Article
Sparse kernel models provide optimization of training set design for genomic prediction in multiyear wheat breeding data.
The plant genome - 1 Dec 2022
Lopez-Cruz Marco, Dreisigacker Susanne, Crespo-Herrera Leonardo, Bentley Alison R, Singh Ravi, Poland Jesse, Shrestha Sandesh, Huerta-Espino Julio, Govindan Velu, Juliana Philomin, Mondal Suchismita, Pérez-Rodríguez Paulino, Crossa Jose
Abstract excerpt
The success of genomic selection (GS) in breeding schemes relies on its ability to provide accurate predictions of unobserved lines at early stages. Multigeneration data provides opportunities to increase the training data size and thus, the likelihood of extracting useful information from ancestors to improve prediction accuracy. The genomic best linear unbiased predictions (GBLUPs) are performed by borrowing...
Read the complete abstract on PubMedTopics
Share this publication in a Topic to start or enrich a Post.