Evidence map›Paper›PMID 37228168›Full record

ArticlePLoS computational biology2023

The proportion of resistant hosts in mixtures should be biased towards the resistance with the lowest breaking cost.

Pauline Clin, Frédéric Grognard, Didier Andrivon, Ludovic Mailleret, Frédéric M Hamelin

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.6field-weighted citation impact, top 14% of its field
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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Review
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

5 authors at 2 institutions in 1 country.

Pauline ClinInstitut Agro, Univ Rennes, INRAE, IGEPP, Rennes, France.ORCID 0000-0002-7176-1451
Frédéric GrognardUniversité Côte d'Azur, Inria, INRAE, CNRS, Sorbonne Université, Biocore, Sophia-Antipolis, France.
Didier AndrivonInstitut Agro, Univ Rennes, INRAE, IGEPP, Rennes, France.
Ludovic MailleretUniversité Côte d'Azur, INRAE, CNRS, ISA, Sophia-Antipolis, France.
Frédéric M HamelinInstitut Agro, Univ Rennes, INRAE, IGEPP, Rennes, France.
Centre National de la Recherche Scientifique · FRInstitut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current agricultural practices facilitate emergence and spread of plant diseases through the wide use of monocultures. Host mixtures are a promising alternative for sustainable plant disease control. Their effectiveness can be partly explained by priming-induced cross-protection among plants. Priming occurs when plants are challenged with non-infective pathogen genotypes, resulting in increased resistance to subsequent infections by infective pathogen genotypes. We developed an epidemiological model to explore how mixing two distinct resistant varieties can reduce disease prevalence. We considered a pathogen population composed of three genotypes infecting either one or both varieties. We found that host mixtures should not contain an equal proportion of resistant plants, but a biased ratio (e.g. 80 : 20) to minimize disease prevalence. Counter-intuitively, the optimal ratio of resistant varieties should contain a lower proportion of the costliest resistance for the pathogen to break. This benefit is amplified by priming. This strategy also prevents the invasion of pathogens breaking all resistances.

Indexed as

Plant DiseasesPlantsDisease Resistance

Identifiers

PMID37228168
PMCPMC10246846
OpenAlexW4378195132

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.