Steffen B, Müller K P, Komenda M, Koppmann R, Schaub A
Zentralinstitut für angewandte Mathematik, Forschungszentrum Jülich, 52425 Jülich, Germany.
J Chromatogr A. 2005 Apr 15;1071(1-2):239-46. doi: 10.1016/j.chroma.2004.11.073.
Automatic peak evaluation in chromatograms and subsequent quantification of compound concentrations is still a challenge in the analysis of complex samples containing hundreds or thousands of compounds. Although a number of software packages for peak evaluation exist, baseline definition and overlapping peaks of different shapes are the main reasons which prevent reliable automatic analysis of complex chromatograms. A new mathematical procedure is presented which uses peak shapes extracted from the chromatogram itself and modified by nonlinear (in fact, hyperbolic) stretching of the peak head and tail. With this approach, the peak parameters are position, height, scale of front, scale of tail, and smoothness of transition from front to tail scaling. This approach is found to give a substantially better fit than traditional analytically defined peak shapes. Together with a good peak finding heuristic and nonlinear optimization of parameters this allows a reliable automatic analysis of chromatograms with a large number of peaks, even with large groups of overlapping peaks. The analysis matches the quality of standard interactive methods, but still permits interactive refinement. This approach has been implemented and tested on a large set of data from chromatography of hydrocarbons in ambient air samples.
在分析含有数百或数千种化合物的复杂样品时，色谱图中的自动峰评估以及随后化合物浓度的定量分析仍然是一项挑战。尽管存在许多用于峰评估的软件包，但基线定义和不同形状的重叠峰是妨碍对复杂色谱图进行可靠自动分析的主要原因。本文提出了一种新的数学方法，该方法使用从色谱图本身提取的峰形，并通过对峰头和峰尾进行非线性（实际上是双曲线）拉伸来进行修改。通过这种方法，峰参数包括位置、高度、峰前尺度、峰尾尺度以及从峰前尺度到峰尾尺度过渡的平滑度。结果发现，这种方法比传统的解析定义峰形拟合效果要好得多。结合良好的峰检测启发式算法和参数的非线性优化，这使得即使存在大量重叠峰的色谱图也能进行可靠的自动分析。该分析与标准交互式方法的质量相当，但仍允许进行交互式优化。这种方法已在大量来自环境空气样品中烃类色谱分析的数据上进行了实现和测试。
