Optimizing Training Population Data and Validation of Genomic Selection for Economic Traits in Soft Winter Wheat

@article{Hoffstetter2016OptimizingTP,
  title={Optimizing Training Population Data and Validation of Genomic Selection for Economic Traits in Soft Winter Wheat},
  author={A. Hoffstetter and A. Cabrera and M. Huang and C. Sneller},
  journal={G3: Genes|Genomes|Genetics},
  year={2016},
  volume={6},
  pages={2919 - 2928}
}
  • A. Hoffstetter, A. Cabrera, +1 author C. Sneller
  • Published 2016
  • Biology, Medicine
  • G3: Genes|Genomes|Genetics
  • Genomic selection (GS) is a breeding tool that estimates breeding values (GEBVs) of individuals based solely on marker data by using a model built using phenotypic and marker data from a training population (TP). The effectiveness of GS increases as the correlation of GEBVs and phenotypes (accuracy) increases. Using phenotypic and genotypic data from a TP of 470 soft winter wheat lines, we assessed the accuracy of GS for grain yield, Fusarium Head Blight (FHB) resistance, softness equivalence… CONTINUE READING
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    References

    SHOWING 1-10 OF 38 REFERENCES
    Genomic Selection Accuracy for Grain Quality Traits in Biparental Wheat Populations
    • 187
    • Highly Influential
    • PDF
    Genomic Selection Accuracy using Multifamily Prediction Models in a Wheat Breeding Program
    • 269
    • Highly Influential
    Prediction of Genetic Values of Quantitative Traits in Plant Breeding Using Pedigree and Molecular Markers
    • 507
    • Highly Influential
    • PDF
    Genomic prediction in CIMMYT maize and wheat breeding programs
    • 225
    • Highly Influential
    • PDF
    Genomic selection for wheat traits and trait stability
    • 37
    Genomic Selection for Crop Improvement
    • 295
    • PDF
    Assessing Genomic Selection Prediction Accuracy in a Dynamic Barley Breeding Population
    • 100
    • Highly Influential
    • PDF
    Increased Genomic Prediction Accuracy in Wheat Breeding Through Spatial Adjustment of Field Trial Data
    • 67
    • Highly Influential
    • PDF