Groundnut Bud Necrosis Virus (GBNV): A New Record for Mungbean in Pakistan

IF 1.1 4区 农林科学 Q3 PLANT SCIENCES Journal of Phytopathology Pub Date : 2025-01-20 DOI:10.1111/jph.70022
Khalid Pervaiz Akhtar, Najeeb Ullah, Muhammad Jawad Asghar, Muhammad Shahid
{"title":"Groundnut Bud Necrosis Virus (GBNV): A New Record for Mungbean in Pakistan","authors":"Khalid Pervaiz Akhtar,&nbsp;Najeeb Ullah,&nbsp;Muhammad Jawad Asghar,&nbsp;Muhammad Shahid","doi":"10.1111/jph.70022","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>Mungbean is an economically important short-duration traditional pulse crop in Pakistan. During a routine inspection of mungbean fields in the summer of 2018, unusual disease symptoms reminiscent of Tospovirus were observed for the first time. These symptoms include severe leaf chlorosis, necrosis, plant stunting and death. To identify the causal virus, symptomatic fresh leaves were analysed following RT-PCR using GBNV-specific primer pair which resulted in the amplification of ~0.8 kbp fragment specific to <i>CP</i> gene of Groundnut bud necrosis virus (GBNV). A representative amplicon was cloned and sequenced. The analysis of the attained sequence confirmed its high resemblance with GBNV earlier reported from different crops in India. The virus was successfully mechanically inoculated onto the mungbean genotype MH-21006 which produced similar symptoms as observed under field conditions. Under the present study, based on the visual assessment, 132 mungbean advanced genotypes and approved varieties were also evaluated against GBNV under field conditions. Data showed that 122 genotypes were resistant with percent disease index (PDI) value ranging from 1.3% to 9.9% while 10 were tolerant with PDI value ranging from 10.3% to 14.2%. Present findings confirm the first natural association of GBNV with mungbean in Pakistan.</p>\n </div>","PeriodicalId":16843,"journal":{"name":"Journal of Phytopathology","volume":"173 1","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Phytopathology","FirstCategoryId":"97","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/jph.70022","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PLANT SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

Mungbean is an economically important short-duration traditional pulse crop in Pakistan. During a routine inspection of mungbean fields in the summer of 2018, unusual disease symptoms reminiscent of Tospovirus were observed for the first time. These symptoms include severe leaf chlorosis, necrosis, plant stunting and death. To identify the causal virus, symptomatic fresh leaves were analysed following RT-PCR using GBNV-specific primer pair which resulted in the amplification of ~0.8 kbp fragment specific to CP gene of Groundnut bud necrosis virus (GBNV). A representative amplicon was cloned and sequenced. The analysis of the attained sequence confirmed its high resemblance with GBNV earlier reported from different crops in India. The virus was successfully mechanically inoculated onto the mungbean genotype MH-21006 which produced similar symptoms as observed under field conditions. Under the present study, based on the visual assessment, 132 mungbean advanced genotypes and approved varieties were also evaluated against GBNV under field conditions. Data showed that 122 genotypes were resistant with percent disease index (PDI) value ranging from 1.3% to 9.9% while 10 were tolerant with PDI value ranging from 10.3% to 14.2%. Present findings confirm the first natural association of GBNV with mungbean in Pakistan.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
求助全文
约1分钟内获得全文 去求助
相关文献
Deep Learning Method Based on Gated Recurrent Unit and Variational Mode Decomposition for Short-Term Wind Power Interval Prediction
IF 10.4 1区 计算机科学IEEE transactions on neural networks and learning systemsPub Date : 2019-11-13 DOI: 10.1109/TNNLS.2019.2946414
Ruoheng Wang;Chaoshun Li;Wenlong Fu;Geng Tang
Ultra-Short-Term Wind Power Prediction Based on Bidirectional Gated Recurrent Unit and Transfer Learning
IF 3.4 4区 工程技术Frontiers in Energy ResearchPub Date : 2021-12-17 DOI: 10.3389/fenrg.2021.808116
Wenjin Chen, Weiwen Qi, Yu Li, Jun Zhang, Feng Zhu, Dongfan Xie, Wei-kang Ru, Gang Luo, Meiya Song, Fei Tang
A robust auto encoder-gated recurrent unit (AE-GRU) based deep learning approach for short term solar power forecasting
IF 3.1 3区 物理与天体物理OptikPub Date : 2022-02-01 DOI: 10.1016/j.ijleo.2021.168515
Amit Rai , Ashish Shrivastava , Kartick C. Jana
来源期刊
Journal of Phytopathology
Journal of Phytopathology 生物-植物科学
CiteScore
2.90
自引率
0.00%
发文量
88
审稿时长
4-8 weeks
期刊介绍: Journal of Phytopathology publishes original and review articles on all scientific aspects of applied phytopathology in agricultural and horticultural crops. Preference is given to contributions improving our understanding of the biotic and abiotic determinants of plant diseases, including epidemics and damage potential, as a basis for innovative disease management, modelling and forecasting. This includes practical aspects and the development of methods for disease diagnosis as well as infection bioassays. Studies at the population, organism, physiological, biochemical and molecular genetic level are welcome. The journal scope comprises the pathology and epidemiology of plant diseases caused by microbial pathogens, viruses and nematodes. Accepted papers should advance our conceptual knowledge of plant diseases, rather than presenting descriptive or screening data unrelated to phytopathological mechanisms or functions. Results from unrepeated experimental conditions or data with no or inappropriate statistical processing will not be considered. Authors are encouraged to look at past issues to ensure adherence to the standards of the journal.
期刊最新文献
Correction to “Identification of Plant Species Using Convolutional Neural Network with Transfer Learning” IoT-Enabled Plant Leaf Disease Detection Using HPJSO_SqueezeNet Rice Sheath Rot: Targeted Approach for Studying the Efficacy of Fungicides and Biocontrol Agents Under Field Conditions of Northern India Potential Distribution of Fusarium Head Blight Under Climate Change Scenarios in Iran Cotton and Soybean Plant Leaf Dataset Generation for Multiclass Disease Classification
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1