Monakhova Yulia B, Mushtakova Svetlana P
Institute of Chemistry, Saratov State University, Astrakhanskaya Street 83, 410012, Saratov, Russia.
Spectral Service AG, Emil-Hoffmann-Straße 33, 50996, Cologne, Germany.
Anal Bioanal Chem. 2017 May;409(13):3319-3327. doi: 10.1007/s00216-017-0275-0. Epub 2017 Mar 15.
A fast and reliable spectroscopic method for multicomponent quantitative analysis of targeted compounds with overlapping signals in complex mixtures has been established. The innovative analytical approach is based on the preliminary chemometric extraction of qualitative and quantitative information from UV-vis and IR spectral profiles of a calibration system using independent component analysis (ICA). Using this quantitative model and ICA resolution results of spectral profiling of "unknown" model mixtures, the absolute analyte concentrations in multicomponent mixtures and authentic samples were then calculated without reference solutions. Good recoveries generally between 95% and 105% were obtained. The method can be applied to any spectroscopic data that obey the Beer-Lambert-Bouguer law. The proposed method was tested on analysis of vitamins and caffeine in energy drinks and aromatic hydrocarbons in motor fuel with 10% error. The results demonstrated that the proposed method is a promising tool for rapid simultaneous multicomponent analysis in the case of spectral overlap and the absence/inaccessibility of reference materials.
建立了一种快速可靠的光谱方法，用于对复杂混合物中具有重叠信号的目标化合物进行多组分定量分析。这种创新的分析方法基于使用独立成分分析（ICA）从校准系统的紫外-可见和红外光谱图中初步提取定性和定量信息的化学计量学方法。利用该定量模型和“未知”模型混合物光谱分析的ICA分辨率结果，无需参考溶液即可计算多组分混合物和真实样品中分析物的绝对浓度。一般获得了95%至105%之间的良好回收率。该方法可应用于任何符合比尔-朗伯-布格定律的光谱数据。所提出的方法在能量饮料中的维生素和咖啡因以及发动机燃料中的芳烃分析中进行了测试，误差为10%。结果表明，所提出的方法是在光谱重叠且参考物质不存在/无法获取的情况下进行快速同时多组分分析的一种有前途的工具。
