Pine wood nematode disease, also known as pine wilt disease, is a devastating forest disease caused by pine wood nematode (Bursaphelenchus xylophilus). It is a major alien invasive species in China and has been included in the domestic and external forest plant quarantine targets. It can cause pine trees to die within 60-90 days after infection, spread rapidly, and cause severe disasters of large-scale deforestation in 3-5 years, and it is extremely difficult to prevent and cause a large number of pine tree deaths in China, Japan and South Korea. Also known as pine cancer, smokeless forest fire.
个省（或直辖市）为潜在适生分布范围。 The status quo of pine wood nematode in China makes monitoring of pine wood nematode disease unmissable. According to the causes of pine wood nematode disease, some experts apply theories and methods such as fuzzy comprehensive evaluation, geographic information system, and geostatistics. They believe that there are 22 provinces in China (Or municipality) is the potential suitable distribution range.
Pine wood nematode disease monitoring is a key method for the prevention and control of pine wood nematodes. Traditional pine wood nematode disease conventional monitoring mainly uses artificial on-site investigation methods. Due to the large area of pine forests in China, and most of the pine forests are distributed in dense mountainous areas, manual monitoring is time-consuming and labor-intensive. 、 5月或秋季9 、 10月按照森林资源小班分布图进行拉网式踏查，主要通过肉眼、望远镜观察树木生长状况，使用采样工具采集疑似病木，手工记录踏查数据等方式进行。 Staff members perform pull-net inspections in accordance with the distribution map of forest resources in April , May or autumn in September and October each year. They mainly observe the tree growth status with the naked eye and telescope, use sampling tools to collect suspected diseased trees, and manually record the inspection data. And so on. The advantage of manual inspection is that it can penetrate into the forest land to ensure no dead ends, but the naked eye can easily lead to untimely detection of atypical symptoms, and the forest resources occupy a large area and space, and manual monitoring is time-consuming and labor-intensive. Once the symptoms are obvious, the situation is difficult Control, it is urgent to find a faster and more convenient monitoring method.
At present, reports of the practical application of the Internet of Things technology in forestry occasionally occur in forest fire monitoring, and there are also reports on the protection of ancient and famous trees. There are reports that five forestry plant quarantine traceability systems across the country are being piloted. The Internet of Things is rarely reported in pine wood nematode monitoring applications. Some studies have reported on the monitoring and prediction of pine wood nematode disease using remote sensing technology, and remote sensing technology also belongs to the Internet of Things category. It can be seen that there is great space for the application of the Internet of Things technology in forestry pest monitoring.
The occurrence and prevalence of pine wood nematode disease are closely related to host tree species, environmental conditions, and vector insects. The disease is transmitted by short-range insects such as Monochamus alternatus. 度高速高清监视器，在某一区域进行动态跟踪，当监视器捕捉到的传播媒介影像与系统内设置的松材线虫传播媒介影像资料吻合时，系统自动预警，提示传播媒介出现，同时可根据传播媒介捕捉数量进而预测危害发生程度。 You can use a 360- degree high-speed high-definition monitor to perform dynamic tracking in a certain area. When the transmission media image captured by the monitor matches the pine wood nematode transmission media image data set in the system, the system automatically warns and prompts the transmission medium to appear At the same time, the extent of hazards can be predicted based on the number of media captures.
Blue discoloration is an important indicator for judging the infection of pine wood nematode. The use of sensors and interventional syringes is very helpful for judging whether the plant is infected with the disease. ℃以上时，可以启动介入式自动注射器向松树植株注射蓝变试剂，试剂注射量和频率随温度增加而增加，传感器捕捉到蓝变信息后立即反馈给中心控制系统，系统发出危险预警，同时开启其他相关工作程序确定病源信息。 When the ambient temperature reaches 10 ℃ or more, the interventional auto-injector can be used to inject the blue change reagent into the pine plant. The amount and frequency of the reagent injection increase with the increase of temperature. The sensor will immediately feed back the central control system after capturing the blue change information. Danger early warning, and start other related work procedures to determine the source of the disease.
Pathogen symptoms and extent monitoring
The typical symptoms of the disease can be divided into four stages: in the early stage of susceptibility, the plant looks normal, but the resin secretion begins to decrease; in the early stage of susceptibility, the resin secretion is stopped, the transpiration is weakened, some needles become yellow, and the tree is visible. In the middle and late stages of susceptibility, most of the coniferous leaves turned yellow, with symptoms of withering and visible scabs; in the late stage of susceptibility, the entire crown needles changed from yellow to brown or reddish brown, and the whole plant died. In the four stages of the disease, sensors can be used to measure the amount of resin secreted and the intensity of transpiration, the leaf color can be identified by a living leaf analyzer, the disease symptoms can be captured by a high-definition monitor, and the disease can also be monitored by remote sensing imaging technology. Various data are collected and analyzed through the central control system to determine the degree of infection.
测，实现监测数据网络共享，实现对重点林业有害生物发生发展状况可视化实时跟踪掌握，大幅提高监测和预报水平。 With the help of the Internet of Things technology and a small number of ground manual monitoring teams, a forest biological disaster ground monitoring system that is suitable for China's national conditions, can be widely promoted and applied, and realizes network information sharing, realizes grid-based networked professional monitoring , and monitor data network sharing Realize the real-time visual tracking of the occurrence and development of key forestry pests, and greatly improve the level of monitoring and forecasting. Let "data speak", improve the accuracy and timeliness of disease judgment, and fight for valuable time to eliminate epidemics in the later period and slow the spread of epidemics.