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Article
Sparse kernel models provide optimization of training set design for genomic prediction in multiyear wheat breeding data
(John Wiley & Sons Inc., 2022)
Article
Genetic gain from phenotypic and genomic selection for quantitative resistance to stem rust of wheat
(Crop Science Society of America, 2015)
Stem rust of wheat (Triticum aestivum L.) caused by Puccinia graminis f. sp. tritici Eriks. and E. Henn. is a globally important disease that can cause severe yield loss. Breeding for quantitative stem rust resistance ...
Article
Efficient use of historical data for genomic selection: a case study of stem rust resistance in wheat
(Crop Science Society of America, 2015)
Genomic selection (GS) is a methodology that can improve crop breeding efficiency. To implement GS, a training population (TP) with phenotypic and genotypic data is required to train a statistical model used to predict ...
Article
Genome-wide association mapping for resistance to leaf rust, stripe rust and tan spot in wheat reveals potential candidate genes
(Springer, 2018)
Leaf rust (LR), stripe rust (YR) and tan spot (TS) are some of the important foliar diseases in wheat (Triticum aestivum L.). To identify candidate resistance genes for these diseases in CIMMYT?s (International Maize and ...
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Multi-modal deep learning improves grain yield prediction in wheat breeding by fusing genomics and phenomics
(Oxford University Press, 2023)
Article
Bayesian multitrait kernel methods improve multienvironment genome-based prediction
(Oxford University Press, 2022)