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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-enabled prediction in maize using kernel models with genotype x environment interaction 

Bandeira e Sousa, M.; Cuevas, J.; De Oliveira Couto, E.G.; Pérez-Rodríguez, P.; Jarquin, D.; Fritsche-Neto, R.; Burgueño, J.; Crossa, J. (Genetics Society of America, 2017)
Multi-environment trials are routinely conducted in plant breeding to select candidates for the next selection cycle. In this study, we compare the prediction accuracy of four developed genomic-enabled prediction models: ...
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A bayesian genomic regression model with skew normal random errors 

Pérez-Rodríguez, P.; Acosta-Pech, R.; Perez-Elizalde, S.; Velasco Cruz, C.; Suarez Espinosa, J.; Crossa, J. (Genetics Society of America, 2018)
Genomic selection (GS) has become a tool for selecting candidates in plant and animal breeding programs. In the case of quantitative traits, it is common to assume that the distribution of the response variable can be ...
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BGGE: a new package for genomic-enabled prediction incorporating genotype × environment interaction models 

Granato, I.; Cuevas, J.; Luna-Vazquez, F.J.; Crossa, J.; Montesinos-Lopez, O.A.; Burgueño, J.; Fritsche-Neto, R. (Genetics Society of America, 2018)
One of the major issues in plant breeding is the occurrence of genotype × environment (GE) interaction. Several models have been created to understand this phenomenon and explore it. In the genomic era, several models were ...
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Genome-wide association study and QTL mapping reveal genomic loci associated with Fusarium ear rot resistance in tropical maize germplasm 

Jiafa Chen; Shrestha, R.; Ding, J.; Zheng, H.; Chunhua Mu; Wu, J.; Mahuku, G. (Genetics Society of America, 2016)
Fusarium ear rot (FER) incited by Fusarium verticillioides is a major disease of maize that reduces grain quality globally. Host resistance is the most suitable strategy for managing the disease. We report the results of ...
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Use of genomic selection and breeding simulation in cross prediction for improvement of yield and quality in wheat (Triticum aestivum L.) 

Ji Yao; Dehui Zhao; Xinmin Chen; Yong Zhang; Jiankang Wang (Elsevier, 2018)
In wheat breeding, it is a difficult task to select the most suitable parents for making crosses aimed at the improvement of both grain yield and grain quality. By quantitative genetics theory, the best cross should have ...
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A Bayesian decision theory approach for genomic selection 

Villar-Hernandez, B.d.J.; Perez-Elizalde, S.; Crossa, J.; Perez-Rodriguez, P.; Toledo, F.H.; Burgueño, J. (Genetics Society of America, 2018)
Plant and animal breeders are interested in selecting the best individuals from a candidate set for the next breeding cycle. In this paper, we propose a formal method under the Bayesian decision theory framework to tackle ...
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A genomic bayesian multi-trait and multi-environment model 

Montesinos-Lopez, O.A.; Montesinos-López, A.; Toledo, F.H.; Pérez-Hernández, O.; Eskridge, K.; Rutkoski, J.; Crossa, J. (Genetics Society of America, 2016)
When information on multiple genotypes evaluated in multiple environments is recorded, a multi-environment single trait model for assessing genotype · environment interaction (G · E) is usually employed. Comprehensive ...
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Genetic architecture is more complex for resistance to Septoria tritici blotch than to Fusarium head blight in Central European winter wheat 

Mirdita, V.; Guozheng Liu; Yusheng Zhao; Miedaner, T.; Longin, F.H.; Gowda, M.; Florian Mette, M.; Reif, J.C. (BioMed Central, 2015)
Fusarium head blight (FHB) and Septoria tritici blotch (STB) severely impair wheat production. With the aim to further elucidate the genetic architecture underlying FHB and STB resistance, we phenotyped 1604 European wheat ...
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Harnessing diversity in wheat to enhance grain yield, climate resilience, disease and insect pest resistance and nutrition through conventional and modern breeding approaches 

Mondal, S.; Rutkoski, J.; Velu, G.; Singh, P.K.; Crespo-Herrera, L.A.; Guzman, C.; Bhavani, S.; Caixia Lan; Xinyao He; Singh, R.P. (Frontiers, 2016)
Current trends in population growth and consumption patterns continue to increase the demand for wheat, a key cereal for global food security. Further, multiple abiotic challenges due to climate change and evolving pathogen ...
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Author
Crossa, J. (25)Montesinos-Lopez, Osval Antonio (11)Singh, R.P. (10)Burgueño, J. (9)Pérez-Rodríguez, Paulino (9)Poland, Jesse (8)Dreisigacker, S. (7)Montesinos-López, A. (6)Rutkoski, Jessica (6)Zhang, Xuecai (6)... View More
Date Issued
2021 (4)2020 (9)2019 (4)2018 (8)2017 (4)2016 (6)2015 (4)2014 (3)2013 (2)
Type
Article (42)Presentation (1)
Agrovoc
MARKER-ASSISTED SELECTION (20)GENOMICS (16)BAYESIAN THEORY (11)WHEAT (11)PLANT BREEDING (10)STATISTICAL METHODS (10)ARTIFICIAL SELECTION (9)MAIZE (8)GENOTYPE ENVIRONMENT INTERACTION (7)DATA ANALYSIS (5)... View More
Keywords
Genomic Selection (44)
GenPred (18)Shared Data Resources (17)Genomic Prediction (9)Wheat Breeding (4)Deep Learning (3)GBLUP (3)Support Vector Machine (3)Association Mapping (2)Best Linear Unbiased Prediction (2)... View More


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