Evidence map›Paper›PMID 21127356›Full record

ArticleAnnals of botany2011

Switching from a mechanistic model to a continuous model to study at different scales the effect of vine growth on the dynamic of a powdery mildew epidemic.

Jean-Baptiste Burie, Michel Langlais, Agnès Calonnec

Abstract read
In one paragraph

Article in Annals of botany, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Pathogenicity Traits Correlate With the SusceptibleFrontiers in plant science · 2018
    Article
  5. Article
  6. Article
  7. Microbial biogeography of wine grapes is conditioned by cultivar, vintage, and climate.Proceedings of the National Academy of Sciences of the United States of America · 2014
    Article
  8. Article
  9. Article
  10. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Jean-Baptiste BurieUMR CNRS IMB & INRIA EPI Anubis, Université Victor Segalen Bordeaux, France.
Michel Langlais
Agnès Calonnec

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

aimsEpidemiological simulation models coupling plant growth with the dispersal and disease dynamics of an airborne plant pathogen were devised for a better understanding of host-pathogen dynamic interactions and of the capacity of grapevine development to modify the progress of powdery mildew epidemics.

methodsThe first model is a complex discrete mechanistic model (M-model) that explicitly incorporates the dynamics of host growth and the development and dispersion of the pathogen at the vine stock scale. The second model is a simpler ordinary differential equations (ODEs) compartmental SEIRT model (C-model) handling host growth (foliar surface) and the ontogenic resistance of the leaves. With the M-model various levels of vine development are simulated under three contrasting climatic scenarios and the relationship between host and disease variables are examined at key periods in the epidemic process. The ability of the C-model to retrieve the main dynamics of the disease for a range of vine growth given by the M-model is investigated. KEY

resultsThe M-model strengthens experimental results observed regarding the effect of the rate of leaf emergence and of the number of leaves at flowering on the severity of the disease. However, it also underlines strong variations of the dynamics of disease depending on the vigour and indirectly on the climatic scenarios. The C-model could be calibrated by using the M-model provided that different parameters before and after shoot topping and for various vigour levels and inoculation time are used. Biologically relevant estimations of the parameters that could be used for its extension to the vineyard scale are obtained.

conclusionsThe M-model is able to generate a wide range of growth scenarios with a strong impact on disease evolution. The C-model is a promising tool to be used at a larger scale.

Indexed as

Models, BiologicalAlgorithmsAscomycotaClimateComputer SimulationCrops, AgriculturalEpidemicsEpidemiologic MethodsFranceHost-Pathogen InteractionsImaging, Three-DimensionalImmunity, InnatePlant DiseasesPlant LeavesPlant StemsVitis

Identifiers

PMID21127356
PMCPMC3077982

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.