Evidence map›Paper›PMID 27415625›Full record

ArticlePloS one2016

Mapping Global Potential Risk of Mango Sudden Decline Disease Caused by Ceratocystis fimbriata.

Tarcísio Visintin da Silva Galdino, Sunil Kumar, Leonardo S S Oliveira, Acelino C Alfenas, Lisa G Neven, Abdullah M Al-Sadi, Marcelo C Picanço

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
6.5field-weighted citation impact, top 4% 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

8 citing papers in PubMed, 60 citations in OpenAlex.

  1. Article
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  3. A MaxEnt Model of Citrus Black FlyPlants (Basel, Switzerland) · 2024
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  4. Prediction of the Potential Distributions ofJournal of fungi (Basel, Switzerland) · 2023
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  5. Article
  6. The Progressive Spread of the Vascular Wilt Like Pathogen ofFrontiers in Forests and Global Change · 2020
    Article
  7. Article
  8. 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

7 authors at 4 institutions in 3 countries.

Tarcísio Visintin da Silva GaldinoDepartment of Plant Science, Universidade Federal de Viçosa, Viçosa, MG, Brazil.ORCID http://orcid.org/0000-0001-7317-0789
Sunil KumarNatural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO, United States of America.
Leonardo S S OliveiraDepartment of Plant Pathology, Universidade Federal de Viçosa, Viçosa, MG, Brazil.
Acelino C AlfenasDepartment of Plant Pathology, Universidade Federal de Viçosa, Viçosa, MG, Brazil.
Lisa G NevenUnited States Department of Agriculture-Agriculture Research Service, Yakima Agricultural Research Laboratory, Wapato, WA, United States of America.
Abdullah M Al-SadiDepartment of Crop Sciences, Sultan Qaboos University, AlKhoud, Oman.
Marcelo C PicançoDepartment of Entomology, Universidade Federal de Viçosa, Viçosa, MG, Brazil.
Universidade Federal de Viçosa · BRColorado State University · USSultan Qaboos University · OMUnited States Department of Agriculture · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Mango Sudden Decline (MSD), also referred to as Mango Wilt, is an important disease of mango in Brazil, Oman and Pakistan. This fungus is mainly disseminated by the mango bark beetle, Hypocryphalus mangiferae (Stebbing), by infected plant material, and the infested soils where it is able to survive for long periods. The best way to avoid losses due to MSD is to prevent its establishment in mango production areas. Our objectives in this study were to: (1) predict the global potential distribution of MSD, (2) identify the mango growing areas that are under potential risk of MSD establishment, and (3) identify climatic factors associated with MSD distribution. Occurrence records were collected from Brazil, Oman and Pakistan where the disease is currently known to occur in mango. We used the correlative maximum entropy based model (MaxEnt) algorithm to assess the global potential distribution of MSD. The MaxEnt model predicted suitable areas in countries where the disease does not already occur in mango, but where mango is grown. Among these areas are the largest mango producers in the world including India, China, Thailand, Indonesia, and Mexico. The mean annual temperature, precipitation of coldest quarter, precipitation seasonality, and precipitation of driest month variables contributed most to the potential distribution of MSD disease. The mango bark beetle vector is known to occur beyond the locations where MSD currently exists and where the model predicted suitable areas, thus showing a high likelihood for disease establishment in areas predicted by our model. Our study is the first to map the potential risk of MSD establishment on a global scale. This information can be used in designing strategies to prevent introduction and establishment of MSD disease, and in preparation of efficient pest risk assessments and monitoring programs.

Indexed as

AnimalsAscomycotaColeopteraMangiferaPlant DiseasesRainRisk FactorsSeasonsTemperature

Identifiers

PMID27415625
PMCPMC4944967
OpenAlexW2475194717

What OpenQuestion holds

Textmetadata
LicenceCC0
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.