Now showing items 1-10 of 21
A Bayesian decision theory approach for genomic selection
(Genetics Society of America, 2018)
Plant and animal breeders are interested in selecting the best individuals from a candidate set for the next breeding cycle. In this paper, we propose a formal method under the Bayesian decision theory framework to tackle ...
A singular value decomposition Bayesian multiple-trait and multiple-environment genomic model
(Springer; Nature Publishing Group; Genetics Society; Genetics Society of Great Britain, 2018)
Today, breeders perform genomic-assisted breeding to improve more than one trait. However, frequently there are several traits under study at one time, and the implementation of current genomic multiple-trait and ...
Increased prediction accuracy in wheat breeding trials using a marker x environment interaction Genomic Selection model
(Genetics Society of America, 2015)
ABSTRACT Genomic selection (GS) models use genome-wide genetic information to predict genetic values of candidates of selection. Originally, these models were developed without considering genotype · environment ...
Genomic bayesian prediction model for count data with genotype X environment interaction
(Genetics Society of America, 2016)
Genomic tools allow the study of the whole genome and are facilitating the study of genotype-environment combinations and their relationship with phenotype. However, most genomic prediction models developed so far are ...
Genomic prediction of genotype x environment interaction kernel regression models
(Crop Science Society of America, 2016)
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 or a nonlinear (Gaussian) kernel. In this ...
Genomic prediction with pedigree and genotype X environment interaction in spring wheat grown in South and West Asia, North Africa, and Mexico
(Genetics Society of America, 2017)
Developing genomic selection (GS) models is an important step in applying GS to accelerate the rate of genetic gain in grain yield in plant breeding. In this study, seven genomic prediction models under two cross-validation ...
An R package for multitrait and multienvironment data with the Item-based collaborative filtering algorithm
(Crop Science Society of America, 2018)
Genomic prediction models for grain yield of spring bread wheat in diverse agro-ecological zones
(Nature Publishing Group, 2016)
Genomic and pedigree predictions for grain yield and agronomic traits were carried out using high density molecular data on a set of 803 spring wheat lines that were evaluated in 5 sites characterized by several environmental ...