Evidence map›Paper›PMID 28931732›Full record

ArticleProceedings. Biological sciences2017

Extending the durability of cultivar resistance by limiting epidemic growth rates.

Kevin Carolan, Joe Helps, Femke van den Berg, Ruairidh Bain, Neil Paveley, Frank van den Bosch

Abstract read
In one paragraph

Article in Proceedings. Biological sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

7 citing papers in PubMed.

  1. A new method to measure ECPest management science · 2026
    Article
  2. Article
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  4. Article
  5. Article
  6. Article
  7. The evolutionary origins of pesticide resistance.Biological reviews of the Cambridge Philosophical Society · 2019
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Kevin CarolanRothamsted Research, Harpenden AL5 5LS, UK kevin.carolan@rothamsted.ac.uk.ORCID http://orcid.org/0000-0003-0853-8457
Joe HelpsRothamsted Research, Harpenden AL5 5LS, UK.
Femke van den BergRothamsted Research, Harpenden AL5 5LS, UK.
Ruairidh BainSRUC, Edinburgh EH9 3JG, UK.
Neil PaveleyADAS, High Mowthorpe, Malton, North Yorkshire YO17 8BP, UK.
Frank van den BoschRothamsted Research, Harpenden AL5 5LS, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cultivar resistance is an essential part of disease control programmes in many agricultural systems. The use of resistant cultivars applies a selection pressure on pathogen populations for the evolution of virulence, resulting in loss of disease control. Various techniques for the deployment of host resistance genes have been proposed to reduce the selection for virulence, but these are often difficult to apply in practice. We present a general technique to maintain the effectiveness of cultivar resistance. Derived from classical population genetics theory; any factor that reduces the population growth rates of both the virulent and avirulent strains will reduce selection. We model the specific example of fungicide application to reduce the growth rates of virulent and avirulent strains of a pathogen, demonstrating that appropriate use of fungicides reduces selection for virulence, prolonging cultivar resistance. This specific example of chemical control illustrates a general principle for the development of techniques to manage the evolution of virulence by slowing epidemic growth rates.

Indexed as

AgricultureCrops, AgriculturalDisease ResistanceFungiFungicides, IndustrialGenetics, PopulationPlant DiseasesSelection, GeneticVirulenceFungicides, Industrialevolutionfungicideintegrated disease controlselectionvirulencevirulence management

Identifiers

PMID28931732
PMCPMC5627193

What OpenQuestion holds

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Registered trials

None linked

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.