Evidence map›Paper›PMID 29177798›Full record

ArticleInternational journal of biometeorology2018

Predicting the risk of cucurbit downy mildew in the eastern United States using an integrated aerobiological model.

K N Neufeld, A P Keinath, B K Gugino, M T McGrath, E J Sikora, S A Miller, M L Ivey, D B Langston, B Dutta, T Keever and 2 more

Abstract read
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In one paragraph

Article in International journal of biometeorology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.5field-weighted citation impact, top 9% 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, 15 citations in OpenAlex.

  1. Development of a NovelJournal of fungi (Basel, Switzerland) · 2026
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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

12 authors at 8 institutions in 1 country.

K N NeufeldCenter for Integrated Fungal Research, Department of Entomology and Plant Pathology, North Carolina State University, Raleigh, NC, 27695, USA.
A P KeinathDepartment of Plant and Environmental Sciences, Clemson University, Charleston, SC, 29414, USA.
B K GuginoDepartment of Plant Pathology and Environmental Microbiology, Pennsylvania State University, University Park, PA, 16802, USA.
M T McGrathPlant Pathology and Plant-Microbe Biology Section, School of Integrative Plant Science, Cornell University, Riverhead, NY, 11901, USA.
E J SikoraDepartment of Entomology and Plant Pathology, Auburn University, Auburn, AL, 36849, USA.
S A MillerDepartment of Plant Pathology, Ohio State University, Wooster, OH, 43210, USA.
M L IveyDepartment of Plant Pathology, Ohio State University, Wooster, OH, 43210, USA.
D B LangstonTidewater Agricultural Research and Extension Center, Department of Plant Pathology, Physiology and Weed Science, Virginia Polytechnic Institute and State University, Suffolk, VA, 23437, USA.
B DuttaDepartment of Plant Pathology, University of Georgia, Tifton, GA, 31793, USA.
T KeeverCenter for Integrated Fungal Research, Department of Entomology and Plant Pathology, North Carolina State University, Raleigh, NC, 27695, USA.
A SimsState Climate Office of North Carolina, North Carolina State University, Raleigh, NC, 27695, USA.
P S OjiamboCenter for Integrated Fungal Research, Department of Entomology and Plant Pathology, North Carolina State University, Raleigh, NC, 27695, USA. pojiamb@ncsu.edu.ORCID http://orcid.org/0000-0002-0984-2760
North Carolina State University · USCollege of Wooster · USAuburn University · USClemson University · USCornell University · USPennsylvania State University · USUniversity of Georgia · USVirginia Tech · US

Funding

USDA-NIFA 2012-34103-19622USDA-NIFA 2012-41530-19623USDA-NIFA 2012-51300-20006
6 · The paper itself

Abstract

Cucurbit downy mildew caused by the obligate oomycete, Pseudoperonospora cubensis, is considered one of the most economically important diseases of cucurbits worldwide. In the continental United States, the pathogen overwinters in southern Florida and along the coast of the Gulf of Mexico. Outbreaks of the disease in northern states occur annually via long-distance aerial transport of sporangia from infected source fields. An integrated aerobiological modeling system has been developed to predict the risk of disease occurrence and to facilitate timely use of fungicides for disease management. The forecasting system, which combines information on known inoculum sources, long-distance atmospheric spore transport and spore deposition modules, was tested to determine its accuracy in predicting risk of disease outbreak. Rainwater samples at disease monitoring sites in Alabama, Georgia, Louisiana, New York, North Carolina, Ohio, Pennsylvania and South Carolina were collected weekly from planting to the first appearance of symptoms at the field sites during the 2013, 2014, and 2015 growing seasons. A conventional PCR assay with primers specific to P. cubensis was used to detect the presence of sporangia in rain water samples. Disease forecasts were monitored and recorded for each site after each rain event until initial disease symptoms appeared. The pathogen was detected in 38 of the 187 rainwater samples collected during the study period. The forecasting system correctly predicted the risk of disease outbreak based on the presence of sporangia or appearance of initial disease symptoms with an overall accuracy rate of 66 and 75%, respectively. In addition, the probability that the forecasting system correctly classified the presence or absence of disease was ≥ 73%. The true skill statistic calculated based on the appearance of disease symptoms in cucurbit field plantings ranged from 0.42 to 0.58, indicating that the disease forecasting system had an acceptable to good performance in predicting the risk of cucurbit downy mildew outbreak in the eastern United States.

Indexed as

Models, TheoreticalMycosesOomycetesPlant DiseasesCucurbitaceaeForecastingRainRiskUnited StatesAerobiological modeling systemCucurbit downy mildewRisk predictionROC analysisSpore depositionTrue skill statistic

Identifiers

PMID29177798
OpenAlexW2769983375

What OpenQuestion holds

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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.