Plant Disease Detection Using an Electronic Nose

• 全文链接

利用电子鼻检测植物病害

关键词：

来源：

2023 IEEE SENSORS 会议

全文链接：

//agri.nais.net.cn/topic/downloadFile/4d0a5087-fdb7-4c40-843a-3077db4606a6

来源地址：

https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10325015

资源所属：

茶学研究专题

类型：

会议论文

语种：

英语

原文发布日期：

2023-10-29

摘要：

This paper presents experimental results on differentiating between healthy wheat plants and plants infected with Fusarium Head Blight (FHB) based on sensing the ambient gases in the plant environment using a gravimetric electronic nose enabled by a functionalized capacitive micromachined ultrasonic transducer (CMUT) array and machine learning (ML) algorithms. The CMUT sensor array is functionalized with organic/inorganic materials to capture disease-related volatile signals. The sensor data is processed and analyzed using ML algorithms for accurate plant classification. Experimental results demonstrate the effectiveness of the proposed approach in achieving high accuracy for plant disease detection at the end of the 11th day after plant inoculation.