Since the inception of the theory and conceptual framework of genomic selection (GS),
extensive research has been done on evaluating its efficiency for utilization in crop …

With marker and phenotype information from observed populations, genomic selection (GS)
can be used to establish associations between markers and phenotypes. It aims to use …

Genomic prediction is an effective way to accelerate the rate of agronomic trait improvement
in plants. Traditional methods typically use linear regression models with clear assumptions; …

Warming and drought are reducing global crop production with a potential to substantially
worsen global malnutrition. As with the green revolution in the last century, plant genetics …

Abstract “Genomic selection,” the ability to select for even complex, quantitative traits based
on marker data alone, has arisen from the conjunction of new high-throughput marker …

In the mid‐1980s, the development of abundant molecular markers, appropriate statistical
procedures, and user‐friendly computer software that implemented these statistical …

Genomic selection (GS) is transforming the field of plant breeding and implementing models
that improve prediction accuracy for complex traits is needed. Analytical methods for …

Rice (Oryza sativa) provides a staple food source for more than half the world population.
However, the current pace of rice breeding in yield growth is insufficient to meet the food …

Parametric and nonparametric methods have been developed for purposes of predicting
phenotypes. These methods are based on retrospective analyses of empirical data …

New methods and algorithms are being developed for predicting untested phenotypes in
schemes commonly used in genomic selection (GS). The prediction of disease resistance in …