Emerging Themes and Approaches in Plant Virus Epidemiology

生物 寄主(生物学) 植物病毒 载体(分子生物学) 传输(电信) 领域(数学) 疾病 流行病学 病毒 生物技术 生态学 风险分析(工程) 病毒学 计算机科学 遗传学 医学 电信 基因 重组DNA 内科学 数学 病理 纯数学
作者
Michael Jeger,Nik J. Cunniffe,Fred Hamelin
出处
期刊:Phytopathology [American Phytopathological Society]
卷期号:113 (9): 1630-1646 被引量:3
标识
DOI:10.1094/phyto-10-22-0378-v
摘要

Plant diseases caused by viruses share many common features with those caused by other pathogen taxa in terms of the host-pathogen interaction, but there are also distinctive features in epidemiology, most apparent where transmission is by vectors. Consequently, the host-virus-vector-environment interaction presents a continuing challenge in attempts to understand and predict the course of plant virus epidemics. Theoretical concepts, based on the underlying biology, can be expressed in mathematical models and tested through quantitative assessments of epidemics in the field; this remains a goal in understanding why plant virus epidemics occur and how they can be controlled. To this end, this review identifies recent emerging themes and approaches to fill in knowledge gaps in plant virus epidemiology. We review quantitative work on the impact of climatic fluctuations and change on plants, viruses, and vectors under different scenarios where impacts on the individual components of the plant-virus-vector interaction may vary disproportionately; there is a continuing, sometimes discordant, debate on host resistance and tolerance as plant defense mechanisms, including aspects of farmer behavior and attitudes toward disease management that may affect deployment in crops; disentangling host-virus-vector-environment interactions, as these contribute to temporal and spatial disease progress in field populations; computational techniques for estimating epidemiological parameters from field observations; and the use of optimal control analysis to assess disease control options. We end by proposing new challenges and questions in plant virus epidemiology.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
包容语蝶发布了新的文献求助10
刚刚
xxx发布了新的文献求助10
1秒前
2秒前
v0id应助瑆姀采纳,获得10
5秒前
5秒前
6秒前
6秒前
7秒前
7秒前
8秒前
科研狗完成签到,获得积分10
8秒前
9秒前
9秒前
黄燕发布了新的文献求助10
10秒前
10秒前
11秒前
11秒前
卷心菜发布了新的文献求助10
12秒前
c182484455完成签到,获得积分10
12秒前
12秒前
小蘑菇应助机智的小七采纳,获得10
12秒前
12秒前
32414额3发布了新的文献求助10
12秒前
所所应助安宁盛世采纳,获得10
13秒前
13秒前
一枝梅完成签到,获得积分10
13秒前
Wenbin发布了新的文献求助10
14秒前
newnew完成签到,获得积分10
15秒前
beauty_bear完成签到,获得积分10
15秒前
hhhhhhh发布了新的文献求助10
16秒前
moca发布了新的文献求助10
16秒前
柠木完成签到,获得积分10
17秒前
核桃发布了新的文献求助10
18秒前
呆萌语梦发布了新的文献求助10
18秒前
Owen应助ye采纳,获得30
18秒前
迷路初兰完成签到,获得积分10
19秒前
科研通AI6.4应助spolo采纳,获得20
19秒前
沉静的吐司完成签到,获得积分10
19秒前
华仔应助兴奋的千筹采纳,获得10
19秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Markov Chain Monte Carlo 5000
Weaponeering: An Introduction Fourth Edition, Volume 1 1000
Advanced Weaponeering Fourth Edition, Volume 2 1000
Evidence Summary. Injection (subcutaneous):op- timal administration 1000
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 700
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7493135
求助须知:如何正确求助?哪些是违规求助? 9084663
关于积分的说明 19374744
捐赠科研通 7105191
什么是DOI,文献DOI怎么找? 3249487
关于科研通互助平台的介绍 2418969
邀请新用户注册赠送积分活动 2235064