Pine wilt disease

Ye, Jian‐Ren; Wu, Xiao‐Qin; Sun, Hui

doi:10.1016/b978-0-443-18694-3.00010-9

Cited by 10 publications

(14 citation statements)

References 49 publications

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“…In China, since its first discovery at the Sun Yat-sen Mausoleum of NanJing in 1982, PWD has rapidly spread and caused irreparable losses [4,5]. The pathogenic pine wood nematode causes pine wilt rapidly and its pathogenesis is complex, which has not been fully understood [6].…”

Section: Introductionmentioning

confidence: 99%

Exploring the Potential of UAV-Based Hyperspectral Imagery on Pine Wilt Disease Detection: Influence of Spatio-Temporal Scales

2023

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Pine wilt disease (PWD), caused by pine wood nematode (PWN, Bursaphelenchus xylophilus), poses a serious threat to the coniferous forests in China. This study used unmanned aerial vehicle (UAV)-based hyperspectral imaging conducted at different altitudes to investigate the impact of spatio-temporal scales on PWD detection in an monoculture Masson pine plantation. The influence of spatio-temporal scales on hyperspectral responses of pine trees infected with PWD and detection accuracies were evaluated by Jeffries–Matusita (J-M) distances and the random forest (RF) algorithm. The optimal vegetation indices (VIs) and spatial resolutions were identified by comparing feature importance and model accuracy. The main results showed that the VIs and J-M distances were greatly affected by spatio-temporal scales. In the early, mid-, and late infection stages, the RF-based PWD detection model had accuracies ranging between 72.05 and 79.48%, 83.71 and 89.59%, and 96.81 and 99.28%, peaking at the 10 cm, 8 cm, and 4 cm spatial resolutions, respectively. The green normalized difference vegetation index (GNDVI) and red edge position (REP) were the optimal VIs in early and mid-infection stages, respectively. This study can be important to improve the efficiency of PWD detection and reducing the loss of forests resources.

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Section: Introductionmentioning

confidence: 99%

Exploring the Potential of UAV-Based Hyperspectral Imagery on Pine Wilt Disease Detection: Influence of Spatio-Temporal Scales

2023

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“…Pinus and Larix are natural host trees of PWNs in China [18]. PWNs can naturally infect at least 17 species in China [79]. They are Pinus armandii, P. bungeana, P. densiflora, P. elliottii, P. kesiya, P. koraiensis, P. luchuensis, P. massoniana, P. sylvestris var.…”

Section: Pwn Host Trees and Non-host Trees In Chinamentioning

confidence: 99%

“…mongolica, P. tabuliformis, P. taeda, P. taiwanensis, P. thunbergia, P. yunnanensis, Larix gmelinii var. principis-rupprechtii, L. kaempferi, and L. olgensis [79].…”

Section: Pwn Host Trees and Non-host Trees In Chinaunclassified

Pine Wilt Disease in Northeast and Northwest China: A Comprehensive Risk Review

Zhang

et al. 2023

Forests

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Pine wilt disease (PWD) caused by the pine wood nematode (PWN) is China’s most serious forest disease in recent decades. Its complex disease system with unclear pathogenesis and differentiated pathogenicity makes it challenging to manage and control. PWD has spread rapidly in Northeast and Northwest China in recent years, exceeding previous predictions and the traditional understanding of its potential distribution. This paper reviewed the comprehensive risk of PWD in Northeast and Northwest China through the occurrence of influencing factors. Regarding PWN’s temperature resistance, all regions of China are suitable for PWD. In terms of altitude, the PWD system is mainly distributed below 1000 m. In China, Pinus and Larix species are confirmed host trees of PWN, while Monochamus alternatus and M. saltuarius are confirmed vector insects of PWN. In this case, PWD may occur in all low-altitude pine forests in China. Northeast China has a higher risk than Northwest China due to its distribution of suitable host trees and vector beetles at low altitudes. To confront the threat, two scientific bottlenecks are required to be demonstrated. The first is the pathogenicity of Chinese PWN strains to Chinese Picea and Abies species. The other is the geographical distribution and highest altitude distribution of other Monochamus species in the Palaearctic region of China and their PWN transmission ability. We also suggest strengthening plant quarantining in Northeast China. In conclusion, this review comprehensively analyzes the risk of PWD in Northeast and Northwest China in terms of temperature, altitude, host trees, and vector insects. It provides a new perspective and reference for the management and research of PWD in China.

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“…The nematode causes millions of dollars in losses annually and has been listed as a quarantine organism in many regions. Following its introduction to East Asia, the PWN triggered catastrophic consequences in pine forests, attributed to shifts in hosts, vector insects, and environmental conditions ( Ye and Wu, 2022 ). PWN has the ability to survive in environments with annual average temperatures below 10°C.…”

Section: Introductionmentioning

confidence: 99%

Response analysis of Pinus sibirica to pine wood nematode infection through transcriptomics and metabolomics study

Zhang,

Ye,

Chen

et al. 2024

Front. Plant Sci.

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Pinus sibirica is primarily distributed in Siberia. Owing to its excellent cold resistance and development potential, it has become an important introduced tree species in the Greater Xing’an area of China. Pine wilt disease, triggered by the pine wood nematode (PWN, Bursaphelenchus xylophilus), constitutes a profoundly critical affliction within forest ecosystems. Its incidence has extended to the northeastern region of China in recent years. To explore the potential host status of P. sibirica in the Greater Xing’an area for PWN and to elucidate the responses following inoculation, artificial inoculation, transcriptomics, and metabolomics methods were used. In the artificial inoculation experiments, quantitative analysis of nematode populations within the trees demonstrated that PWN exhibited normal growth and reproductive capabilities within P. sibirica. Subsequently, transcriptome and metabolome sequencing were conducted at four time points before disease onset (3-, 5-, 7-, and 9-days post inoculation). Gene trend analysis and differentially expressed gene screening were employed and the results indicated that genes associated with the flavonoid biosynthesis pathway exhibited predominant enrichment among the up-regulated genes. Metabolome analysis showed that the abundance of flavonoid-related metabolites in P. sibirica increased after inoculation with PWN. Integrated analysis of transcriptome and metabolome revealed that after PWN inoculation in P. sibirica, two chalcone synthase (chs) genes and a chalcone isomerase (chi) gene were significantly upregulated, and the upregulation should accumulate naringenin, pinocembrin, and apigenin to help P. sibirica resist infection of PWN. The results suggested that flavonoid biosynthesis pathway continued to respond after P. sibirica was infected with PWN and played an important role in the interaction between P. sibirica and PWN.

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Pine wilt disease

Cited by 10 publications

References 49 publications

Exploring the Potential of UAV-Based Hyperspectral Imagery on Pine Wilt Disease Detection: Influence of Spatio-Temporal Scales

Exploring the Potential of UAV-Based Hyperspectral Imagery on Pine Wilt Disease Detection: Influence of Spatio-Temporal Scales

Pine Wilt Disease in Northeast and Northwest China: A Comprehensive Risk Review

Response analysis of Pinus sibirica to pine wood nematode infection through transcriptomics and metabolomics study

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