Arne De Coninck

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Genomic prediction for plant breeding requires taking into account environmental effects and variations of genetic effects across environments. The latter can be modelled by estimating the effect of each genetic marker in every possible environmental condition, which leads to a huge amount of effects to be estimated. Nonetheless, the information about these(More)
In genomic prediction, common analysis methods rely on a linear mixed-model framework to estimate SNP marker effects and breeding values of animals or plants. Ridge regression–best linear unbiased prediction (RR-BLUP) is based on the assumptions that SNP marker effects are normally distributed, are uncorrelated, and have equal variances. We propose(More)
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