Gong F, Liang Y Z, Xu Q S, Chau F T
College of Chemistry and Chemical Engineering, Institute of Chemometrics and Chemical Sensing Technology, Hunan University, Changsha, PR China.
J Chromatogr A. 2001 Jan 5;905(1-2):193-205. doi: 10.1016/s0021-9673(00)00976-6.
In this paper, a novel procedure for qualitative and quantitative analysis of the two-dimensional data obtained from GC-MS is investigated to determine chemical components of essential oils in Cortex Cinnamomi from four different producing areas. A new method named iterative optimization procedure (IOP) specially used to resolve embedded peaks is also developed. With the help of IOP and other chemometric techniques, such as heuristic evolving latent projections, evolving factor analysis, sub-window factor analysis and orthogonal projection resolution, and etc., the detection of the purity of chromatographic peaks can be first addressed, and then the overlapping peaks are resolved into the pure chromatogram and mass spectrum of each component. The similarity searches in the MS database are finally conducted to qualitatively determine the chemical components. The results obtained showed that the accuracy of qualitative and quantitative analysis could be greatly enhanced by chemometric resolution methods. The chemometric resolution techniques upon the two-dimensional data can be quite promising tools for the analysis of the complex samples like traditional Chinese medicine.
本文研究了一种用于对气相色谱-质谱联用(GC-MS)获得的二维数据进行定性和定量分析的新方法,以确定来自四个不同产地的肉桂皮层中挥发油的化学成分。还开发了一种专门用于解析重叠峰的名为迭代优化程序(IOP)的新方法。借助IOP和其他化学计量学技术,如启发式演化潜投影、演化因子分析、子窗口因子分析和正交投影分辨等,可以首先解决色谱峰纯度的检测问题,然后将重叠峰解析为各组分的纯色谱图和质谱图。最后在质谱数据库中进行相似性搜索以定性确定化学成分。所得结果表明,化学计量学分辨方法可大大提高定性和定量分析的准确性。基于二维数据的化学计量学分辨技术对于分析像中药这样的复杂样品可能是非常有前途的工具。