Genome-based prediction of maize hybrid performance across genetic groups, testers, locations, and years

@article{Albrecht2014GenomebasedPO,
  title={Genome-based prediction of maize hybrid performance across genetic groups, testers, locations, and years},
  author={Theresa Albrecht and Hans-J{\"u}rgen Auinger and Valentin Wimmer and Joseph Ochieng Ogutu and Carsten Knaak and Milena Ouzunova and Hans-Peter Piepho and Chris-Carolin Sch{\"o}n},
  journal={Theoretical and Applied Genetics},
  year={2014},
  volume={127},
  pages={1375-1386}
}
The calibration data for genomic prediction should represent the full genetic spectrum of a breeding program. Data heterogeneity is minimized by connecting data sources through highly related test units. One of the major challenges of genome-enabled prediction in plant breeding lies in the optimum design of the population employed in model training. With highly interconnected breeding cycles staggered in time the choice of data for model training is not straightforward. We used cross-validation… CONTINUE READING
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