Analytical Chemistry Group, van 't Hoff Institute for Molecular Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands; Centre for Analytical Sciences Amsterdam (CASA), The Netherlands.
DSM Engineering Materials, Geleen, The Netherlands.
J Chromatogr A. 2023 Aug 30;1705:464223. doi: 10.1016/j.chroma.2023.464223. Epub 2023 Jul 20.
Analytical data processing often requires the comparison of data, i.e. finding similarities and differences within separations. In this context, a peak-tracking algorithm was developed to compare multiple datasets in one-dimensional (1D) and two-dimensional (2D) chromatography. Two application strategies were investigated: i) data processing where all chromatograms are produced in one sequence and processed simultaneously, and ii) method optimization where chromatograms are produced and processed cumulatively. The first strategy was tested on data from comprehensive 2D liquid chromatography and comprehensive 2D gas chromatography separations of academic and industrial samples of varying compound classes (monoclonal-antibody digest, wine volatiles, polymer granulate headspace, and mayonnaise). Peaks were tracked in up to 29 chromatograms at once, but this could be upscaled when necessary. However, the peak-tracking algorithm performed less accurate for trace analytes, since, peaks that are difficult to detect are also difficult to track. The second strategy was tested with 1D liquid chromatography separations, that were optimized using automated method-development. The strategy for method optimization was quicker to detect peaks that were still poorly separated in earlier chromatograms compared to assigning a target chromatogram, to which all other chromatograms are compared. Rendering it a useful tool for automated method optimization.
分析数据处理通常需要比较数据，即寻找分离物内的相似性和差异性。在这种情况下，开发了一种峰跟踪算法，以比较一维（1D）和二维（2D）色谱中的多个数据集。研究了两种应用策略：i）在一个序列中生成所有色谱图并同时进行处理的数据处理，以及 ii）累积生成和处理色谱图的方法优化。第一种策略在综合二维液相色谱和综合二维气相色谱的学术和工业样品的分离数据上进行了测试，这些样品的化合物种类不同（单克隆抗体消化物、葡萄酒挥发物、聚合物颗粒顶空和蛋黄酱）。可以同时跟踪多达 29 个色谱图中的峰，但在必要时可以扩展。然而，对于痕量分析物，峰跟踪算法的性能较差，因为难以检测到的峰也难以跟踪。第二种策略使用 1D 液相色谱分离进行了测试，该分离使用自动化方法开发进行了优化。与分配目标色谱图相比，该方法优化策略可以更快地检测到早期色谱图中仍未完全分离的峰，而目标色谱图是所有其他色谱图进行比较的基准。这使其成为自动化方法优化的有用工具。
