Blomquist G, Johansson E, Söderström B, Wold S
J Chromatogr. 1979 May 11;173(1):19-32. doi: 10.1016/s0021-9673(01)80442-8.
Repetitive samples of three strains of the mould Penicillium were subjected to pyrolysis-gas chromatography (Py-GC). From the chromatograms, 26 peak heights were used in a subsequent SIMCA pattern recognition analysis. This data analysis gives a marked improvement in the classification of the samples (100% correct, 85% unique) in comparison with the traditional analysis based on the average chromatogram of each class (92% correct, 45% unique). The data analytical method is described in detail using the Py-GC data as an illustration.
对三种青霉菌株的重复样本进行了热解气相色谱分析(Py-GC)。从色谱图中选取了26个峰高用于后续的软独立建模类比法(SIMCA)模式识别分析。与基于每个类别平均色谱图的传统分析方法相比(正确率92%,独特率45%),这种数据分析方法在样本分类方面有显著改进(正确率100%,独特率85%)。以Py-GC数据为例详细描述了该数据分析方法。