Evidence map›Paper›PMID 32248658›Full record

ReviewPest management science2020

Identifying drivers of spatio-temporal dynamics in barley yellow dwarf virus epidemiology as a critical factor in disease control.

Renik Van den Eynde, Thomas Van Leeuwen, Geert Haesaert

Open access · hybridAbstract readReview
In one paragraph

Review in Pest management science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.8field-weighted citation impact, top 10% 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

6 citing papers in PubMed, 32 citations in OpenAlex.

  1. Article
  2. Fine mapping a QTL for BYDV-PAV resistance in maize.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024
    Article
  3. Article
  4. Article
  5. Article
  6. 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

3 authors at 1 institution in 1 country.

Renik Van den EyndeDepartment of Plants and Crops, Faculty of Bioscience Engineering, Ghent University, Bottelare, Belgium.ORCID https://orcid.org/0000-0003-2650-2888
Thomas Van LeeuwenDepartment of Plants and Crops, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.ORCID https://orcid.org/0000-0003-4651-830X
Geert HaesaertDepartment of Plants and Crops, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
Ghent University · BE

Funding

Agentschap Innoveren en Ondernemen
6 · The paper itself

Abstract

Barley yellow dwarf virus (BYDV) is one of the most important viral diseases of small grains worldwide. An understanding of its epidemiology is crucial to control this disease in a sustainable way. The virus moves through the agricultural landscape via cereal aphids as vectors. Understanding movement of these aphids in space and time is of key importance and in doing so, the spatial and temporal variables that influence BYDV epidemiology can be identified. The presence of summer hosts, crop rotation, crop diversity, agricultural practices and climate variables are crucial. Through digitalization, spatial (e.g. land-use) and temporal (e.g. weather) information is becoming more readily available. Including this information into a prediction model could improve decision support systems that will rationalize the decision-making process towards a more integrated control of the disease. © 2020 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Indexed as

LuteovirusAnimalsAphidsClimateHordeumPlant DiseasesBYDVcereal aphidsdecision support systemsepidemiologyIPMspatio-temporal influences

Identifiers

PMID32248658
PMCPMC7383682
OpenAlexW3014925810

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.