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.

Keywords

modeling; Bayesian decision theory; epidemiology; disease triangle

Published in

Annual Review of Phytopathology
2015, Volume: 53, pages: 471-484
Publisher: ANNUAL REVIEWS, 4139 EL CAMINO WAY, PO BOX 10139, PALO ALTO, CA 94303-0897 USA

SLU Authors

• Yuen, Jonathan

  • Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences
    

Associated SLU-program

SLU Plant Protection Network


UKÄ Subject classification

Botany
Agricultural Science


Publication identifier

DOI: https://doi.org/10.1146/annurev-phyto-080614-120406

Permanent link to this page (URI)

https://res.slu.se/id/publ/76175