Acta Chimica Sinica ›› 2013, Vol. 71 ›› Issue (05): 729-732.

Article

### 一种新型交替迭代算法用于农药GC-MS信号快速分析

1. 南开大学化学学院 天津 300071
• 投稿日期:2013-01-09 发布日期:2013-03-08
• 通讯作者: 邵学广,xshao@nankai.edu.cn E-mail:xshao@nankai.edu.cn
• 基金资助:

项目受国家自然科学基金(No. 21175074)资助.

### Rapid Analysis of Pesticide Mixture by Gas Chromatography-Mass Spectrometry with a New Alternative Iterative Algorithm

Mei Zhen, Cai Wensheng, Shao Xueguang

1. College of Chemistry, Nankai University, Tianjin 300071
• Received:2013-01-09 Published:2013-03-08
• Supported by:

Project supported by the National Natural Science Foundation of China (No. 21175074).

Chemometric methods have been proved to be a powerful tool for resolution of overlapping signals. Immune algorithm (IA) is one of the chemometric approaches for analyzing multi-component GC-MS signals. The method extracts the information of the components by iteratively eliminating standard information (chromatogram or mass spectrum) from overlapping GC-MS signals. In the primary IA, however, the standard signal of each component possibly contained in the mixture must be provided by measuring the standard or by theoretical simulation. When there is difference between the measured signals of the standards and the mixture, distortion and negative values will appear in the resolved chromatograms. In order to conquer the problem, an algorithm based on an alternative iteration of least squares fitting and IA was proposed in this work. In the method, the measurement of GC-MS was achieved with a very fast temperature program to make the analytes to elute within a short retention time period, and then the chromatographic and mass spectral information of the components in the overlapping signal is calculated with the proposed algorithm. In the calculation, the algorithm takes random mass spectra of the components as the starting input, and then the information of each component is obtained with an alternating iterative process. In the iteration, the mass spectra are calculated by using the least squares fitting and the chromatographic profiles are resolved by IA. Furthermore, the non-negative and unimodality constraints are adopted in the calculation for improving the resolved results. The iteration stops when the remaining signal does not change. The feasibility of the method was validated by using a simulated GC-MS data matrix of a three-component mixture, and the practicability of the method was proved by resolving the GC-MS data of the 40-pesticide mixture. The results show that both the mass spectra and the chromatographic information of the components were extracted from the overlapping signals, and the pesticide mixture was analyzed within 10 min elution with the help of the proposed method.