Detection of Neonicotinoid-Contaminated Drinking Water by D-SERS and SIMCA Class Modeling

Abstract Neonicotinoids are insecticides widely used in agriculture and are highly toxic to invertebrates. There is evidence linking the use of neonicotinoids to declines in bee populations. Due to their high persistence, these compounds can remain in soil and water for long periods and are frequently detected in surface water, groundwater, and even drinking water, thereby posing risks to human health. This study reports the development of a polytetrafluoroethylene (PTFE)-based AgNP substrate for the detection of the neonicotinoids imidacloprid (IMD), thiamethoxam (THX), and their mixture in drinking water using the D-SERS (Dynamic-Surface Enhancement Raman Spectroscopy) methodology, together with the development of a class-modeling method based on Soft Independent Modeling of Class Analogy (SIMCA) that allowed the classification of drinking water samples containing one or more pesticides, achieving an efficiency of 97%. This study presents the first reported application of the SIMCA model for the classification of neonicotinoids.