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Calibration and validation of predicted genomic breeding values in an advanced cycle maize population
Calibration and validation of predicted genomic breeding values in an advanced cycle maize population

The transition from phenotypic to genome-based selection requires a profound understanding of factors that determine genomic prediction accuracy. We analysed experimental data from a commercial maize breeding programme to investigate if genomic measures can assist in identifying optimal calibration sets for model training. The data set consisted of six contiguous selection cycles comprising testcrosses of 5968 doubled haploid lines genotyped with a minimum of 12,000 SNP markers.

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