Buscar
Mostrando ítems 1-10 de 21
Presentation
Article
Genomic-enabled prediction with classification algorithms
(Springer Nature, 2014)
Pearson’s correlation coefficient (ρ) is the most commonly reported metric of the success of prediction in genomic selection (GS). However, in real breeding ρ may not be very useful for assessing the quality of the regression ...
Article
Article
Single-step genomic and pedigree genotype x environment interaction models for predicting wheat lines in international environments
(Crop Science Society of America, 2017)
Genomic prediction models have been commonly used in plant breeding but only in reduced datasets comprising a few hundred genotyped individuals. However, pedigree information for an entire breeding population is frequently ...
Article
Prospects and challenges of applied genomic selection-a new paradigm in breeding for grain yield in bread wheat
(Crop Science Society of America, 2018)
Genomic selection (GS) has been promising for increasing genetic gains in several species. Therefore, we evaluated the potential integration of GS for grain yield (GY) in bread wheat (Triticum aestivum L.) in CIMMYT's elite ...
Article
Hybrid wheat prediction using genomic, pedigree, and environmental covariables interaction models
(Crop Science Society of America, 2019)
In this study, we used genotype × environment interactions (G×E) models for hybrid prediction, where similarity between lines was assessed by pedigree and molecular markers, and similarity between environments was accounted ...
Article
Applications of machine learning methods to genomic selection in breeding wheat for rust resistance
(Crop Science Society of America, 2018)
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 GS has its own peculiarities: a) there is consensus ...
Article
Genomic prediction of genetic values for resistance to wheat rusts
(Crop Science Society of America, 2012)
Durable resistance to the rust diseases of wheat (Triticum aestivum L.) can be achieved by developing lines that have race-nonspecific adult plant resistance conferred by multiple minor slow-rusting genes. Genomic selection ...
Article
Comparison between linear and non-parametric regression models for genome-enabled prediction in wheat
(Genetics Society of America, 2012)
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 models using dense molecular markers. The ...
Article
Integrating genomic-enabled prediction and high-throughput phenotyping in breeding for climate-resilient bread wheat
(Springer, 2019)
Genomic selection and high-throughput phenotyping (HTP) are promising tools to accelerate breeding gains for high-yielding and climate-resilient wheat varieties. Hence, our objective was to evaluate them for predicting ...