College of Mechanical and Electrical Engineering, Henan Agricultural University, Zhengzhou 450002, China; Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment & Technology, School of Intelligent Manufacturing, Jiangnan University, Wuxi 214122, China.
College of Mechanical and Electrical Engineering, Henan Agricultural University, Zhengzhou 450002, China.
Food Chem. 2025 Jan 15;463(Pt 2):141205. doi: 10.1016/j.foodchem.2024.141205. Epub 2024 Sep 10.
A novel approach combing a fluorescent microfluidic paper strip with a portable smartphone-based sensing platform is developed for rapid and sensitive detection of omethoate pesticide. The detection mechanism of the microfluidic paper strip is based on the fluorescence quenching of graphene oxide (GO) toward the cyanine 3 (Cy3)-labeled aptamer (Cy3-APT). Upon exposure to omethoate, the Cy3-APT detaches from the surface of GO, resulting in considerable fluorescence recovery, which can be visualized through the smartphone-based sensing platform. The images are analyzed through a self-developed app embedded with a pretrained convolutional neural network model, achieving a high regression coefficient of 0.9964 at an omethoate concentration range of 0-750 nM. The smartphone-based platform enables rapid on-site detection of omethoate pesticide in real samples within 10 min, with results comparable to those obtained using standard methods. In short, the proposed microfluidic paper-based fluorescent sensor combined with the smartphone-based sensing platform enhances the detection performance toward organophosphorus pesticides.
一种结合荧光微流控纸条和便携式智能手机感应平台的新方法被开发出来，用于快速灵敏地检测氧乐果农药。微流控纸条的检测机制基于氧化石墨烯（GO）对花菁 3（Cy3）标记的适体（Cy3-APT）的荧光猝灭。暴露于氧乐果后，Cy3-APT 从 GO 表面脱离，导致荧光显著恢复，这可以通过基于智能手机的感应平台可视化。通过嵌入经过预先训练的卷积神经网络模型的自开发应用程序对图像进行分析，在 0-750 nM 的氧乐果浓度范围内实现了 0.9964 的高回归系数。基于智能手机的平台能够在 10 分钟内快速现场检测实际样品中的氧乐果农药，结果可与标准方法相媲美。总之，提出的结合智能手机感应平台的基于微流控纸的荧光传感器提高了对有机磷农药的检测性能。
