%A HUANG Li, MA Rui-jun, CHEN Yu, CAI Xiang, YAN Zhen-feng, TANG Hao, LI Yan-fen
%T Experimental Study on Rapid Detection of Various Organophosphorus Pesticides in Water by UV-Vis Spectroscopy and Parallel Factor Analysis
%0 Journal Article
%D 2023
%J SPECTROSCOPY AND SPECTRAL ANALYSIS
%R 10.3964/j.issn.1000-0593(2023)11-3452-09
%P 3452-3460
%V 43
%N 11
%U {https://www.gpxygpfx.com/CN/abstract/article_13572.shtml}
%8 2023-11-01
%X In order to realize the qualitative identification and quantitative detection of multi-component organophosphorus pesticides in mixed systems, this paper combines ultraviolet-visible absorption spectra with Parallel Factor Analysis (PARAFAC) to analyze the mixed solution of multi-component organophosphorus pesticides in water rapidly. The absorption spectra of experimental samples of single-component, two-component and three-component pesticide solutions composed of chlorpyrifos, methyl-parathion and profenofos in pure water were obtained by UV-Vis spectrometer. These pure water-organophosphorus pesticide absorption spectrum data were constructed into different three-dimensional data matrices. Then the PARAFAC algorithm was used to decompose the three-dimensional data after the factor number was determined by the nuclear consensus diagnosis method. It was found that the spectrum obtained by the decomposition of two-component and three-component pesticides was very similar to the actual single-component spectrum, which shows the algorithm can realize the qualitative analysis of multi-component organophosphorus pesticides in water. A linear regression model was constructed using the score matrix obtained by the algorithm decomposition and the true concentration of each component to predict different data sets (including a spectral data set with farmland water as dilution background). The prediction results of the model show that the PARAFAC algorithm has a significant second-order advantage. Even when the spectral overlap is serious, and there is interference information in the prediction set that does not exist in the calibration set, the algorithm can still effectively detect the mixed system. Qualitative analysis and quantitative detection were achieved for all the two-component mixed solutions, with the model evaluation coefficient of *R*^{2} greater than 0.9 and the RPD greater than 3. The qualitative analysis was achieved for chlorpyrifos, methyl-parathion, and propamocarb in the three-component mixed solutions, in which chlorpyrifos and methyl-parathion met the quantitative detection requirements, and only profenofos showed unsatisfactory quantitative detection results. It may be that the overall spectral intensity level of profenofos solution is significantly lower than that of chlorpyrifos and methyl-parathion solutions of the same concentration, and its spectral contribution is the smallest, so the algorithm has poor resolution of profenofos in its mixed system. PARAFAC algorithm achieves the effect of “mathematical separation” instead of “chemical separation” that can qualitatively identify and quantitatively detect multi-component organophosphorus pesticide mixtures with serious spectral overlap without complicated preprocessing. The method provides a theoretical basis for rapidly detecting and analysing organophosphorus pesticide residues in water.