Leveraging Automated Machine Learning for Environmental Data‐Driven Genetic Analysis and Genomic Prediction in Maize Hybrids
Abstract Genotype, environment, and genotype‐by‐environment (G×E) 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 geno...
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| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-05-01
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| Series: | Advanced Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/advs.202412423 |
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