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一种新的色谱峰对齐方法与三维色谱数据分析的三线性分解相结合,以获得二阶优势。

A novel chromatographic peak alignment method coupled with trilinear decomposition for three dimensional chromatographic data analysis to obtain the second-order advantage.

机构信息

State Key Laboratory for Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha, 410082, PR China.

出版信息

Analyst. 2013 Jan 21;138(2):627-34. doi: 10.1039/c2an35931f.

Abstract

The alignment of chromatographic peaks and deconvolution of overlapped peaks still remain challenges in the field of complex sample analysis. In this paper, we highlight a strategy that employs a new time shift alignment method derived from the well-known Rank Minimization method for aligning chromatographic peak shifts among samples and then uses trilinear decomposition methodology to interpret the overlapped chromatographic peaks in order to quantify analytes of interest. The performance of this novel strategy for chromatographic data analysis was evaluated using simulated chromatographic data as well as real chromatographic data. The results indicate that the new time shift alignment method can accurately correct time shifts in test samples even in the presence of unexpected interferences, and thus the low-rank trilinearity of the same analyte can be obtained, which will be helpful for trilinear decomposition to achieve the second-order advantage. Moreover, the results showed that this new alignment method is more automated in comparison with the Rank Minimization method and will be suitable for the alignment of the time shifts of analytes that are completely overlapped by coeluted interferences.

摘要

在复杂样品分析领域,色谱峰的对齐和重叠峰的分解仍然是一个挑战。本文提出了一种策略,该策略使用一种新的时间偏移对齐方法,该方法源自著名的秩最小化方法,用于对齐样品之间的色谱峰偏移,然后使用三线性分解方法来解释重叠的色谱峰,以定量感兴趣的分析物。使用模拟色谱数据和真实色谱数据评估了这种用于色谱数据分析的新策略的性能。结果表明,即使存在意外干扰,新的时间偏移对齐方法也可以准确校正测试样品中的时间偏移,从而获得相同分析物的低阶三线性,这将有助于三线性分解实现二阶优势。此外,结果表明,与秩最小化方法相比,这种新的对齐方法更加自动化,并且适用于完全由共洗脱干扰重叠的分析物的时间偏移的对齐。

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