The effects of training population design on genomic prediction accuracy in wheat

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Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 1432-2242

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: The effects of training population design on genomic prediction accuracy in wheat ; day:19 ; month:3 ; year:2019 ; pages:1-10
Theoretical and applied genetics ; (19.3.2019), 1-10

Classification: Landwirtschaft, Veterinärmedizin

Creator: Edwards, Stefan McKinnon
Buntjer, Jaap B.
Jackson, Robert
Bentley, Alison R.
Lage, Jacob
Byrne, Ed
Burt, Chris
Jack, Peter
Berry, Simon
Flatman, Edward
Poupard, Bruno
Smith, Stephen
Hayes, Charlotte
Gaynor, R. Chris
Gorjanc, Gregor
Howell, Phil
Ober, Eric
Mackay, Ian J.
Hickey, John M.

Contributor: SpringerLink (Online service)

DOI: 10.1007/s00122-019-03327-y

URN: urn:nbn:de:101:1-2019041201144945983553

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 14.08.2025, 11:02 AM CEST

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Associated

Edwards, Stefan McKinnon
Buntjer, Jaap B.
Jackson, Robert
Bentley, Alison R.
Lage, Jacob
Byrne, Ed
Burt, Chris
Jack, Peter
Berry, Simon
Flatman, Edward
Poupard, Bruno
Smith, Stephen
Hayes, Charlotte
Gaynor, R. Chris
Gorjanc, Gregor
Howell, Phil
Ober, Eric
Mackay, Ian J.
Hickey, John M.
SpringerLink (Online service)

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The effects of training population design on genomic prediction accuracy in wheat

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Other Objects (12)

Increased genomic prediction accuracy in wheat breeding using a large Australian panel

Multi-trait genomic prediction using in-season physiological parameters increases prediction accuracy of complex traits in US wheat

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A deterministic equation to predict the accuracy of multi-population genomic prediction with multiple genomic relationship matrices

Fixed-length haplotypes can improve genomic prediction accuracy in an admixed dairy cattle population

Accuracy of genomic prediction using multiple Atlantic salmon populations

Haplotype-tagged SNPs improve genomic prediction accuracy for Fusarium head blight resistance and yield-related traits in wheat

A simple, cost-effective high-throughput image analysis pipeline improves genomic prediction accuracy for days to maturity in wheat

Factors influencing the accuracy of genomic prediction in plant breeding

psBLUP: incorporating marker proximity for improving genomic prediction accuracy

ShinyGPAS: interactive genomic prediction accuracy simulator based on deterministic formulas

Incorporating kernelized multi-omics data improves the accuracy of genomic prediction

Increased genomic prediction accuracy in wheat breeding using a large Australian panel

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A deterministic equation to predict the accuracy of multi-population genomic prediction with multiple genomic relationship matrices

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psBLUP: incorporating marker proximity for improving genomic prediction accuracy

ShinyGPAS: interactive genomic prediction accuracy simulator based on deterministic formulas

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Multi-trait genomic prediction using in-season physiological parameters increases prediction accuracy of complex traits in US wheat

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A deterministic equation to predict the accuracy of multi-population genomic prediction with multiple genomic relationship matrices

Fixed-length haplotypes can improve genomic prediction accuracy in an admixed dairy cattle population

Accuracy of genomic prediction using multiple Atlantic salmon populations

Haplotype-tagged SNPs improve genomic prediction accuracy for Fusarium head blight resistance and yield-related traits in wheat

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psBLUP: incorporating marker proximity for improving genomic prediction accuracy

ShinyGPAS: interactive genomic prediction accuracy simulator based on deterministic formulas

Incorporating kernelized multi-omics data improves the accuracy of genomic prediction

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