4.7 Article

Quantitative determination of carbosulfan residues by surface-enhanced Raman spectroscopy

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PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.saa.2022.122315

Keywords

Carbosulfan; Ag nanoparticles; Surface -enhanced Raman scattering; Pesticide residues; Density functional theory

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In this study, a super-sensitive method of surface-enhanced Raman spectroscopy (SERS) was used to detect carbosulfan residues in vegetables. It was found that carbosulfan easily decomposes into carbofuran and 3-Hydroxy carbofuran. Silver sol was prepared as the SERS substrate and a complex of carbosulfan, chromogenic agent, and sodium hydroxide was mixed with the silver sol in the best proportion for SERS spectra examination. Density functional theory calculations were used to determine the spectral peak positions of carbosulfan. The optimal mixing ratio and the detection limit of carbosulfan were investigated. The results suggest that SERS is a promising technique for detecting single-molecule pesticide residues in vegetables.
Carbosulfan gets easily decomposed into carbofuran and 3-Hydroxy carbofuran in vegetables and forms harmful residues. To detect the residues of carbosulfan in vegetables (for example, cowpeas), a super-sensitive method of surface-enhanced Raman spectroscopy (SERS) was used in this work. Silver sol was prepared as the SERS substrate. To solve the adsorption problem of carbosulfan on Ag nanoparticles, 2, 6-dichloroquinone-4-chlorimide (chromogenic agent), and sodium hydroxide were added in carbosulfan to generate a complex, which was then mixed with the silver sol in the best proportion to examine SERS spectra. According to density functional theory calculations, the spectral peak positions of carbosulfan were determined. The optimal mixing ratio of the complex and the silver sol to obtain the optimal SERS spectrum and the detection limit of carbosulfan were investigated. The ultra-sensitive detection of carbosulfan residues (8.7 x 10-11 g/L) in cowpeas was realized. The results of this work indicate that SERS is a promising technique for detecting single-molecule pesticide residues in vegetables.

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