基于无透镜成像的物联网气传病害早期预警系统  

IoT System for Early Warning of Airborne Fungal Diseases Based on Lens-less Imaging

作　　者：李国晓 武君伟 费蒙 韩雨露 魏明吉 Li Guoxiao

机构地区：[1]江苏农林职业技术学院信息工程学院,江苏镇江212400 [2]江苏大学电气信息工程学院,江苏镇江212013

出　　处：《工业控制计算机》2023年第11期59-61,共3页Industrial Control Computer

基　　金：江苏省大学生创新创业训练计划项目成果(项目名称:基于无透镜成像的气传真菌性病害早期预警物联网系统,202113103042y)。

摘　　要：作物真菌性气传病害的特点意味着早期预警和干预能有效提高防治效果。现有孢子监测装置体积大、成本高、空间布局灵活性差,降低了病情评估的准确度。提出了一种基于无透镜成像的便携式孢子监测物联网系统。将空气中的孢子富集于载玻片上,采集24.396 mm2的无透镜成像,所设计的算法获得高质量重建结果,提取包括形态、幅相在内的多维度特征,实现孢子识别和分类。采用该方法对稻瘟病孢子进行富集和浓度检测,结果表明,该方法成像视场大、准确度高、检出限高,能在病害早期预警。其便携式、自动化特点有望为明确气传病害演化规律和预防流行传播提供数据支持。This paper proposes a portable spore-monitoring IoT system based on lens-less imaging.By enriching the spores in the air on the slide and using lens-free images of 24.396 mm2,the designed algorithm can not only obtain high-quality reconstruction results,extract multi-dimensional features including morphology,amplitude and phase,but also complete the recognition and classification of spores.The results show that this method has a large field of view,high accuracy and high detection limit,and can be used for early warning of disease when detecting the enrichment and concentration of rice blast spores by the device.Its portable and automatic characteristics are expected to provide data support for clarifying the evolution law of gas-borne diseases and preventing epidemic transmission.

关 键 词：孢子分析 无透镜成像 识别分类 气传病害 早期预警 便携式 

分 类 号：S432.44[农业科学—植物病理学] TP277[农业科学—农业昆虫与害虫防治]