Genomic selection is an integral tool for breeders to accurately select plants directly from
genotype data leading to faster and more resource-efficient breeding programs. Several …

Genomic prediction tools support crop breeding based on statistical methods, such as the
genomic best linear unbiased prediction (GBLUP). However, these tools are not designed to …

Abstract Background Several conventional genomic Bayesian (or no Bayesian) prediction
methods have been proposed including the standard additive genetic effect model for which …

Phenotyping is the current bottleneck in plant breeding, especially because next-generation
sequencing has decreased genotyping cost more than 100.000 fold in the last 20 years …

Main conclusion Deep learning is a promising technology to accurately select individuals
with high phenotypic values based on genotypic data. Abstract Genomic selection (GS) is a …

Highly efficient and accurate selection of elite genotypes can lead to dramatic shortening of
the breeding cycle in major crops relevant for sustaining present demands for food, feed …

Current practice in agriculture applies genomic prediction to assist crop breeding in the
analysis of genetic marker data. Genomic selection methods typically use linear mixed …

Genomic selection (GS) has the potential to revolutionize predictive plant breeding. A
reference population is phenotyped and genotyped to train a statistical model that is used to …

Background The accurate prediction of genomic breeding values is central to genomic
selection in both plant and animal breeding studies. Genomic prediction involves the use of …

In the two decades of continuous development of genomic selection, a great variety of
models have been proposed to make predictions from the information available in dense …