Evidence map›Paper›PMID 35003202›Full record

ArticleFrontiers in genetics2021

Harnessing Genetic Diversity in the USDA Pea Germplasm Collection Through Genomic Prediction.

Md Abdullah Al Bari, Ping Zheng, Indalecio Viera, Hannah Worral, Stephen Szwiec, Yu Ma, Dorrie Main, Clarice J Coyne, Rebecca J McGee, Nonoy Bandillo

Abstract read
In one paragraph

Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

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  6. Harnessing historical genebank data to accelerate pea breeding.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
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  15. Genetic Diversity and Population Structure of a WideInternational journal of molecular sciences · 2023
    Article
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  20. 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

10 authors.

Md Abdullah Al BariDepartment of Plant Sciences, North Dakota State University, Fargo, ND, United States.
Ping ZhengDepartment of Horticulture, Washington State University, Pullman, WA, United States.
Indalecio VieraDepartment of Plant Sciences, North Dakota State University, Fargo, ND, United States.
Hannah WorralNDSU North Central Research Extension Center, Minot, ND, United States.
Stephen SzwiecNDSU North Central Research Extension Center, Minot, ND, United States.
Yu MaDepartment of Horticulture, Washington State University, Pullman, WA, United States.
Dorrie MainDepartment of Horticulture, Washington State University, Pullman, WA, United States.
Clarice J CoyneUSDA-ARS Plant Germplasm Introduction and Testing, Washington State University, Pullman, WA, United States.
Rebecca J McGeeUSDA-ARS Grain Legume Genetics and Physiology Research, Pullman, WA, United States.
Nonoy BandilloDepartment of Plant Sciences, North Dakota State University, Fargo, ND, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Phenotypic evaluation and efficient utilization of germplasm collections can be time-intensive, laborious, and expensive. However, with the plummeting costs of next-generation sequencing and the addition of genomic selection to the plant breeder's toolbox, we now can more efficiently tap the genetic diversity within large germplasm collections. In this study, we applied and evaluated genomic prediction's potential to a set of 482 pea (

Indexed as

genomic predictiongenomic selectiongermplasm accessionsnext-generation sequencingpea (Pisum sativum L)reliability criteria

Identifiers

PMID35003202
PMCPMC8740293

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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.