Evidence map›Paper›PMID 32436136›Full record

ArticleInternational journal of biometeorology2020

BotRisk: simulating the annual bunch rot risk on grapevines (Vitis vinifera L. cv. Riesling) based on meteorological data.

Daniel Molitor, Ottmar Baus, Yoanne Didry, Jürgen Junk, Lucien Hoffmann, Marco Beyer

Abstract read
PubMed Publisher
In one paragraph

Article in International journal of biometeorology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 19% 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

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. 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 at 2 institutions in 2 countries.

Daniel MolitorEnvironmental Research and Innovation (ERIN) Department, LIST - Luxembourg Institute of Science and Technology, 41, rue du Brill, L-4422, Belvaux, Luxembourg. daniel.molitor@list.lu.ORCID https://orcid.org/0000-0001-7487-6740
Ottmar BausHochschule Geisenheim University, Institute of Phytomedicine, Von-Lade-Str. 1, D-65366, Geisenheim, Germany.
Yoanne DidryEnvironmental Research and Innovation (ERIN) Department, LIST - Luxembourg Institute of Science and Technology, 41, rue du Brill, L-4422, Belvaux, Luxembourg.
Jürgen JunkEnvironmental Research and Innovation (ERIN) Department, LIST - Luxembourg Institute of Science and Technology, 41, rue du Brill, L-4422, Belvaux, Luxembourg.
Lucien HoffmannEnvironmental Research and Innovation (ERIN) Department, LIST - Luxembourg Institute of Science and Technology, 41, rue du Brill, L-4422, Belvaux, Luxembourg.
Marco BeyerEnvironmental Research and Innovation (ERIN) Department, LIST - Luxembourg Institute of Science and Technology, 41, rue du Brill, L-4422, Belvaux, Luxembourg.
Luxembourg Institute of Science and Technology · LUHochschule Geisenheim University · DE

Funding

Horizon 2020 Framework Programme 810176
6 · The paper itself

Abstract

The aim of the present investigations was to simulate the annual risk of bunch rot (Botrytis cinerea) on Vitis vinifera L. cv. Riesling grapes based on three long-term (n = 3 × 7 = 21 cases) assessment data sets originating from three Central European grape-growing regions. Periods when meteorological parameters were significantly (p < 0.01) correlated with the cumulative degree day (CDD

Indexed as

MeteorologyVitisBotrytisPlant DiseasesWeatherBotrytis cinereaBunch rot riskClimate changeCumulative degree daysDecision support toolEpidemiologyWindow Pane analysis

Identifiers

PMID32436136
OpenAlexW3026558935

What OpenQuestion holds

Textmetadata
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.