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Increased prediction accuracy in wheat breeding trials using a marker x environment interaction Genomic Selection model 

Lopez-Cruz, M.; Poland, J.; Jannink, J.L.; De los Campos, G.; Crossa, J.; Singh, R.P.; Dreisigacker, S.; Bonnett, D.; Autrique, E. (Genetics Society of America, 2015)
Genomic selection (GS) models use genome-wide genetic information to predict genetic values of candidates of selection. Originally, these models were developed without considering genotype · environment interaction( G·E). ...
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A genomic selection index applied to simulated and real data 

Ceron Rojas, J.J.; Crossa, J.; Arief, V.N.; Basford, K.E.; Rutkoski, J.; Jarquin, D.; Alvarado Beltrán, G.; Beyene, Y.; Fentaye Kassa Semagn; DeLacy, I.H. (Genetics Society of America, 2015)
A genomic selection index (GSI) is a linear combination of genomic estimated breeding values that uses genomic markers to predict the net genetic merit and select parents from a nonphenotyped testing population. Some authors ...
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Comparison between linear and non-parametric regression models for genome-enabled prediction in wheat 

Pérez-Rodríguez, P.; Gianola, D.; Gonzalez-Camacho, J.M.; Crossa, J.; Manes, Y.; Dreisigacker, S. (Genetics Society of America, 2012)
In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The ...
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A benchmarking between deep learning, support vector machine and bayesian threshold best linear unbiased prediction for predicting ordinal traits in plant breeding 

Montesinos-Lopez, O.A.; Martin-Vallejo, J.; Crossa, J.; Gianola, D.; Hernández Suárez, C.M.; Montesinos-Lopez, A.; Juliana, P.; Singh, R.P. (Genetics Society of America, 2019)
Genomic selection is revolutionizing plant breeding. However, still lacking are better statistical models for ordinal phenotypes to improve the accuracy of the selection of candidate genotypes. For this reason, in this ...

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Author
Crossa, J. (4)Dreisigacker, S. (2)Gianola, D. (2)Singh, R.P. (2)Alvarado Beltrán, G. (1)Arief, V.N. (1)Autrique, E. (1)Basford, K.E. (1)Beyene, Y. (1)Bonnett, D. (1)... View More
Date Issued
2019 (1)2015 (2)2012 (1)
Type
Article (4)
Agrovoc
CROP FORECASTING (4)
DATA ANALYSIS (3)BAYESIAN THEORY (2)STATISTICAL METHODS (2)ARTIFICIAL SELECTION (1)BREEDING VALUE (1)GENETIC MARKERS (1)MACHINE LEARNING (1)MARKER-ASSISTED SELECTION (1)MATHEMATICAL MODELS (1)... View More
Keywords
GenPred (4)
Shared Data Resources (4)Genomic Selection (3)Deep Learning (1)GBLUP (1)Genomic Estimated Breeding Value (1)Genomic Prediction (1)International Bread Wheat Screening Nursery (1)Marker Environment Interaction (1)Multienvironment Genomic Best Linear Unbiased Prediction (1)... View More
Region
Global (1)


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