{"title":"Interference-Free Automated 96-Well Plate SERS Platform for High-Throughput Detection of Thiamethoxam","authors":"Hao Wang, Xinxin Duan, Yuhang Sun, Wenjun Zhang, Wenxi Liu, Mengmeng Yan, Jianqing Wang, Kushiev Khabibjon","doi":"10.1016/j.jfutfo.2025.12.016","DOIUrl":null,"url":null,"abstract":"• Developed an interference-free SERS platform with automated 96-well for TXM high-throughput detection. • Au@PB NPs probe provides a clear Raman peak at 2155 cm −1 , free of food matrix interference. • Achieved a detection range of 1-100 ng/mL with a detection limit as low as 0.19 ng/mL. • Results align with HPLC-MS/MS, confirming high accuracy in real sample detection. Establishing accurate, sensitive, and high-throughput pesticide residue detection technologies is crucial for ensuring food safety. In this study, we developed a quartz plate cover to level the liquid surface and maintain consistent laser focus during SERS acquisition. This design significantly improved signal uniformity and reproducibility across multiple wells. By leveraging the sharp Raman peak at 2155 cm −1 , one-step synthesized gold@Prussian blue nanoparticles (Au@PB NPs) were employed to eliminate spectral interference from complex food matrices and target. In the competitive immunoassay, thiamethoxam (TXM) in the sample competed with TXM antigen-conjugated magnetic beads for binding to the probes. Higher TXM concentrations resulted in reduced binding of SERS probes to the capture substrate and a subsequent decrease in Raman intensity at 2155 cm −1 . Uder optimized conditions, the platform achieved a linear detection range of 1-100 ng/mL and a detection limit of 0.19 ng/mL. The method was validated in pear, leek, and celery samples, showing high accuracy and consistency with HPLC-MS/MS results. This automated SERS platform combines strong anti-interference capability and signal stability with scalable high-throughput performance, providing a robust solution for the trace-level detection of pesticide residues in complex matrices.","PeriodicalId":100784,"journal":{"name":"Journal of Future Foods","volume":"1 1","pages":""},"PeriodicalIF":10.6000,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Future Foods","FirstCategoryId":"0","ListUrlMain":"https://doi.org/10.1016/j.jfutfo.2025.12.016","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
• Developed an interference-free SERS platform with automated 96-well for TXM high-throughput detection. • Au@PB NPs probe provides a clear Raman peak at 2155 cm −1 , free of food matrix interference. • Achieved a detection range of 1-100 ng/mL with a detection limit as low as 0.19 ng/mL. • Results align with HPLC-MS/MS, confirming high accuracy in real sample detection. Establishing accurate, sensitive, and high-throughput pesticide residue detection technologies is crucial for ensuring food safety. In this study, we developed a quartz plate cover to level the liquid surface and maintain consistent laser focus during SERS acquisition. This design significantly improved signal uniformity and reproducibility across multiple wells. By leveraging the sharp Raman peak at 2155 cm −1 , one-step synthesized gold@Prussian blue nanoparticles (Au@PB NPs) were employed to eliminate spectral interference from complex food matrices and target. In the competitive immunoassay, thiamethoxam (TXM) in the sample competed with TXM antigen-conjugated magnetic beads for binding to the probes. Higher TXM concentrations resulted in reduced binding of SERS probes to the capture substrate and a subsequent decrease in Raman intensity at 2155 cm −1 . Uder optimized conditions, the platform achieved a linear detection range of 1-100 ng/mL and a detection limit of 0.19 ng/mL. The method was validated in pear, leek, and celery samples, showing high accuracy and consistency with HPLC-MS/MS results. This automated SERS platform combines strong anti-interference capability and signal stability with scalable high-throughput performance, providing a robust solution for the trace-level detection of pesticide residues in complex matrices.