School of Food Science and Engineering, South China University of Technology, Guangzhou 510641, China; Academy of Contemporary Food Engineering, South China University of Technology, Guangzhou Higher Education Mega Centre, Guangzhou 510006, China; Engineering and Technological Research Centre of Guangdong Province on Intelligent Sensing and Process Control of Cold Chain Foods, Guangzhou Higher Education Mega Centre, Guangzhou 510006, China.
School of Food Science and Engineering, South China University of Technology, Guangzhou 510641, China; Academy of Contemporary Food Engineering, South China University of Technology, Guangzhou Higher Education Mega Centre, Guangzhou 510006, China; Engineering and Technological Research Centre of Guangdong Province on Intelligent Sensing and Process Control of Cold Chain Foods, Guangzhou Higher Education Mega Centre, Guangzhou 510006, China; Food Refrigeration and Computerized Food Technology (FRCFT), Agriculture and Food Science Centre, University College Dublin, National University of Ireland, Belfield, Dublin 4, Ireland.
Talanta. 2019 May 1;196:537-545. doi: 10.1016/j.talanta.2018.12.030. Epub 2018 Dec 12.
Fast sampling and multicomponent detections are important in the analysis of pesticide residues detection. In this work, surface-enhanced Raman scattering (SERS) method based on silver-coated gold nanoparticles (Au@Ag NPs) was used to simultaneously detect multi-class pesticide residues such as thiacloprid (carbamate), profenofos (organophosphate) and oxamyl (neonicotinoid) in standard solution and peach fruit. The Au@Ag NPs with 26 nm Au core size and 6 nm Ag shell thickness exhibited significant Raman enhancement, especially by the creation of hot spots through NPs aggregation induced by the connection between Au@Ag NPs and target molecules. The findings demonstrated that the characteristic wavenumber of the pesticides (thiacloprid, profenofos, and oxamyl) could be precisely identified using the SERS method. Compared with earlier studies, the current approach was rapid, inexpensive and without lengthy sample pretreatment. Moreover, the results revealed that the limit of detection (LOD) was 0.1 mg/kg for thiacloprid obtained in the peach extract with determination coefficient (R) of 0.986. Additionally, LOD for both profenofos and oxamyl was 0.01 mg/kg with a determination coefficient (R) of 0.985 and 0.988, respectively. Good recovery percentage (78.6-162.0%) showed the high SERS activity with better accuracy for the detection of the thiacloprid, profenofos, and oxamyl in peach. The results of this study could offer a promising SERS platform for simultaneous detection of other contaminants such as thiacloprid, profenofos and oxamyl in multifaceted food matrices.
快速采样和多组分检测在农药残留分析中非常重要。在这项工作中，基于银包裹金纳米粒子（Au@Ag NPs）的表面增强拉曼散射（SERS）方法被用于同时检测标准溶液和桃果实中的多类农药残留，如噻虫啉（氨基甲酸酯）、丙溴磷（有机磷）和涕灭威（新烟碱类）。Au@Ag NPs 的 Au 核尺寸为 26nm，Ag 壳厚度为 6nm，表现出显著的拉曼增强，特别是通过 Au@Ag NPs 与目标分子之间的连接引起的 NPs 聚集来产生热点。研究结果表明，可通过 SERS 方法精确识别农药（噻虫啉、丙溴磷和涕灭威）的特征波数。与早期的研究相比，本方法快速、廉价，且无需冗长的样品预处理。此外，结果表明，在桃提取物中，噻虫啉的检测限（LOD）为 0.1mg/kg，决定系数（R）为 0.986。对于丙溴磷和涕灭威，LOD 分别为 0.01mg/kg，决定系数（R）分别为 0.985 和 0.988。良好的回收率（78.6-162.0%）表明，SERS 活性高，对桃中噻虫啉、丙溴磷和涕灭威的检测具有更好的准确性。这项研究的结果可为同时检测多种食品基质中的噻虫啉、丙溴磷和涕灭威等其他污染物提供一个有前景的 SERS 平台。
