Self-Cleaning-Mediated SERS Chip Coupled Chemometric Algorithms for Detection and Photocatalytic Degradation of Pesticides in Food

• Published in: Journal of agricultural and food chemistry Vol. 69; no. 5; pp. 1667 - 1674
• Main Authors: Xu, Yi, Hassan, Md Mehedi, Ali, Shujat, Li, Huanhuan, Ouyang, Qin, Chen, Quansheng
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 10.02.2021
• Subjects: Algorithms; chemometrics; food chemistry; Food Contamination - analysis; Food Safety and Toxicology; irradiation; Light; Limit of Detection; Metal Nanoparticles - chemistry; nanosilver; Pesticide Residues - chemistry; photocatalysis; porous media; prediction; pymetrozine; rapid methods; Silver - chemistry; Spectrum Analysis, Raman - instrumentation; Spectrum Analysis, Raman - methods; tea; thiram; SERS chip; self-cleaning; pesticides; dual mode; random frog partial least square
• ISSN: 0021-8561; 1520-5118; 1520-5118
• DOI: 10.1021/acs.jafc.0c06513

Pesticide residues in food have been a grave concern to consumers. Herein, we have developed a dual-mode SERS chip using Cu2O mesoporous spheres decorated with Ag nanoparticles (MCu2O@Ag NPs) as both sensing and degradation/clearing unit for rapid detection of pymetrozine and thiram pesticides in tea samples. Three kinds of chemometric algorithms were comparatively applied to analyze the collected SERS spectra of pesticides. In comparison, random frog-partial least squares achieved the best performance with root mean square error of prediction and residual predictive deviation values of 0.9871, 6.17, and 0.9873, 6.64 for pymetrozine and thiram, respectively. Additionally, the prepared SERS chip showed great photocatalytic activity to degrade pesticides under visible light irradiation. Through a facile method, this work presented a novel dual-functional SERS chip for the rapid detection and degradation of low-concentration pesticides in both environmental and food samples.