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Using machine learning to integrate genetic and environmental data to model genotype-by-environment interactions - MaRDI portal

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Using machine learning to integrate genetic and environmental data to model genotype-by-environment interactions

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DOI10.5281/zenodo.12702650Zenodo12702650MaRDI QIDQ6682684

Dataset published at Zenodo repository.

Author name not available (Why is that?)

Publication date: 9 July 2024

Copyright license: No records found.



Description

Files generated from the study described inFernandes et. al (2024) . The file "cvs_h2s.csv" comprises the coefficient of variation and the Cullis heritability for each environment. The file "all_predictions.csv" contains the predictions from all the models evaluated, in different cross-validation (CV) scenarios. The file "coincidence_index.csv" has the Coincidence Index (CI) for each CV and models evaluated in our study. Our study used the multi-environment maize yield trials data from the Genomes to Fields 2022 initiative (Lima et. al 2024).






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