Evidence map›Paper›PMID 36851675›Full record

ArticleViruses2023

Influence of Climatic Variables on Incidence of Whitefly-Transmitted Begomovirus in Soybean and Bean Crops in North-Western Argentina.

Pablo Reyna, Franco Suarez, Mónica Balzarini, Patricia Rodriguez Pardina

Abstract read
In one paragraph

Article in Viruses, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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

4 authors.

Pablo ReynaUnidad Ejecutora UFYMA-INTA-CONICET, Córdoba X5020ICA, Argentina.
Franco SuarezUnidad Ejecutora UFYMA-INTA-CONICET, Córdoba X5020ICA, Argentina.ORCID 0000-0003-3179-2701
Mónica BalzariniUnidad Ejecutora UFYMA-INTA-CONICET, Córdoba X5020ICA, Argentina.
Patricia Rodriguez PardinaUnidad Ejecutora UFYMA-INTA-CONICET, Córdoba X5020ICA, Argentina.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the last 20 years, begomoviruses have emerged as devastating pathogens, limiting the production of different crops worldwide. Weather conditions increase vector populations, with negative effects on crop production. In this work we evaluate the relationship between the incidence of begomovirus and weather before and during the crop cycle. Soybean and bean fields from north-western (NW) Argentina were monitored between 2001 and 2018 and classified as moderate (≤50%) or severe (>50%) according to the begomovirus incidence. Bean golden mosaic virus (BGMV) and soybean blistering mosaic virus (SbBMV) were the predominant begomovirus in bean and soybean crops, respectively. Nearly 200 bio-meteorological variables were constructed by summarizing climatic variables in 10-day periods from July to November of each crop year. The studied variables included temperature, precipitation, relative humidity, wind (speed and direction), pressure, cloudiness, and visibility. For bean, high maximum winter temperatures, low spring humidity, and precipitation 10 days before planting correlated with severe incidence. In soybeans, high temperatures in late winter and in the pre-sowing period, and low spring precipitations were found to be good predictors of high incidence of begomovirus. The results suggest that temperature and pre-sowing precipitations can be used to predict the incidence status [predictive accuracy: 80% (bean) and 75% (soybean)]. Thus, these variables can be incorporated in early warning systems for crop management decision-making to reduce the virus impact on bean and soybean crops.

Indexed as

BegomovirusGlycine maxArgentinaCrops, AgriculturalIncidenceWeatherpathosystempredictive modelviral diseasesweather

Identifiers

PMID36851675
PMCPMC9963925

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Registered trials

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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.