Results 11 to 20 of about 34,555 (216)

Analysis of the Mathematical Model for the Spread of Pine Wilt Disease [PDF]

open access: yesJournal of Applied Mathematics, 2013
This paper formulates and analyzes a pine wilt disease model. Mathematical analyses of the model with regard to invariance of nonnegativity, boundedness of the solutions, existence of nonnegative equilibria, permanence, and global stability are presented.
Xiangyun Shi, Guohua Song
doaj   +4 more sources

Pine wilt disease detection algorithm based on improved YOLOv5 [PDF]

open access: yesFrontiers in Plant Science
Pine wilt disease (PWD) poses a significant threat to forests due to its high infectivity and lethality. The absence of an effective treatment underscores the importance of timely detection and isolation of infected trees for effective prevention and control.
Xinyu Zheng, Dasheng Wu
exaly   +5 more sources

Microhabitat Governs the Microbiota of the Pinewood Nematode and Its Vector Beetle: Implication for the Prevalence of Pine Wilt Disease [PDF]

open access: yesMicrobiology Spectrum, 2022
Our understanding of environmental acquisition of microbes and migration-related alteration of microbiota across habitats has rapidly increased. However, in complex life cycles, such as for many parasites, exactly how these microbes are transmitted ...
Haokai Tian   +3 more
doaj   +2 more sources

The Detection of Pine Wilt Disease: A Literature Review. [PDF]

open access: yesInt J Mol Sci, 2022
Pine wilt disease (PWD) is a global quarantine disease of forests that mainly affects Pinaceae species. The disease spreads rapidly. Once infected, pine trees have an extremely high mortality rate. This paper provides a summary of the common techniques used to detect PWD, including morphological-, molecular-, chemical- and physical-based methods.
Li M   +5 more
europepmc   +3 more sources

Insights into the Role of Fungi in Pine Wilt Disease. [PDF]

open access: yesJ Fungi (Basel), 2021
Pine wilt disease (PWD) is a complex disease that severely affects the biodiversity and economy of Eurasian coniferous forests. Three factors are described as the main elements of the disease: the pinewood nematode (PWN) Bursaphelenchus xylophilus, the insect-vector Monochamus spp., and the host tree, mainly Pinus spp.
Vicente CSL   +4 more
europepmc   +6 more sources

Detection of Pine Wilt Nematode from Drone Images Using UAV

open access: yesSensors, 2022
Pine wilt nematode disease is a devastating forest disease that spreads rapidly. Using drone remote sensing to monitor pine wilt nematode trees promptly is an effective way to control the spread of pine wilt nematode disease.
Zhengzhi Sun   +2 more
doaj   +1 more source

A Deep Learning-Based Generalized System for Detecting Pine Wilt Disease Using RGB-Based UAV Images

open access: yesRemote Sensing, 2021
Pine wilt is a devastating disease that typically kills affected pine trees within a few months. In this paper, we confront the problem of detecting pine wilt disease.
Jie You, Ruirui Zhang, Joonwhoan Lee
doaj   +1 more source

MPs, insects and trees: The Pine Wood Nematode in the Portuguese Parliament [PDF]

open access: yesSHS Web of Conferences, 2022
The Pine Wood Nematode (PWN) Bursaphelenchus xylophilus is the causal agent of the pine wilt disease, and a quarantine organism within the European Union.
García-Pereda Ignacio
doaj   +1 more source

Genome Assembly Resource and Annotation of Bursaphelenchus xylophilus TS-1, the Causal Agent of Pine Wilt Disease

open access: yesPhytoFrontiers, 2023
Pine wilt disease is a major biological disaster caused by Bursaphelenchus xylophilus. This study establishes a high-quality and well-annotated genome sequence of B. xylophilus strain TS-1 from Mountain Tai in Shandong province, China.
Jie Li   +6 more
doaj   +1 more source

Detection Methods for Pine Wilt Disease: A Comprehensive Review. [PDF]

open access: yesPlants (Basel)
Pine wilt disease (PWD), caused by the nematode Bursaphelenchus xylophilus, is a highly destructive forest disease that necessitates rapid and precise identification for effective management and control. This study evaluates various detection methods for PWD, including morphological diagnosis, molecular techniques, and remote sensing. While traditional
Tahir S, Hassan SS, Yang L, Ma M, Li C.
europepmc   +4 more sources

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