Evidence map›Paper›PMID 41829809›Full record

ArticlePlants (Basel, Switzerland)2026

Trait Association for Flowering Time in Lentil from Global Multi-Environment Data Using GWAS and Machine Learning.

Shriprabha R Upadhyaya, Hawlader A Al-Mamun, Monica F Danilevicz, Shameela Mohamedikbal, Mohammed Bennamoun, Jacqueline Batley, Kirstin E Bett, David Edwards

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Plants (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Shriprabha R UpadhyayaCentre for Applied Bioinformatics, The University of Western Australia, Perth, WA 6009, Australia.ORCID 0000-0001-9511-9562
Hawlader A Al-MamunCentre for Applied Bioinformatics, The University of Western Australia, Perth, WA 6009, Australia.ORCID 0000-0003-2453-0914
Monica F DanileviczAustralian Herbicide Resistance Initiative, School of Agriculture and Environment, The University of Western Australia, Perth, WA 6009, Australia.ORCID 0000-0001-7599-8184
Shameela MohamedikbalCentre for Applied Bioinformatics, The University of Western Australia, Perth, WA 6009, Australia.
Mohammed BennamounSchool of Physics, Mathematics and Computing, The University of Western Australia, Perth, WA 6009, Australia.ORCID 0000-0002-6603-3257
Jacqueline BatleySchool of Biological Science, The University of Western Australia, Perth, WA 6009, Australia.ORCID 0000-0002-5391-5824
Kirstin E BettDepartment of Plant Sciences, University of Saskatchewan, Saskatoon, SK S7N 5A8, Canada.ORCID 0000-0001-7959-6959
David EdwardsCentre for Applied Bioinformatics, The University of Western Australia, Perth, WA 6009, Australia.ORCID 0000-0001-7599-6760

Funding

Australian Research Council DP200100762Australian Research Council DP210100296Australian Research Council LP230100351Genome Canada Application of Genomics to Innovation in the Lentil Economy (AGILE)
6 · The paper itself

Abstract

Flowering time is an important developmental stage in plants, influenced by multiple genes and environmental factors. Understanding its genetic basis and interaction with the environment facilitates the development of improved varieties adapted to different environments. Conventional Genome-Wide Association Studies (GWAS) have been widely used to associate genetic markers with heritable traits, but they do not inherently capture interactions among single nucleotide polymorphisms (SNPs) or between SNPs and the environment. Machine Learning (ML) approaches can model these interactions and improve trait prediction even in the presence of noise and missing data. In this study, multi-environment lentil (

Indexed as

epistasisSHAPsingle nucleotide polymorphisms (SNPs)XAI

Identifiers

PMID41829809
PMCPMC12987266

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.