Chen Pei, Harnly James M, Harrington Peter de B
U.S. Department of Agriculture, Food Composition Laboratory, Beltsville Human Nutrition Research Center, Agricultural Research Service, Beltsville, MD 20705, USA.
J AOAC Int. 2011 Jan-Feb;94(1):90-9.
This study describes the use of spectral fingerprints acquired by flow injection(FI)-MS and multivariate analysis to differentiate three Panax species: P. ginseng, P. quinquefolius, and P. notoginseng. Data were acquired using both high resolution and unit resolution MS, and were processed using principal component analysis (PCA), soft independent modeling of class analogy (SIMCA), partial least squares-discriminant analysis (PLS-DA), and a fuzzy rule-building expert system (FuRES). Both high and unit resolution MS allowed discrimination among the three Panax species. PLS-DA and FuRES provided classification with 100% accuracy while SIMCA provided classification accuracies of 77 and 88% by high- and low-resolution MS, respectively. The method does not quantify any of the sample components. With FI-MS, the analysis time was less than 2 min.
本研究描述了利用流动注射（FI）-质谱法获得的光谱指纹图谱和多变量分析来区分三种人参属植物：人参、西洋参和三七。使用高分辨率和单位分辨率质谱仪采集数据，并采用主成分分析（PCA）、类相关软独立建模（SIMCA）、偏最小二乘判别分析（PLS-DA）和模糊规则构建专家系统（FuRES）进行数据处理。高分辨率和单位分辨率质谱均能区分这三种人参属植物。PLS-DA和FuRES的分类准确率均为100%，而SIMCA通过高分辨率和低分辨率质谱的分类准确率分别为77%和88%。该方法不对任何样品成分进行定量。采用FI-质谱法时，分析时间不到2分钟。
