Neonicotinoids such as imidacloprid (IMI) and thiamethoxam (THMX), together with paraquat (PQ), are widely used agrochemicals that pose significant environmental and food safety risks due to their toxicity and persistence. Simultaneous electrochemical detection of these pesticides remains challenging because of intrinsically overlapping redox signals. Unlike conventional graphene-based electrochemical sensors that rely on peak separation, this work introduces a factorial design–assisted strategy enabling quantitative interpretation of overlapping responses and simultaneous group detection of structurally similar neonicotinoid pesticides. A chemometric-assisted electrochemical sensing approach was developed for rapid, reliable, and on-site analysis using a carbon paste electrode modified with nickel-decorated reduced graphene oxide (Ni–rGO/CPE). To the best of our knowledge, this represents one of the first application of a Ni–rGO composite combined with factorial design to quantitatively evaluate a multi-analyte pesticide system. Carbon paste electrodes served as a low-cost, versatile proof-of-concept platform. The Ni–rGO/CPE exhibited enhanced electron-transfer properties and stable electrochemical performance, confirmed by cyclic voltammetry and electrochemical impedance spectroscopy. Differential pulse voltammetry enabled detection with limits of 0.77 ppm for IMI, 1.63 ppm for THMX, and 0.70 ppm for PQ, with linear response ranges of 3–154 ppm (IMI), 4–110 ppm (THMX), and 3–119 ppm (PQ). The sensor demonstrated good reproducibility (RSD = 5.2% for IMI and 5.6% for PQ). Factorial analysis identified THMX as the dominant contributor, while PQ exhibited a suppressive interference effect, enabling quantitative interpretation of mixed-analyte responses. The method was successfully validated in river water and mandarin samples, demonstrating satisfactory accuracy and reproducibility, with recoveries of 88.5–112.6% for IMI and 76.9–108.1% for mixed solutions. This work demonstrates the potential of graphene-based nanocomposites combined with factorial design as a scalable strategy for multi-analyte pesticide detection, with further improvements achievable through integration into printed electrode systems for practical on-site monitoring.
Kulla et al. (Sun,) studied this question.