农业机械学报2024，Vol.55Issue(6)：210-218,9.DOI:10.6041/j.issn.1000-1298.2024.06.022
柑橘木虱YOLO v8-MC识别算法与虫情远程监测系统研究
Research on Asian Citrus Psyllid YOLO v8-MC Recognition Algorithm and Insect Remote Monitoring System
摘要
Abstract
The Asian citrus psyllid(ACP)serves as the primary vector for Huanglongbing(HLB),a citrus tree disease with potentially devastating consequences for citrus orchards.In order to achieve efficient monitoring of ACP populations,an intelligent monitoring system capable of insect trapping,pest identification,and result visualization was developed.A monitoring device equipped with an automatic renewal mechanism for the insect trapping tape and real-time image capturing was designed.To improve the performance of the YOLO v8 model for ACP recognition,targeted cropping and Mosaic data augmentation techniques were employed to effectively expand the ACP dataset,addressing issues related to limited sample size and constrained positioning in the datasets.The application of a coordinate attention(CA)mechanism guided the model to comprehensively consider both channel and spatial information,thereby enhancing its ability to accurately locate the target psyllids.Additionally,the Web interface and mobile APP were developed to enable data visualization and remote control.During the model testing phase,the improved YOLO v8-MC achieved significant better performance than the baseline model,reaching 91.20％,91％,and 90.60％in terms of recall rate,F1 score,and precision,respectively.In the field experiment,the model exhibited a recall rate of 88.64％,an F1 score of 87％and a precision of 84.78％,and the system operated effectively,meeting the requirements for field applications.In conclusion,the intelligent monitoring system developed enabled remote monitoring of ACP populations in orchards,providing an efficient mehtod for the management and control of such pest infestations.关键词
柑橘木虱/虫害监测/诱捕监测装置/YOLO v8-MCKey words
Asian citrus psyllid/pest monitoring/trap monitoring device/YOLO v8-MC分类
农业科技引用本文复制引用
李善军,梁千月,余勇华,陈耀晖,付慧敏,张宏宇..柑橘木虱YOLO v8-MC识别算法与虫情远程监测系统研究[J].农业机械学报,2024,55(6):210-218,9.基金项目
国家柑橘产业技术体系项目(CARS-Citrus)、国家重点研发计划项目(2021YFD1400802-4、2020YFD1000101、2021YFD1400802-44)和柑橘全程机械化科研基地建设项目(农计发[2017]19号) （CARS-Citrus）
