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Article
Extending the marker x environment interaction model for genomic-enabled prediction and genome-wide association analysis in durum wheat
(Crop Science Society of America (CSSA), 2016)
The marker ´ environment interaction (M´E) genomic model can be used to generate predictions for untested individuals and identify genomic regions in which effects are stable across environments and others that show ...
Article
Genomic and pedigree-based prediction for leaf, stem, and stripe rust resistance in wheat
(Springer, 2017)
The unceasing plant-pathogen arms race and ephemeral nature of some rust resistance genes have been challenging for wheat (Triticum aestivum L.) breeding programs and farmers. Hence, it is important to devise strategies ...
Article
Genomic prediction of breeding values when modeling genotype × environment interaction using pedigree and dense molecular markers
(Crop Science Society of America (CSSA), 2012)
Genomic selection (GS) has become an important aid in plant and animal breeding. Multienvironment (multitrait) models allow borrowing of information across environments (traits), which could enhance prediction accuracy. ...
Article
Canopy temperature and vegetation indices from high-throughput phenotyping improve accuracy of pedigree and genomic selection for grain yield in wheat
(Genetics Society of America, 2016)
Genomic selection can be applied prior to phenotyping, enabling shorter breeding cycles and greater rates of genetic gain relative to phenotypic selection. Traits measured using high-throughput phenotyping based on proximal ...
Article
Wheat quality improvement at CIMMYT and the use of genomic selection on it
(Elsevier, 2016)
The International Center for Maize and Wheat Improvement (CIMMYT) leads the Global Wheat Program, whose main objective is to increase the productivity of wheat cropping systems to reduce poverty in developing countries. ...
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
Comparison of models and whole-genome profiling approaches for genomic-enabled prediction of Septoria Tritici Blotch, Stagonospora Nodorum Blotch, and tan spot resistance in wheat
(Crop Science Society of America, 2017)
The leaf spotting diseases in wheat that include Septoria tritici blotch (STB) caused by Zymoseptoria tritici, Stagonospora nodorum blotch (SNB) caused by Parastagonospora nodorum, and tan spot (TS) caused by Pyrenophora ...
Article
Partial least squares enhances genomic prediction of new environments
(Frontiers, 2022)
Article
Application of multi-trait Bayesian decision theory for parental genomic selection
(Genetics Society of America, 2021)