## 1 Introduction  
Pesticides, whether chemically synthesized or extracted from biological and other natural substances, are widely used to prevent and control diseases, insects, weeds, rodents, and other pests that threaten agriculture and forestry. They are also employed to regulate the growth of plants and insects. With the rapid growth in population and the intensification of global industrialization, pesticides have become an indispensable and important part of agricultural production [1; 2]. The effective use of pesticides helps reduce pests and weeds, thus increasing crop product yield [3; 4]. However, widespread use, coupled with high environmental persistence and human reliance, and the misuse of pesticides has led to significant residues in soil and water [5; 6]. These residues pose serious risks by contaminating food, damaging ecosystems [7; 8; 9], and entering the human body through the food chain, potentially causing health issues and irreversible harm to organs such as the brain, heart, liver, and lungs [10; 11]. Therefore, it is critical to develop sensitive methods for the detection and qualitative and quantitative analysis of pesticide residues to ensure human and environmental safety [12]. Several conventional techniques are employed for pesticide detection, including gas chromatography (GC) [13; 14], mass spectrum (MS) [15], GC-MS [16; 17; 18; 19; 20; 21], high-performance liquid chromatography [22; 23], spectrophotometry, enzyme-linked immunosorbent assays, molecularly imprinted assays, nuclear magnetic resonance spectrometry [24], and electrochemical techniques [25; 26]. While these methods provide high selectivity, sensitivity, and the ability to detect pesticides in complex samples, they also present several notable drawbacks. These include the high cost of instrumentation, lengthy sample preparation procedures, complex sampling techniques, limited portability, and the need for specialized technicians to operate the equipment [27; 28]. Additionally, large-scale analytical methods are often associated with significant manpower and time costs and strict testing conditions and are unsuitable for rapid quantitative detection or real-time, on-site analysis [29]. As a result, there is an urgent need for a simpler, faster, and more user-friendly method that can sensitively and selectively detect pesticide residues in the environment. Fluorescence detection offers a promising alternative, with advantages such as low detection limits, high sensitivity, ease of operation, and rapid response times. Fluorescence detection methods offer several advantages, such as high sensitivity to target analytes, biocompatibility, and high photoluminescence quantum yield [30; 31; 32]. Over the past few decades, researchers have successfully employed these methods for the detection of a wide range of substances [33; 34; 35; 36; 37; 38]. However, additional research is needed to improve the detection of pesticide residues in environmental settings, particularly in aqueous environments where most pesticide residues accumulate, creating a complex detection challenge. In aqueous environments, traditional fluorescent molecules tend to aggregate, resulting in the weakening or quenching of fluorescence, a phenomenon known as aggregation-caused quenching (ACQ). This significantly impairs the performance of fluorescence sensors for detecting pesticide residues [39]. To overcome this challenge, extensive research has been conducted, and one of the most notable breakthroughs is the concept of aggregation-induced emission (AIE), first proposed by [PERSON] et al. [40]. Unlike the ACQ effect, AIE materials exhibit enhanced fluorescence in an aggregated state (e.g., at higher concentrations or in the solid state), providing a novel approach for developing fluorescence-based sensing and detection systems [41; 42]. AIEgens (aggregation-induced emission fluorophores) [43] can emit bright and stable light due to their non-planar structure, which prevents \(\pi\)-\(\pi\) stacking interactions.