Increasing Genomic‐Enabled Prediction Accuracy by Modeling Genotype × Environment Interactions in Kansas Wheat-Reference-Cited by-同舟云学术

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Increasing Genomic‐Enabled Prediction Accuracy by Modeling Genotype × Environment Interactions in Kansas Wheat

Published:2017-07 Issue:2 Volume:10 Page:
ISSN:1940-3372
Container-title:The Plant Genome
language:en
Short-container-title:Plant Genome

Author:

Jarquín Diego¹,Lemes da Silva Cristiano²,Gaynor R. Chris³,Poland Jesse⁴,Fritz Allan²,Howard Reka⁵,Battenfield Sarah⁶,Crossa Jose⁷

Affiliation:

1. Dep. of Agronomy and HorticultureUniv. of NebraskaLincolnNE68583

2. Dep. of AgronomyKansas State Univ.ManhattanKS66506

3. The Roslin Institute and Royal School of Veterinary StudiesUniv. of EdinburghEaster BushMidlothianUK

4. Wheat Genetics Resource Center, Dep. of Plant PathologyKansas State Univ.ManhattanKS66506

5. Dep. of StatisticsUniv. of NebraskaLincolnNE

6. AgriPro WheatSyngentaJunction CityKS66441

7. Biometrics and Statistics Unit, CIMMYTEl BatanMexico

Publisher

Wiley

Subject

Plant Science,Agronomy and Crop Science,Genetics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.3835/plantgenome2016.12.0130

Reference29 articles.

1. Breeding schemes for the implementation of genomic selection in wheat ( Triticum spp . )

2. Battenfield S.D. Guzmán C. Gaynor R.C. Singh R.P. Peña R.J. andDreisigacker S.et al.2016.Genomic selection for processing and end‐use quality traits in the CIMMYT spring bread wheat breeding program.Plant Genome9. doi:10.3835/plantgenome2016.01.0005

3. TASSEL: software for association mapping of complex traits in diverse samples

4. Genomic Prediction of Breeding Values when Modeling Genotype × Environment Interaction using Pedigree and Dense Molecular Markers

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