Key Laboratory of Food Science and Technology, Nanchang University, Nanchang, 330047, China.
Analyst. 2011 Feb 7;136(3):550-9. doi: 10.1039/c0an00639d. Epub 2010 Nov 25.
This work is concerned with the research and development of methodology for analysis of complex mixtures such as pharmaceutical or food samples, which contain many analytes. Variously treated samples (swill washed, fried and scorched) of the Rhizoma atractylodis macrocephalae (RAM) traditional Chinese medicine (TCM) as well as the common substitute, Rhizoma atractylodis (RA) TCM were chosen as examples for analysis. A combined data matrix of chromatographic 2-D HPLC-DAD-FLD (two-dimensional high performance liquid chromatography with diode array and fluorescence detectors) fingerprint profiles was constructed with the use of the HPLC-DAD and HPLC-FLD individual data matrices; the purpose was to collect maximum information and to interpret this complex data with the use of various chemometrics methods e.g. the rank-ordering multi-criteria decision making (MCDM) PROMETHEE and GAIA, K-nearest neighbours (KNN), partial least squares (PLS), back propagation-artificial neural networks (BP-ANN) methods. The chemometrics analysis demonstrated that the combined 2-D HPLC-DAD-FLD data matrix does indeed provide more information and facilitates better performing classification/prediction models for the analysis of such complex samples as the RAM and RA ones noted above. It is suggested that this fingerprint approach is suitable for analysis of other complex, multi-analyte substances.
本工作致力于研究和开发用于分析复杂混合物（如药物或食品样品）的方法学，这些混合物中含有许多分析物。选择了不同处理的苍术（白术）中药（TCM）样品（冲洗、油炸和烧焦）以及常见替代品苍术（RA）TCM 作为分析示例。使用 HPLC-DAD 和 HPLC-FLD 单个数据矩阵构建了色谱二维 HPLC-DAD-FLD（二维高效液相色谱与二极管阵列和荧光检测器）指纹图谱的组合数据矩阵；目的是收集最大信息，并使用各种化学计量学方法（例如排序多准则决策制定（MCDM）PROMETHEE 和 GAIA、K-最近邻（KNN）、偏最小二乘（PLS）、反向传播-人工神经网络（BP-ANN）方法）解释此复杂数据。化学计量学分析表明，组合的 2-D HPLC-DAD-FLD 数据矩阵确实提供了更多信息，并为分析上述 RAM 和 RA 等复杂样品提供了更好的分类/预测模型。建议该指纹方法适用于分析其他复杂的多分析物物质。
