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Genomic-enabled prediction Kernel models with random intercepts for multi-environment trials 

Cuevas, J.; Granato, I.; Fritsche-Neto, R.; Montesinos-Lopez, O.A.; Burgueño, J.; Bandeira e Sousa, M.; Crossa, J. (Genetics Society of America, 2018)
In this study, we compared the prediction accuracy of the main genotypic effect model (MM) without G×E interactions, the multi-environment single variance G×E deviation model (MDs), and the multienvironment environment-specific ...
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Genomic prediction enhanced sparse testing for multi-environment trials 

Jarquín, D.; Howard, R.; Crossa, J.; Beyene, Y.; Gowda, M.; Martini, J.W.R.; Covarrubias-Pazaran, G.; Burgueño, J.; Pacheco Gil, R. A.; Grondona, M.; Wimmer, V.; Prasanna, B.M. (Genetics Society of America, 2020)

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Author
Burgueño, J. (2)Crossa, J. (2)Beyene, Y. (1)Covarrubias, E. (1)Cuevas, J. (1)E Sousa, M. (1)Fritsche-Neto, R. (1)Gowda, Manje (1)Granato, I. (1)Grondona, M. (1)... View More
Date Issued
2020 (1)2018 (1)
Type
Article (2)
Agrovoc
GENOMICS (2)GENOTYPE ENVIRONMENT INTERACTION (2)MAIZE (1)... View More
Keywords
Genomic Enabled Prediction Accuracy (2)
GenPred (2)
Shared Data Resources (2)Allocation of Nonoverlapping (1)Deviations from Main Genetic Effects (1)Genomic Selection (1)Main Genetic Effects (1)Multienvironment Trials (1)Random Crossvalidations (1)Random Intercepts (1)... View More


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