一种检测病原体的锌空气燃料电池自供能水凝胶传感器、传感装置及其制备方法和应用
By combining a zinc-air fuel cell self-powered hydrogel sensor with DNA molecule recognition and nucleic acid amplification reaction, along with machine learning algorithms, a highly sensitive and specific detection of sugarcane top rot was achieved, overcoming the shortcomings of traditional detection methods and making it suitable for resource-scarce environments in the field.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- GUANGXI UNIV FOR NATITIES
- Filing Date
- 2026-05-15
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies are insufficient for the rapid and accurate detection of sugarcane top rot, especially in resource-scarce environments. Furthermore, traditional biosensors suffer from poor stability and difficulty in eliminating environmental noise interference during signal analysis. The detection sensitivity and specificity are also limited when powered by a zinc-air fuel cell.
By combining DNA molecular recognition technology with nucleic acid amplification reaction, the oxygen reduction catalyst is targetedly released through a self-powered hydrogel sensor in a zinc-air fuel cell. The optimal model is then selected using machine learning algorithms to perform intelligent signal analysis and precise quantification.
It improves the sensitivity and specificity of pathogen detection, adapts to changing environments, simplifies the operation process, reduces costs, is suitable for portable devices, and is applicable to early warning and precise control of sugarcane top rot.
Smart Images
Figure CN122193335B_ABST