Evidence map›Paper›PMID 34919115›Full record

ArticleGenetics and molecular biology2021

Flowering process in soybean under water deficit conditions: A review on genetic aspects.

Mayla Daiane Correa Molinari, Renata Fuganti-Pagliarini, Daniel de Amorim Barbosa, Silvana Regina Rockenbach Marin, Daniel Rockenbach Marin, Elíbio Leopoldo Rech, Liliane Marcia Mertz-Henning, Alexandre Lima Nepomuceno

Abstract read
In one paragraph

Article in Genetics and molecular biology, 2021. 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. 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

8 authors.

Mayla Daiane Correa MolinariUniversidade Estadual de Londrina, Departamento de Biologia Geral, Londrina, PR, Brazil.ORCID http://orcid.org/0000-0002-9135-0422
Renata Fuganti-PagliariniEmbrapa Soja, Londrina, PR, Brazil.ORCID http://orcid.org/0000-0001-9282-2826
Daniel de Amorim BarbosaUniversidade Estadual de Londrina, Departamento de Biologia Geral, Londrina, PR, Brazil.
Silvana Regina Rockenbach MarinEmbrapa Soja, Londrina, PR, Brazil.
Daniel Rockenbach MarinEmbrapa Soja, Londrina, PR, Brazil.
Elíbio Leopoldo RechEmbrapa Recursos Genéticos e Biotecnologia, Instituto Nacional de Ciência e Tecnologia em Biologia Sintética, Brasília, DF, Brazil.
Liliane Marcia Mertz-HenningEmbrapa Soja, Londrina, PR, Brazil.
Alexandre Lima NepomucenoEmbrapa Soja, Londrina, PR, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Soybean is a key crop in many countries, being used from human food to the animal industry due to its nutritional properties. Financially, the grain chain moves large sums of money into the economy of producing countries. However, like other agricultural commodities around the world, it can have its final yield seriously compromised by abiotic environmental stressors, like drought. As flowers imply in pods and in grains inside it to minimize damages caused by water restriction, researchers have focused on understanding flowering-process related genes and their interactions. Here a review dedicated to the soybean flowering process and gene network involved in it is presented, describing gene interactions and how genes act in this complex mechanism, also ruled by environmental triggers such as day-light and circadian cycle. The objective was to gather information and insights on the soybean flowering process, aiming to provide knowledge useful to assist in the development of drought-tolerant soybean lines, minimizing losses due to delays or anticipation of flowering and, consequently, restraining financial and productivity losses.

Identifiers

PMID34919115
PMCPMC8679260

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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.