用于农药灵敏智能分析的荧光传感阵列和逻辑门构筑

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.

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。

农药残留污染一直是人们普遍关注的热点问题，其对环境卫生、食品安全、以及人类健康都具有较大威胁。因此，为了确保广大人民群众的农产品食用安全，研究快速、可靠、高效、选择性好的农药检测方法是非常重要的。项目首先制备了多种性能优异、成本低、稳定性好的荧光传感材料（钙钛矿量子点、石墨烯量子点、荧光共轭聚合物点、上转换纳米粒子、荧光分子探针等）和多种纳米酶。利用它们开发了多个比色和荧光传感器，实现了食品因子、污染物及一些生物功能因子的分析检测，为农药等污染物的智能分析提供了新策略。除此之外，项目对化学阵列传感器以及逻辑门技术展开了深入研究，构筑了多个传感器阵列及逻辑门，实现了对多种农药、金属离子、蛋白质等物质的区分检测，进而应用于矿泉水、牛奶掺假等，为食品品质监控、产品质量监测提供技术支持。总结相关工作，在Food Chem., J. Agric. Food Chem., Sens. Actuator B-Chem.等杂志发表SCI收录学术论文23篇，其中中科院一区TOP期刊7篇。申请国家发明专利4项，授权发明专利1项。