Integration of machine learning and genome‐wide association study to explore the genomic prediction accuracy of agronomic trait in oats (Avena sativa L.)
Abstract Machine learning (ML) has garnered significant attention for its potential to enhance the accuracy of genomic predictions (GPs) in various economic crops with the use of complete genomic information. Genome‐wide association studies (GWAS) are widely used to pinpoint trait‐related causal var...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-03-01
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| Series: | The Plant Genome |
| Online Access: | https://doi.org/10.1002/tpg2.20549 |
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