New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes

New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes

The seven data sets are wheat data from CIMMYT Global Wheat Breeding program. They comprise different traits, like days to heading, days to maturity, grain yield, grain color, different type of leaf and stripe rust in wheat. Also the trials were run in different environments.

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Bibliographic Details
Main Authors: Montesinos-López, Osval A., Martín-Vallejo, Javier, Crossa, Jose, Gianola, Daniel, Hernández-Suarez, Carlos Moisés, Montesinos-López, Abelardo, Juliana, Philomin, Singh, Ravi
Other Authors: Shrestha, Rosemary
Format: Experimental data biblioteca
Language:English
Published: CIMMYT Research Data & Software Repository Network 2018
Subjects:Agricultural Sciences, Agricultural research, Wheat, Days to heading, Days to maturity, Grain yield, Grain color, Genomic selection, Deep learning, Plant breeding, Multi-trait, Mixed phenotypes,
Online Access:https://hdl.handle.net/11529/10548140
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https://hdl.handle.net/11529/10548140

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