Selection for wheat (Triticum aestivum L.) grain quality is often costly and time-consuming
since it requires extensive phenotyping in the last phases of development of new lines and …

Genotyping has become cost-and time-effective with the advent of next-generation
sequencing technologies, thus making genomic selection (GS) a feasible selection tool in …

The prediction accuracies of genomic selection depend on several factors, including the
genetic architecture of target traits, the number of traits considered at a given time, and the …

In order to meet the goal of doubling wheat yield by 2050, breeders must work to improve
breeding program efficiency while also implementing new and improved technologies in …

Key message The implementation of genomic selection in breeding programs can be
recommended for hybrid and line breeding in wheat. Abstract High prediction accuracies …

Genomic selection (GS) uses genomewide molecular markers to predict breeding values
and make selections of individuals or breeding lines prior to phenotyping. Here we show …

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 (GS) models have been validated for many quantitative traits in wheat
(Triticum aestivum L.) breeding. However, those models are mostly constrained within the …

Genomic selection applied to plant breeding enables earlier estimates of a line's
performance and significant reductions in generation interval. Several factors affecting …

Wheat quality improvement is an important objective in all wheat breeding programs.
However, due to the cost, time and quantity of seed required, wheat quality is typically …