Cargando…

Research Progress on the Early Monitoring of Pine Wilt Disease Using Hyperspectral Techniques

Pine wilt disease (PWD) caused by pine wood nematode (PWN, Bursaphelenchus xylophilus) originated in North America and has since spread to Asia and Europe. PWN is currently a quarantine object in 52 countries. In recent years, pine wilt disease has caused considerable economic losses to the pine for...

Descripción completa

Detalles Bibliográficos
Autores principales: Wu, Weibin, Zhang, Zhenbang, Zheng, Lijun, Han, Chongyang, Wang, Xiaoming, Xu, Jian, Wang, Xinrong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7374340/
https://www.ncbi.nlm.nih.gov/pubmed/32635285
http://dx.doi.org/10.3390/s20133729
_version_ 1783561676173344768
author Wu, Weibin
Zhang, Zhenbang
Zheng, Lijun
Han, Chongyang
Wang, Xiaoming
Xu, Jian
Wang, Xinrong
author_facet Wu, Weibin
Zhang, Zhenbang
Zheng, Lijun
Han, Chongyang
Wang, Xiaoming
Xu, Jian
Wang, Xinrong
author_sort Wu, Weibin
collection PubMed
description Pine wilt disease (PWD) caused by pine wood nematode (PWN, Bursaphelenchus xylophilus) originated in North America and has since spread to Asia and Europe. PWN is currently a quarantine object in 52 countries. In recent years, pine wilt disease has caused considerable economic losses to the pine forest production industry in China, as it is difficult to control. Thus, one of the key strategies for controlling pine wilt disease is to identify epidemic points as early as possible. The use of hyperspectral cameras mounted on drones is expected to enable PWD monitoring over large areas of forest, and hyperspectral images can reflect different stages of PWD. The trend of applying hyperspectral techniques to the monitoring of pine wilt disease is analyzed, and the corresponding strategies to address the existing technical problems are proposed, such as data collection of early warning stages, needs of using unmanned aerial vehicles (UAVs), and establishment of models after preprocessing.
format Online
Article
Text
id pubmed-7374340
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-73743402020-08-06 Research Progress on the Early Monitoring of Pine Wilt Disease Using Hyperspectral Techniques Wu, Weibin Zhang, Zhenbang Zheng, Lijun Han, Chongyang Wang, Xiaoming Xu, Jian Wang, Xinrong Sensors (Basel) Review Pine wilt disease (PWD) caused by pine wood nematode (PWN, Bursaphelenchus xylophilus) originated in North America and has since spread to Asia and Europe. PWN is currently a quarantine object in 52 countries. In recent years, pine wilt disease has caused considerable economic losses to the pine forest production industry in China, as it is difficult to control. Thus, one of the key strategies for controlling pine wilt disease is to identify epidemic points as early as possible. The use of hyperspectral cameras mounted on drones is expected to enable PWD monitoring over large areas of forest, and hyperspectral images can reflect different stages of PWD. The trend of applying hyperspectral techniques to the monitoring of pine wilt disease is analyzed, and the corresponding strategies to address the existing technical problems are proposed, such as data collection of early warning stages, needs of using unmanned aerial vehicles (UAVs), and establishment of models after preprocessing. MDPI 2020-07-03 /pmc/articles/PMC7374340/ /pubmed/32635285 http://dx.doi.org/10.3390/s20133729 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Wu, Weibin
Zhang, Zhenbang
Zheng, Lijun
Han, Chongyang
Wang, Xiaoming
Xu, Jian
Wang, Xinrong
Research Progress on the Early Monitoring of Pine Wilt Disease Using Hyperspectral Techniques
title Research Progress on the Early Monitoring of Pine Wilt Disease Using Hyperspectral Techniques
title_full Research Progress on the Early Monitoring of Pine Wilt Disease Using Hyperspectral Techniques
title_fullStr Research Progress on the Early Monitoring of Pine Wilt Disease Using Hyperspectral Techniques
title_full_unstemmed Research Progress on the Early Monitoring of Pine Wilt Disease Using Hyperspectral Techniques
title_short Research Progress on the Early Monitoring of Pine Wilt Disease Using Hyperspectral Techniques
title_sort research progress on the early monitoring of pine wilt disease using hyperspectral techniques
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7374340/
https://www.ncbi.nlm.nih.gov/pubmed/32635285
http://dx.doi.org/10.3390/s20133729
work_keys_str_mv AT wuweibin researchprogressontheearlymonitoringofpinewiltdiseaseusinghyperspectraltechniques
AT zhangzhenbang researchprogressontheearlymonitoringofpinewiltdiseaseusinghyperspectraltechniques
AT zhenglijun researchprogressontheearlymonitoringofpinewiltdiseaseusinghyperspectraltechniques
AT hanchongyang researchprogressontheearlymonitoringofpinewiltdiseaseusinghyperspectraltechniques
AT wangxiaoming researchprogressontheearlymonitoringofpinewiltdiseaseusinghyperspectraltechniques
AT xujian researchprogressontheearlymonitoringofpinewiltdiseaseusinghyperspectraltechniques
AT wangxinrong researchprogressontheearlymonitoringofpinewiltdiseaseusinghyperspectraltechniques