我国农药滥用问题严重，威胁公共健康。着眼于现有的基于酶抑制作用的农药比色检测方法在灵敏度和选择性方面的诸多不足，申请项目将利用多种多色荧光量子点（半导体量子点、石墨烯量子点和共轭聚合物量子点）作为信号输出，利用多种酶（胆碱酯酶、磷酸酯酶、抗坏血酸氧化酶、单胺氧化酶）作为农药识别单元，开发高灵敏的果蔬中农药残留荧光分析新方法；并基于不同农药对几种酶的抑制效果差异，结合多种新颖的阵列传感技术和逻辑门技术，进行具有相似主体结构的农药的特异性区分，以及多种农药的智能识别和分析。该方法检测灵敏度高、特异性强、准确性好，并有望实现同种属农药的特异性区分——农药快速检测方法的一个挑战。

In China, pesticide abuse is a serious threat to public health. Focusing on the disadvantages (low sensitivity and selectivity) of colorimetric detection methods for pesticides based on enzyme inhibition, the project will develop a series of highly sensitive fluorescence technics for pesticides in fruits and vegetables using multi-color fluorescent quantum dots (semiconductor quantum dots, graphene quantum dots and conjugated polymer dots, etc.) as signal outputs, and using enzymes (alkaline esterase, phosphatase, ascorbate oxidase, monoamine oxidase, etc.) as identification units for pesticides. The project will also involve the specific differentiation of pesticides with similar chemical structures and intelligent identification of pesticides, based on the difference of inhibition effect of the pesticides on various enzymes and combined with multidimensional array technology and logic gates. Our methods are expected to be sensitive, selective and precise, and are expected to achieve the identification of pesticides with similarity main structure --- a challenge for pesticide detection methods.