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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 ...
Book Chapter
Chapter 3. Defining target wheat breeding environments
(Springer Nature, 2022)
Article
Article
Article
Sparse kernel models provide optimization of training set design for genomic prediction in multiyear wheat breeding data
(John Wiley & Sons Inc., 2022)
Book Chapter
Chapter 32. Theory and practice of phenotypic and genomic selection indices
(Springer Nature, 2022)
Article
Article
Deep learning methods improve genomic prediction of wheat breeding
(Frontiers Media S.A., 2024)
Article
Genetic gains for grain yield in CIMMYT’s semi-arid wheat yield trials grown in suboptimal environments
(Crop Science Society of America (CSSA), 2018)
Wheat (Triticum aestivum L.) is a major staple food crop grown worldwide on >220 million ha. Climate change is regarded to have severe effect on wheat yields, and unpredictable drought stress is one of the most important ...