Leveraging automated machine learning for environmental data-driven genetic analysis and genomic prediction in maize hybrids
Genotype, environment, and genotype-by-environment (GxE) interactions play a critical role in shaping crop phenotypes. Here, a large-scale, multi-environment hybrid maize dataset is used to construct and validate an automated machine learning framework that integrates environmental and genomic data...
| Autores principales: | , , , , , , , , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Wiley-VCH Verlag
2025
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/179136 |
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