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Sparse kernel models provide optimization of training set design for genomic prediction in multiyear wheat breeding data
(John Wiley & Sons Inc., 2022)
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
Genomic prediction models for count data
(Springer Verlag; American Statistical Association; International Biometrics Society, 2015)
Whole genome prediction models are useful tools for breeders when selecting candidate individuals early in life for rapid genetic gains. However, most prediction models developed so far assume that the response variable ...
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 ...
Article
Article
Deep kernel for genomic and near infrared predictions in multi-environment breeding trials
(Genetics Society of America, 2019)
Kernel methods are flexible and easy to interpret and have been successfully used in genomic-enabled prediction of various plant species. Kernel methods used in genomic prediction comprise the linear genomic best linear ...
Article
Joint use of genome, pedigree, and their interaction with environment for predicting the performance of wheat lines in new environments
(Genetics Society of America, 2019)
Genome-enabled prediction plays an essential role in wheat breeding because it has the potential to increase the rate of genetic gain relative to traditional phenotypic and pedigree-based selection. Since the performance ...