表面增强拉曼光谱
胶体金
拉曼光谱
表面等离子共振
分析物
百草枯
基质(水族馆)
化学
污染
纳米技术
杀虫剂
农药残留
纳米颗粒
分析化学(期刊)
环境化学
拉曼散射
色谱法
材料科学
生物
有机化学
农学
生态学
物理
海洋学
地质学
光学
作者
Kairui Zhai,Li Sun,Trang H.D. Nguyen,Mengshi Lin
标识
DOI:10.1111/1750-3841.16986
摘要
Abstract In recent years, concerns have been raised regarding the contamination of grapes with pesticide residues. As consumer demand for safer food products grows, regular monitoring of pesticide residues in food has become essential. This study sought to develop a rapid and sensitive technique for detecting two specific pesticides (phosmet and paraquat) present on the grape surface using the surface‐enhanced Raman spectroscopy (SERS) method. Gold nanostars (AuNS) particles were synthesized, featuring spiky tips that act as hot spots for localized surface plasmon resonance, thereby enhancing Raman signals. Additionally, the roughened surface of AuNS increases the surface area, resulting in improved interactions between the substrate and analyte molecules. Prominent Raman peaks of mixed contaminants were acquired and used to characterize and quantify the pesticides. It was observed that the SERS intensity of the Raman peaks changed in proportion to the concentration ratio of phosmet and paraquat. Moreover, AuNS exhibited superior SERS enhancement compared to gold nanoparticles. The results demonstrate that the lowest detectable concentration for both pesticides on grape surfaces is 0.5 mg/kg. These findings suggest that SERS coupled with AuNS constitutes a practical and promising approach for detecting and quantifying trace contaminants in food. Practical Application This research established a novel surface‐enhanced Raman spectroscopy (SERS) method coupled with a simplified extraction protocol and gold nanostar substrates to detect trace levels of pesticides in fresh produce. The detection limits meet the maximum residue limits set by the EPA. This substrate has great potential for rapid measurements of chemical contaminants in foods.
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