Campus Units

Plant Pathology and Microbiology

Document Type

Article

Publication Version

Published Version

Publication Date

11-2006

Journal or Book Title

Fitopatologia Brasileira

Volume

31

Issue

6

First Page

533

Last Page

544

DOI

10.1590/S0100-41582006000600001

Abstract

Asian rust of soybean [Glycine max (L.) Merril] is one of the most important fungal diseases of this crop worldwide. The recent introduction of Phakopsora pachyrhiziSyd. & P. Syd in the Americas represents a major threat to soybean production in the main growing regions, and significant losses have already been reported. P. pachyrhizi is extremely aggressive under favorable weather conditions, causing rapid plant defoliation. Epidemiological studies, under both controlled and natural environmental conditions, have been done for several decades with the aim of elucidating factors that affect the disease cycle as a basis for disease modeling. The recent spread of Asian soybean rust to major production regions in the world has promoted new development, testing and application of mathematical models to assess the risk and predict the disease. These efforts have included the integration of new data, epidemiological knowledge, statistical methods, and advances in computer simulation to develop models and systems with different spatial and temporal scales, objectives and audience. In this review, we present a comprehensive discussion on the models and systems that have been tested to predict and assess the risk of Asian soybean rust. Limitations, uncertainties and challenges for modelers are also discussed.

Comments

This article is from Fitopatologia Brasileira 31 (2006): 533–544, doi:10.1590/S0100-41582006000600001. Posted with permission.

Rights

All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License

Language

en

File Format

application/pdf

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