In this study, the SERS technique was used to detect Thiram, Ferbam and Ziram in Dithiocarbamate by electrochemical cyclic voltammetry. The SERS substrate was prepared first. It was found that the best SERS effect was obtained when using 1 M sulfuric acid as the electrolyte and scanning for six times. The growth of nanoparticles is very uniform, and the SERS substrate using this condition can detect 5 ppm of Thiram, 10 ppm of Ferbam, and 5 ppm of Ziram, respectively. Since it can be seen that the Raman spectra of the Dithiocarbamate pesticides are similar, in this study, with the assistance of artificial intelligence, the Raman spectra combined with artificial intelligence and machine learning algorithms were analyzed, and the prediction accuracy reached 96.7% respectively. With a prediction accuracy of 95%, it proves the feasibility of combining SERS substrates with artificial intelligence, and develops a fast, accurate and inexpensive pesticide detection system.
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