Genomic selection (GS) is a method to estimate the breeding values of individuals by using
markers throughout the genome. We evaluated the accuracies of GS using data from five …

In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression
models have been used. This study assessed the predictive ability of linear and non-linear …

Starting with a base yield of 3 t/ha under drought, conventional breeding for regional
adaptation should reliably deliver 50 kg/ha/yr (~ 1.4%/yr). MAS, which has performed well in …

Intense structuring of plant breeding populations challenges the design of the training set
(TS) in genomic selection (GS). An important open question is how the TS should be …

Fusarium head blight (FHB) is a major fungal disease affecting wheat production worldwide.
Since the early 1990s, FHB, caused primarily by Fusarium graminearum, has become one of …

An increase in the rate of crop improvement is essential for achieving sustained food
production and other needs of ever-increasing population. Genomic selection (GS) is a …

Although genome-wide association studies have identified markers that are associated with
various human traits and diseases, our ability to predict such phenotypes remains limited. A …

The availability of high density panels of molecular markers has prompted the adoption of
genomic selection (GS) methods in animal and plant breeding. In GS, parametric, semi …

Key message Genomic selection models can be trained using historical data and filtering
genotypes based on phenotyping intensity and reliability criterion are able to increase the …

Genomic selection offers great potential for increasing the rate of genetic improvement in
plant breeding programs. This research used simulation to evaluate the effectiveness of …