Literature DB >> 26047560

Landscape-scale disease risk quantification and prediction.

Jonathan Yuen1, Asimina Mila.   

Abstract

The study of plant disease epidemics at a landscape scale can be extended to allow for predictions about disease occurrence at this scale. Examined within the context of the disease triangle, systems developed to incorporate information primarily about the pathogen and conditions conducive to the infection process. Parametric methods can be used to relate environmental conditions to disease, and specifically relate environment to the inoculum production, the resulting infection process, or both. Aspects relating to the presence or absence of the host plant within the landscape, or patterns of the host within the landscape, are much rarer in disease prediction, although analyses incorporating these factors have been conducted. Predictive systems at the landscape scale may concentrate only on the conditions for infection or possible migratory paths of pathogen propagules. Incorporation of all components of the disease triangle may be one way to improve these systems.

Entities:  

Keywords:  Bayesian decision theory; disease triangle; epidemiology; modeling

Mesh:

Year:  2015        PMID: 26047560     DOI: 10.1146/annurev-phyto-080614-120406

Source DB:  PubMed          Journal:  Annu Rev Phytopathol        ISSN: 0066-4286            Impact factor:   13.078


  4 in total

1.  Modelling coffee leaf rust risk in Colombia with climate reanalysis data.

Authors:  Daniel P Bebber; Ángela Delgado Castillo; Sarah J Gurr
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2016-12-05       Impact factor: 6.237

2.  Population Genomic Analysis Reveals a Highly Conserved Mitochondrial Genome in Fusarium asiaticum.

Authors:  Meixin Yang; Hao Zhang; Theo A J van der Lee; Cees Waalwijk; Anne D van Diepeningen; Jie Feng; Balázs Brankovics; Wanquan Chen
Journal:  Front Microbiol       Date:  2020-05-05       Impact factor: 5.640

Review 3.  A Landscape of Opportunities for Microbial Ecology Research.

Authors:  Cendrine Mony; Philippe Vandenkoornhuyse; Brendan J M Bohannan; Kabir Peay; Mathew A Leibold
Journal:  Front Microbiol       Date:  2020-11-20       Impact factor: 5.640

4.  Spatial distribution and identification of potential risk regions to rice blast disease in different rice ecosystems of Karnataka.

Authors:  Chittaragi Amoghavarsha; Devanna Pramesh; Shankarappa Sridhara; Balanagouda Patil; Sandip Shil; Ganesha R Naik; Manjunath K Naik; Shadi Shokralla; Ahmed M El-Sabrout; Eman A Mahmoud; Hosam O Elansary; Anusha Nayak; Muthukapalli K Prasannakumar
Journal:  Sci Rep       Date:  2022-05-06       Impact factor: 4.996

  4 in total

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