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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)
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Multi-modal deep learning improves grain yield prediction in wheat breeding by fusing genomics and phenomics
(Oxford University Press, 2023)
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Bayesian multitrait kernel methods improve multienvironment genome-based prediction
(Oxford University Press, 2022)
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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 ...