Applications of machine learning methods to genomic selection in breeding wheat for rust resistance
JM González‐Camacho, L Ornella… - The plant …, 2018 - Wiley Online Library
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 …
schemes commonly used in genomic selection (GS). The prediction of disease resistance in …
[HTML][HTML] Integrated genomic selection for rapid improvement of crops
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 …
production and other needs of ever-increasing population. Genomic selection (GS) is a …
Nonlinear kernels, dominance, and envirotyping data increase the accuracy of genome-based prediction in multi-environment trials
Modern whole-genome prediction (WGP) frameworks that focus on multi-environment trials
(MET) integrate large-scale genomics, phenomics, and envirotyping data. However, the …
(MET) integrate large-scale genomics, phenomics, and envirotyping data. However, the …
[HTML][HTML] Kernel-based whole-genome prediction of complex traits: a review
Prediction of genetic values has been a focus of applied quantitative genetics since the
beginning of the 20th century, with renewed interest following the advent of the era of whole …
beginning of the 20th century, with renewed interest following the advent of the era of whole …
Genomic selection in cereal breeding
CD Robertsen, RL Hjortshøj, LL Janss - Agronomy, 2019 - mdpi.com
Genomic Selection (GS) is a method in plant breeding to predict the genetic value of
untested lines based on genome-wide marker data. The method has been widely explored …
untested lines based on genome-wide marker data. The method has been widely explored …
Bayesian genomic prediction with genotype× environment interaction kernel models
The phenomenon of genotype× environment (G× E) interaction in plant breeding decreases
selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction …
selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction …
Genomic prediction of genotype× environment interaction kernel regression models
In genomic selection (GS), genotype× environment interaction (G× E) can be modeled by a
marker× environment interaction (M× E). The G× E may be modeled through a linear kernel …
marker× environment interaction (M× E). The G× E may be modeled through a linear kernel …
Genomic selection in crops, trees and forages: a review
Genomic selection is now being used at an accelerating pace in many plant species. This
review first discusses the factors affecting the accuracy of genomic selection, and then …
review first discusses the factors affecting the accuracy of genomic selection, and then …
[HTML][HTML] Incorporating genome-wide association mapping results into genomic prediction models for grain yield and yield stability in CIMMYT spring bread wheat
Untangling the genetic architecture of grain yield (GY) and yield stability is an important
determining factor to optimize genomics-assisted selection strategies in wheat. We …
determining factor to optimize genomics-assisted selection strategies in wheat. We …
A genomic Bayesian multi-trait and multi-environment model
OA Montesinos-López… - G3: Genes …, 2016 - academic.oup.com
When information on multiple genotypes evaluated in multiple environments is recorded, a
multi-environment single trait model for assessing genotype× environment interaction (G× E) …
multi-environment single trait model for assessing genotype× environment interaction (G× E) …