物色谱峰,以保留时间为1 106.52~1 108.38 s及1 184 s的色谱峰为例,经熵最小算法解析,共发现5个纯组分。采用熵最小算法可以清楚地对共流物色谱峰进行解析并得到所包含的各个纯组分,该法可提高复杂成分定性定量分析结果的准确性。     

GC-MS法测定油漆行业废气化学成分及化学计量学解析

采用GU/MS法分离测定油漆行业废气污染物化学成分,利用化学计量学解析法(CRM)对重叠的色谱峰进行解析,得到各成分的纯色谱曲线和质谱,通过质谱库对解析的纯组分进行定性,用解析色谱曲线积分法进行定量.从25个色谱峰中解析出了49个组分,按检索相似度大于90%的原则,鉴定出了其中40个化合物,占总含量的92.3%.废气污染物的主要成分为苯系物和烷烃,分别占总含量的46.8%和27.2%.     

基于高通量解析算法的复杂样品重叠气相色谱-质谱信号的快速分析

化学计量学算法为重叠气相色谱-质谱(GC-MS)信号的解析提供了有效手段,但其在计算过程中一般需要将数据进行分段处理,然后只对信号的某些区间进行解析,难以实现真正意义上的高通量分析。该文结合移动窗口目标转换因子分析(MWTTFA)和非负免疫算法(NNIA),建立了一种高通量解析方法。首先,根据所有可能存在的目标组分的标准质谱信息,利用MWTTFA检验复杂信号中存在的组分,并确定目标组分的质谱信息和洗脱时间区域。以得到的质谱信息作为后续计算的输入值,利用NNIA解析得到相应的色谱信息。采用快速升温程序对17种和42种农药混合标准样品的GC-MS信号进行分析,利用所建立的方法可在10 min内得到全部组分的色谱和质谱信息。     

联用色谱数据的局部分辨

提出了一种对二维数据严重重叠峰中待测组份进行分辨的新方法：子窗口分析法（ｓｕｂｗｉｎｄｏｗ ａｎａｌｙｓｉｓ，ＳＡ）。该方法充分利用重叠区信息，成功地解析出严重重叠峰中待测组份的光谱，进而利用正交投影求得待测组份色谱曲线．这种对二维数据进行局部分辨的方法，降低了对色谱分离条件的要求，可直接应用于未知组份的定性定量分析。     

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.     

利用气相色谱/质谱-化学计量学分辨法分析川芎挥发性成分

采用加速溶剂萃取法提取挥发性成分,气相色谱-质谱(GC-MS)联用分析,并借助化学计量学分辨方法,对川芎的挥发性成分进行了定性定量分析。通过采用子窗口因子分析法对重叠色谱峰进行分辨,从而获得每一组分的纯色谱和质谱。依靠每一组分纯质谱在NIST质谱库进行相似性检索而定性分析,用总体积积分法进行定量分析。在川芎挥发油中共分辨出67个色谱峰,通过质谱库检索得到其中56个组分的定性定量结果,占总含量的87.67%。该方法增加了可鉴定化合物的数目,提高了定性的准确度,能用于川芎的质量控制。     

Multi‐scale Gaussian/Haar wavelet strategies coupled with sub‐window factor analysis for an accurate alignment in nontargeted metabolic profiling to enhance herbal origin discrimination capability

Metabolic dataset can provide an overview of different herbal origin, which is conducted by some statistical procedures. Such results often deviate to a certain degree, due to peaks shifts in chromatographic signals. In order to solve this problem, an improved algorithm of combining sub‐window factor analysis with the mass spectrum information is proposed. The algorithm uses a peak detection approach derived either from multi‐scale Gaussian function or Haar wavelet to locate the peaks with different application scope; the candidate drift points at each peak are estimated by Fast Fourier transform cross correlation; Specifically, the best drift points at each candidate peaks are confirmed by sub‐window factor analysis and mass spectrum information in nontargeted metabolic profiling. Finally, the peak regions were aligned against a reference chromatogram, and the non‐peak regions were used linear interpolation. The chromatographic signals of 30 Bupleurum samples were aligned as an illustration of this algorithm, and they could be well distinguished using some statistical procedures. The result demonstrates that the presented method is stronger than other mass‐spectra based algorithms, when facing the alignment of some co‐eluted peaks.     

Recursive Wavelet Peak Detection of Analytical Signals

A novel algorithm, entitled recursive wavelet peak detection (RWPD), is proposed to detect both normal and overlapped peaks in analytical signals. Recursive peak detection is based on continuous wavelet transforms (CWTs), which can be used to obtain initial peak positions even for overlapped peaks. Genetic algorithm (GA) and Gaussian fitting are used to refine peak parameters (peak positions, widths, and heights). Finally, area of peaks can be calculated by numeric integration. Simulated and ultrahigh performance liquid chromatographic ion trap time-of-flight mass spectrometry (UPLC-IT-TOF-MS) data sets have been analyzed by RWPD, MassSpecWavelet, and peakfit package by Tom O’Haver. Results show that RWPD can obtain more accurate positions and smaller relative fitting errors than MassSpecWavelet and peakfit, especially in overlapped peaks. RWPD is a convenient tool for peak detection and deconvolution of overlapped peaks, and it has been developed in R programming language and is available at https://github.com/zmzhang/RWPD.

     

Multivariate curve resolution in liquid chromatography—resolving two-way multi-component data using a Varimax extended rotation

The Varimax extended rotations (VER) have been proposed as a new method to mathematically resolve severely overlapped peaks in chromatographic experiments that produce bilinear data. VER employs a four-step procedure to determine the relative concentration and identity of the components that comprise a severely overlapped chromatographic peak. In the first step, the data are pre-processed to ensure that they are in a form suitable for multivariate curve resolution. The second step involves principal component analysis, which reduces the dimensionality of the data matrix while simultaneously retaining the information present in the data. In the third step, a new coordinate system is developed for the data using a Varimax rotation followed by a so-called extended rotation, which assists in identifying the so-called pure regions in the peak. Identifying these regions is crucial to rotating the concentration and spectral matrices towards a solution. The fourth step utilizes alternating least squares (ALS) to improve the estimates of the concentration and spectral profiles of each component. Results from real and simulated data are used to illustrate the efficacy and simplicity of the proposed method.     

Spectral transformations for deconvolution methods applied on gas chromatography-mass spectrometry data

In hyphenated chromatography, overlapping chromatographic peaks can be resolved into pure spectra and pure chromatographic profiles by several multivariate deconvolution techniques. In general, these methods require bilinearity, which implies that the spectrum of each analyte is constant. The slow scan speeds normally used in gas chromatography-mass spectrometry (GC-MS) will destroy bilinearity and introduce systematic noise in the data because the concentration in the detector changes during the scan. This effect, described as the scan effect, may hinder successful resolution by multivariate deconvolution. In selected ion monitoring (SIM) GC-MS, the scan effect may be removed by simple transformations of the mass spectra. The effects of different transformations are demonstrated both on pure chromatographic peaks and on difficult resolution problems where there are small differences between the spectra of the analytes.     

Automatic extraction of relevant peaks and reconstruction of mass spectra for low signal-to-noise GC-MS data

A method for the automatic extraction of spectra from GC-MS data is described. The program localizes chromatographic peaks and provides a reconstructed spectrum of each compound. It is particularly designed for low-sampling conditions frequently encountered with efficient GC columns, requiring threshold methods rather than methods based on peak shape; automatic threshold adjustments on the mass chromatograms are thus performed at different stages of the process. A test of the program on two sets of experimental data revealed better performances than manual data treatment, particularly in the case of low signal-to-noise ratios.     

Application of point-to-point matching algorithms for background correction in on-line liquid chromatography-Fourier transform infrared spectrometry (LC-FTIR)

A new background correction method for the on-line coupling of gradient liquid chromatography and Fourier transform infrared spectrometry has been developed. It is based on the use of a point-to-point matching algorithm that compares the absorption spectra of the sample data set with those of a previously recorded reference data set in order to select an appropriate reference spectrum. The spectral range used for the point-to-point comparison is selected with minimal user-interaction, thus facilitating considerably the application of the whole method. The background correction method has been successfully tested on a chromatographic separation of four nitrophenols running acetonitrile (0.08%, v/v TFA):water (0.08%, v/v TFA) gradients with compositions ranging from 35 to 85% (v/v) acetonitrile, giving accurate results for both, baseline resolved and overlapped peaks.     

基于积分渐进展开的气相色谱重叠峰快速解析法

论文提出用积分渐进展开解析气相色谱重叠峰,该方法有3个主要步骤：首先将谷峰或肩峰分成两个积分区域,得到一个子区域的积分方程和一个重叠峰面积的代数方程;然后用数值积分求出这两个方程计算中所需要的峰面积,再用积分渐进公式将积分方程展开成代数方程;最后,将这两个方程与峰高约束方程联立后,得到一个非线性代数方程组,用Gauss-Seidel迭代可以快速求解方程组,方程收敛的最大迭代次数不超过20次。仿真和实验结果表明,解析的峰高和峰面积误差均很小,峰面积最大误差低于6.44%,峰高的最大误差约为6.80%。由于该算法精度高,效率高,所以这个方法可以用于气相色谱重叠峰和一般色谱峰的实时在线解析。     

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。     

Resolving overlapped spectra with curve fitting

A novel method of curve fitting based on Gaussian function, which is used to resolve the overlapped peaks, is presented in this paper. The resolution of several kinds of overlapped peaks with noise simulated by computer has been performed and discussed in details. This method has been used for resolving of the UV-vis overlapped spectrum. The results indicate that the proposed algorithm can been used to resolve overlapped spectra effectively and satisfactorily.