Literature DB >> 17408356

Disease cycle approach to plant disease prediction.

Erick D De Wolf1, Scott A Isard.   

Abstract

Plant disease cycles represent pathogen biology as a series of interconnected stages of development including dormancy, reproduction, dispersal, and pathogenesis. The progression through these stages is determined by a continuous sequence of interactions among host, pathogen, and environment. The stages of the disease cycle form the basis of many plant disease prediction models. The relationship of temperature and moisture to disease development and pathogen reproduction serve as the basis for most contemporary plant disease prediction systems. Pathogen dormancy and inoculum dispersal are considered less frequently. We found extensive research efforts evaluating the performance of prediction models as part of operation disease management systems. These efforts appear to be greater than just a few decades ago, and include novel applications of Bayesian decision theory. Advances in information technology have stimulated innovations in model application. This trend must accelerate to provide the disease management strategies needed to maintain global food supplies.

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Year:  2007        PMID: 17408356     DOI: 10.1146/annurev.phyto.44.070505.143329

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


  12 in total

1.  Predicting plant disease epidemics from functionally represented weather series.

Authors:  D A Shah; P A Paul; E D De Wolf; L V Madden
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2019-06-24       Impact factor: 6.237

2.  Aggressiveness Changes in Populations of Didymella pinodes over Winter and Spring Pea Cropping Seasons.

Authors:  G Laloi; J Montarry; M Guibert; D Andrivon; D Michot; C Le May
Journal:  Appl Environ Microbiol       Date:  2016-06-30       Impact factor: 4.792

3.  Development and validation of a weather-based model for predicting infection of loquat fruit by Fusicladium eriobotryae.

Authors:  Elisa González-Domínguez; Josep Armengol; Vittorio Rossi
Journal:  PLoS One       Date:  2014-09-18       Impact factor: 3.240

4.  Predictive Models for Tomato Spotted Wilt Virus Spread Dynamics, Considering Frankliniella occidentalis Specific Life Processes as Influenced by the Virus.

Authors:  Pamella Akoth Ogada; Dany Pascal Moualeu; Hans-Michael Poehling
Journal:  PLoS One       Date:  2016-05-09       Impact factor: 3.240

Review 5.  Biology and Epidemiology of Venturia Species Affecting Fruit Crops: A Review.

Authors:  Elisa González-Domínguez; Josep Armengol; Vittorio Rossi
Journal:  Front Plant Sci       Date:  2017-09-19       Impact factor: 5.753

Review 6.  The Potential Role of Microbial Biostimulants in the Amelioration of Climate Change-Associated Abiotic Stresses on Crops.

Authors:  Ayomide Emmanuel Fadiji; Olubukola Oluranti Babalola; Gustavo Santoyo; Michele Perazzolli
Journal:  Front Microbiol       Date:  2022-01-14       Impact factor: 5.640

7.  Linking climate suitability, spread rates and host-impact when estimating the potential costs of invasive pests.

Authors:  Darren J Kriticos; Agathe Leriche; David J Palmer; David C Cook; Eckehard G Brockerhoff; Andréa E A Stephens; Michael S Watt
Journal:  PLoS One       Date:  2013-02-06       Impact factor: 3.240

8.  Development of a Model to Predict the Primary Infection Date of Bacterial Spot (Xanthomonas campestris pv. vesicatoria) on Hot Pepper.

Authors:  Ji-Hoon Kim; Wee-Soo Kang; Sung-Chul Yun
Journal:  Plant Pathol J       Date:  2014-06       Impact factor: 1.795

9.  A three-year field validation study to improve the integrated pest management of hot pepper.

Authors:  Ji-Hoon Kim; Sung-Chul Yun
Journal:  Plant Pathol J       Date:  2013-09       Impact factor: 1.795

10.  Application of Numerical Weather Prediction Data to Estimate Infection Risk of Bacterial Grain Rot of Rice in Korea.

Authors:  Hyo-Suk Kim; Ki Seok Do; Joo Hyeon Park; Wee Soo Kang; Yong Hwan Lee; Eun Woo Park
Journal:  Plant Pathol J       Date:  2020-02-01       Impact factor: 1.795

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