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.     

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。     

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。     

移动子窗口中搜索法在紫丁香挥发油气相色谱-质谱分析中的应用

基于气相色谱-质谱仪产生的二维数据,采用移动子窗口搜索法,以纯组分峰为标准对同一样品在不同色谱柱上或不同样品在相同色谱柱上所获得的总离子流图的一定保留时间范围内搜索,可以得到目标化合物的流出区域,取其中点作为保留时间,从而计算各化合物在不同极性色谱柱上的程序升温保留指数.采用GC-MS与色谱保留指数相结合的方法,分别在HP-5MS和DB-35MS柱上,于80℃～290℃(4℃/min)的升温程序下,对黑龙江产紫丁香花蕾与花挥发油的分析结果表明,辅以化学计量学方法和双柱色谱保留指数定性比单用GC-MS定性结果更加快速可靠.     

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。     

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。     

移动子窗口搜索法在紫丁香挥发油气相色谱-质谱分析中的应用

基于气相色谱-质谱仪产生的二维数据，采用移动子窗口搜索法，以纯组分峰为标准对同一样品在不同色谱柱上或不同样品在相同色谱柱上所获得的总离子流图的一定保留时间范围内搜索，可以得到目标化合物的流出区域，取其中点作为保留时间，从而计算各化合物在不同极性色谱柱上的程序升温保留指数。采用GC-MS与色谱保留指数相结合的方法，分别在HP-5MS和DB-35MS柱上，于80℃～290℃（4℃／min）的升温程序下，对黑龙江产紫丁香花蕾与花挥发油的分析结果表明，辅以化学计量学方法和双柱色谱保留指数定性比单用GC-MS定性结果更加快速可靠。     

苯二氮卓类新精神活性物质Flubromazolam的快速检测

建立了气相色谱-质谱(GC-MS)和超高效液相色谱-串联四极杆飞行时间质谱(UPLC-Q-TOF MS)技术联合鉴定检材中flubromazolam的方法。未知样品用甲醇和水提取,取上清液,采用GC-MS和UPLC-Q-TOF MS进行分析。经GC-MS检测,保留时间为17.96 min的未知组分的质谱碎片主要特征离子峰有m/z 222,341,343,370,372,111,102,75。经UPLC-QTOF M S检测,保留时间为4.99 min的未知组分的准分子离子峰为m/z 371.0298,碰撞诱导解离(CID)模式下二级质谱主要离子有m/z 343.0114,302.9928,292.1118,263.0982,237.0951,223.0670。经美国缉毒署毒品分析谱库、缴获毒品分析科学工作组(SWGDRUG)分析谱库检索和文献查询获得的信息资料进行比对,确认目标物为flubromazolam。     

岩香菊精油的气相色谱-气相色谱-质谱联用分析

在植物挥发油等复杂有机混合物的气相色谱-质谱联用(GC-MS)分析中,常遇到分离不良的色谱峰,所取得的质谱不易识别和解析。多维色谱法则是解决复杂有机混合物分离的有力工具。对质谱工作而言,把多维色谱的卓越分离能力与质谱仪的定性鉴定能力结合起来,构成一个气相色谱-气相色谱-质谱联用(GC-GC-MS)系统,就能大大改进常规GC-MS系统的功能,但有关报道很少,尚未得到     

基于化学计量学的GC-MS分析方法研究

气相色谱-质谱联用(GC-MS)、液相色谱-质谱联用(LC-MS)等,为分析多组分混合物提供了有力手段并广泛地应用于化工、食品、生物、医药等领域.但在分析多组分复杂体系时,其色谱信号严重重叠,使得该方法难于进行准确的定性定量分析.化学计量学方法的引入,为解决该问题提供了一种新手段.例如化学因子分析(CFA)、多元校正解析方法(MCR)、免疫算法(IA)和小波变换(WT)等已被成功地运用于复杂体系分析化学重叠信号的解析.     

Rapid analysis of multicomponent pesticide mixture by GC-MS with the aid of chemometric resolution

Applications of hyphenated chromatographic techniques, especially GC-MS technique, have been reported in chemical, biological, environmental, agricultural and medical analysis. The complexity of the samples in these fields is still an obstacle for the technique to be practical and the overlapping of the multicomponent signals induces chemometric methods widely employed. In this work, taking the rapid analysis of pesticide mixture as an example, a chemometric approach was proposed for resolution of multicomponent overlapping GC-MS signal. In the method, a mass spectral library of pesticides was organized at first, then target factor analysis (TFA) was employed for testing the existence of a specific pesticide in the multicomponent overlapping GC-MS signal, and finally the chromatographic information of the pesticide was extracted by a non-negative immune algorithm (IA). A GC-MS signal of a 40-component pesticide mixture eluted within 9 min was analyzed by the method. It was found that the mass spectra and chromatographic profiles of almost all the pesticides can be obtained.     

Resolving overlapping GC–MS signals with a multistep screening chemometric approach for the fast determination of pesticides

For the rapid analysis of multicomponent mixtures using GC–MS, a chemometric multistep screening approach was proposed to extract the signals of the components from the overlapping signals measured with a very fast temperature program. At first, independent component analysis was used to find all the possible mass spectra from the overlapping signal in the moving windows along the retention time, and iterative target transformation factor analysis was employed to validate the existence of the extracted spectra from each window. Then, identical signals in the validated spectra were excluded using match ratio as a criterion. Finally, the chromatographic profiles for each spectrum were calculated using non‐negative immune algorithm, and the spectra with a reasonable profile were taken as the identified components. A mixture of 53 pesticides was analyzed with a very fast temperature program of 7 min. A total of 48 pesticides and 16 interferences were identified from the overlapping GC–MS signal.     

High-throughput approach for analysis of multicomponent gas chromatographic–mass spectrometric signals

Hyphenated techniques such as gas chromatography–mass spectrometry (GC–MS) or high-performance liquid chromatography–mass spectrometry (LC–MS) produce a large amount of data in a form of two-way data matrix. It has been a great challenge to furthest extract the useful information from the data. In this work, a chemometric approach based on a modification of adaptive immune algorithm (AIA) was proposed for a high-throughput analysis of the multicomponent overlapping GC–MS signals. With the proposed method, the chromatographic profile of each component in an overlapping signal can be extracted independently and sequentially along the retention time. In order to show the efficiency of the method, a stimulated GC–MS data of six components with background and an experimental GC–MS data of 40 pesticides were investigated. It was found that the multicomponent overlapping GC–MS signals could be fast and accurately resolved. Furthermore, the quantitative property of the extracted information was also investigated. The correlation coefficients (r) between the peak area and the added volumes of the sample are in the range 0.9658–0.9953.     

断层扫描分析法用于联用色谱二维数据的解析Ⅱ. 定量分析:原理与应用

提出了一种全新的色谱一光谱二维数据信息处理手段——断层扫描分析法。本研究介绍断层扫描分析法的定量分析原理：在重叠色谱峰簇中,每个色谱保留时间处都可得到一条光谱“断层”;针对不同的光谱“断层”,可结合褶合曲线分析法进行定量分析,并最终获得重叠色谱峰簇中待测组分的定量信息。用断层扫描分析法对一实验体系进行了定量分析,结果满意。     

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。     

Fast determination of ginsenosides in ginseng by high‐performance liquid chromatography with chemometric resolution

Ginseng is a well‐known traditional Chinese medicinal herb, and ginsenosides are its major active components. A method for the fast determination of ginsenosides in ginseng samples by high‐performance liquid chromatography was developed and used for the quantitative analysis of four ginsenosides in three different ginseng samples. In this method, instead of time‐consuming gradient elution, isocratic elution was used to speed up the analysis. Under strong isocratic elution, all the ginsenosides are eluted in 2.3 min. Although the measured signal is composed of overlapped peaks with the interferences and background, the signal of ginsenosides can be extracted by chemometric resolution. A non‐negative immune algorithm was employed to obtain the chromatographic information of the target components from the data. Compared with conventional chemometric approaches, the method can perform the extraction for one‐dimensional overlapping signals. The method was validated by the determination of four ginsenosides in three different ginseng samples. The recoveries of the spiked samples were in the range of 94.08–107.3%.     

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.     

小波变换用于重叠色谱峰组分信息的提取

提出了一个小波变换用于提取重叠色谱中组分信息的理论公式，并将它应用于三组分和五组分重叠色谱实验数据的解析。结果表明：在定定分离度范围内，当相邻色谱峰峰宽相近时，根据此公式的计算结果，可以将各组分的信息从重叠色谱峰信号中提取出来。洒工作对小波变换用于重叠峰的解析具有重要意义。     

Resolution of multicomponent NMR signals using wavelet compression and immune algorithm

A novel algorithm for fast resolution of multicomponent overlapping nuclear magnetic resonance (NMR) spectrum using the wavelet compression and the immune algorithm (IA) is proposed. Taking advantage of the linear property of the wavelet transform (WT), the overlapping NMR spectrum (antigen) can be compressed by WT before it is input into the immune network, the antibodies are also compressed to the same scheme. After extraction of the compressed information of each component, the resolved NMR spectra can be restored by the WT reconstruction. It was proven that the result is almost the same with the result from an IA, but the calculation speed is much faster.