scholarly journals Fusarium falciforme , a pathogen causing wilt disease of chrysanthemum in Vietnam

2021 ◽  
Vol 43 (2) ◽  
Author(s):  
L.D. Thao ◽  
P.T. Anh ◽  
T.T.T. Trang ◽  
T.N. Khanh ◽  
L.T. Hien ◽  
...  
Keyword(s):  
Wilt Disease ◽  
Fusarium Falciforme

scholarly journals First report of Fusarium falciforme (FSSC 3+4) causing wilt disease of Phaseolus vulgaris in Mexico

Plant Disease ◽  
2020 ◽  
Author(s):  
José Francisco Díaz-Nájera ◽  
Sergio Ayvar-Serna ◽  
Antonio Mena-Bahena ◽  
Emiliano Baranda-Cruz ◽  
Mateo Vargas-Hernández ◽  
...  
Keyword(s):  
Phaseolus Vulgaris ◽  
Tap Water ◽  
Wilt Disease ◽  
Healthy Plant ◽  
Pathogenicity Test ◽  
Distilled Water ◽  
Conidial Suspension ◽  
Single Spore ◽  
First Report ◽  
Fusarium Falciforme

Bean (Phaseolus vulgaris) is the second most important crop in Mexico after corn due to the high consumption of beans in all regions of the country. In the winter (January 2016), bean plants showing wilting, root discoloration and necrosis were observed, with an incidence of approximately 30% in different fields (<1 ha) in Tecoanapa, Guerrero State, Mexico. Symptomatic fine roots (<2 mm) were cut into 0.5 cm long pieces, washed with tap-water, surface disinfected with 1.5% NaOCl for 3 min, and rinsed with sterile distilled water. Thirty-five pieces were placed on potato dextrose agar (PDA, Difco) and incubated at 25 ℃ for seven days. Then, single-spore isolates were obtained. Colonies on PDA showed abundant white aerial mycelium and a growth rate of 4.5 mm/day, and in reverse, colonies were white/pink with a brown centre. Microconidia were cylindrical to ellipsoid, aseptate, hyaline and 7.8-(6.0)-4.7 × 2.7-(2.1)-1.6 µm. On carnation leaf agar, macroconidia were 37.8-(29.4)-23.5 × 4.1-(3.5)-2.6 µm, hyaline, falcate, with slightly curved apexes, and 3-5 septa. Chlamydospores were round, intercalary, hyaline, single or in chains (Boot 1971). A representative strain (CSAEGRO-AyDi-Ef) was analyzed by PCR and the translation elongation factor 1-alpha (tef1) gene (GenBank accession number MK945757) was sequenced using the EF-1/EF-2 primers (O’Donnell 2000). FUSARIUM-ID (Geiser et al. 2004) analysis showed 100% similarity with the Fusarium solani species complex (FSSC 3+4) strain NRRL28562. In addition, Bayesian phylogenetic analysis placed this strain in the Fusarium falciforme clade. A pathogenicity test was performed by immersing healthy plant roots (cv. Negro Jamapa) in 200 mL of a conidial suspension (50×106 conidia mL-1) for 10 min, and then transplanting the plants into pots. Control plants were immersed in sterile distilled water. Similar symptoms as those in the field were observed at 10 days after inoculation, and the controls were healthy. The fungus was reisolated from infected plants and showed the same morphology and tef1 sequence as the original isolate, fulfilling Koch’s postulates. Recently, F. falciforme was reported to cause wilting of P. vulgaris in Cuba (Duarte et al. 2019); however, this is the first report of F. falciforme (FSSC 3+4) causing wilt disease of P. vulgaris in Mexico. This species was previously reported in Mexico affecting onion (Tirado-Ramírez et al. 2018), papaya, tomato (Vega-Gutiérrez et al. 2019a, b), and maize (Douriet-Angulo et al. 2019), suggesting an ample host range in the country.

Identification of control agents against melon wilt disease in laboratory and field in NE China

2018 ◽  
Vol 51 (2) ◽  
Author(s):  
Xiaomei Wang ◽  
Zijian Zhao ◽  
Qingmei Chen ◽  
Shao Hongbo
Keyword(s):  
Wilt Disease ◽  
Ne China

Reaction and growth of cucumber hybrids grafted on hybrid squash in response to infection with Fusarium wilt disease

2017 ◽  
Vol 35 (1) ◽  
pp. 027-035
Author(s):  
Alaa Ibrahim ◽  
◽  
Omar Hmmoudi ◽  
George Asmar ◽  
Naser Sheikh Suleiman ◽  
...  
Keyword(s):  
Fusarium Wilt ◽  
Wilt Disease ◽  
Fusarium Wilt Disease

scholarly journals Effects of cavitation on the development of pine wilt disease caused by Bursaphelenchus xylophilus.

1988 ◽  
Vol 54 (5) ◽  
pp. 606-615 ◽  
Author(s):  
Keiko KURODA ◽  
Toshihiro YAMADA ◽  
Kazuhiko MINEO ◽  
Hirotada TAMURA
Keyword(s):  
Pine Wilt Disease ◽  
Bursaphelenchus Xylophilus ◽  
Wilt Disease ◽  
Pine Wilt

scholarly journals Early detection of pine wilt disease in Pinus tabuliformis in North China using a field portable spectrometer and UAV-based hyperspectral imagery

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Run Yu ◽  
Lili Ren ◽  
Youqing Luo
Keyword(s):  
Early Stage ◽  
Vegetation Indices ◽  
Pine Wilt Disease ◽  
Wilt Disease ◽  
Pinus Tabulaeformis ◽  
Pine Tree ◽  
Preventative Measures ◽  
Pine Wilt ◽  
Pine Trees ◽  
Airborne Vehicle

Abstract Background Pine wilt disease (PWD) is a major ecological concern in China that has caused severe damage to millions of Chinese pines (Pinus tabulaeformis). To control the spread of PWD, it is necessary to develop an effective approach to detect its presence in the early stage of infection. One potential solution is the use of Unmanned Airborne Vehicle (UAV) based hyperspectral images (HIs). UAV-based HIs have high spatial and spectral resolution and can gather data rapidly, potentially enabling the effective monitoring of large forests. Despite this, few studies examine the feasibility of HI data use in assessing the stage and severity of PWD infection in Chinese pine. Method To fill this gap, we used a Random Forest (RF) algorithm to estimate the stage of PWD infection of trees sampled using UAV-based HI data and ground-based data (data directly collected from trees in the field). We compared relative accuracy of each of these data collection methods. We built our RF model using vegetation indices (VIs), red edge parameters (REPs), moisture indices (MIs), and their combination. Results We report several key results. For ground data, the model that combined all parameters (OA: 80.17%, Kappa: 0.73) performed better than VIs (OA: 75.21%, Kappa: 0.66), REPs (OA: 79.34%, Kappa: 0.67), and MIs (OA: 74.38%, Kappa: 0.65) in predicting the PWD stage of individual pine tree infection. REPs had the highest accuracy (OA: 80.33%, Kappa: 0.58) in distinguishing trees at the early stage of PWD from healthy trees. UAV-based HI data yielded similar results: the model combined VIs, REPs and MIs (OA: 74.38%, Kappa: 0.66) exhibited the highest accuracy in estimating the PWD stage of sampled trees, and REPs performed best in distinguishing healthy trees from trees at early stage of PWD (OA: 71.67%, Kappa: 0.40). Conclusion Overall, our results confirm the validity of using HI data to identify pine trees infected with PWD in its early stage, although its accuracy must be improved before widespread use is practical. We also show UAV-based data PWD classifications are less accurate but comparable to those of ground-based data. We believe that these results can be used to improve preventative measures in the control of PWD.

Biocontrol of tomato Fusarium wilt disease by a new Moringa endophytic Aspergillus isolates

2021 ◽  
Author(s):  
Ahmed M. Aldinary ◽  
Amer Morsy Abdelaziz ◽  
Ayman A. Farrag ◽  
Mohamed S. Attia
Keyword(s):  
Fusarium Wilt ◽  
Wilt Disease ◽  
Fusarium Wilt Disease

Dynamical aspects of pine wilt disease and control measures

2021 ◽  
Vol 145 ◽  
pp. 110764
Author(s):  
Takasar Hussain ◽  
Adnan Aslam ◽  
Muhammad Ozair ◽  
Fatima Tasneem ◽  
J.F. Gómez-Aguilar
Keyword(s):  
Pine Wilt Disease ◽  
Wilt Disease ◽  
Control Measures ◽  
Pine Wilt ◽  
And Control

scholarly journals Spatiotemporal Pattern of Pine Wilt Disease in the Yangtze River Basin

Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 731
Author(s):  
Zhuoqing Hao ◽  
Jixia Huang ◽  
Yantao Zhou ◽  
Guofei Fang
Keyword(s):  
River Basin ◽  
Yangtze River ◽  
Yangtze River Basin ◽  
Pine Wilt Disease ◽  
Wilt Disease ◽  
Spatiotemporal Pattern ◽  
Pinewood Nematode ◽  
The Yangtze River ◽  
Pine Wilt ◽  
The Yangtze River Basin

The Yangtze River Basin is among the river basins with the strongest strategic support and developmental power in China. As an invasive species, the pinewood nematode (PWN) Bursaphelenchus xylophilus has introduced a serious obstacle to the high-quality development of the economic and ecological synchronization of the Yangtze River Basin. This study analyses the occurrence and spread of pine wilt disease (PWD) with the aim of effectively managing and controlling the spread of PWD in the Yangtze River Basin. In this study, statistical data of PWD-affected areas in the Yangtze River Basin are used to analyse the occurrence and spread of PWD in the study area using spatiotemporal visualization analysis and spatiotemporal scanning statistics technology. From 2000 to 2018, PWD in the study area showed an “increasing-decreasing-increasing” trend, and PWD increased explosively in 2018. The spatial spread of PWD showed a “jumping propagation-multi-point outbreak-point to surface spread” pattern, moving west along the river. Important clusters were concentrated in the Jiangsu-Zhejiang area from 2000 to 2015, forming a cluster including Jiangsu and Zhejiang. Then, from 2015–2018, important clusters were concentrated in Chongqing. According to the spatiotemporal scanning results, PWD showed high aggregation in the four regions of Zhejiang, Chongqing, Hubei, and Jiangxi from 2000 to 2018. In the future, management systems for the prevention and treatment of PWD, including ecological restoration programs, will require more attention.

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