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1 to 4 of 4 Results
Dataset / Software
Feb 16, 2017
Bandeira e Sousa, Massaine; Cuevas, Jaime; Oliveira Couto, Evellyn Giselly de; Pérez-Rodríguez, Paulino; Jarquín, Diego; Fritsche-Neto, Roberto; Burgueño, Juan; Crossa, Jose, 2017, "Genomic-enabled prediction in maize using kernel models with genotype × environment interaction", hdl:11529/10887, CIMMYT Research Data & Software Repository Network, V1
Dataset / Software
Nov 11, 2016
Sukumaran, Sivakumar; Crossa, José; Jarquín, Diego; Lopes, Marta; Reynolds, Matthew P., 2016, "Genomic and pedigree prediction with genotype × environment interaction in spring wheat grown in South and Western Asia, North Africa, and Mexico", hdl:11529/10714, CIMMYT Research Data & Software Repository Network, V2
Increases in genetic gains in grain yield can be accelerated through genomic selection (GS). In the present study seven genomic prediction models under two cross validation scenarios were evaluated on the Wheat Association Mapping Initiative population of 287 advanced elite lines...
Dataset / Software
Jan 25, 2016
Jarquín, Diego; Pérez-Elizalde, Sergio; Burgueño, Juan; Crossa, José, 2015, "A Hierarchical Bayesian Estimation Model for Multi-Environment Plant Breeding Trials in Successive Years", hdl:11529/10463, CIMMYT Research Data & Software Repository Network, V2
In agriculture and plant breeding, multi-environment trials over multiple years are conducted to evaluate and predict genotypic performance under different environmental conditions, and to analyze, study, and interpret genotype × environment interaction (G×E). In this study, we p...
Dataset / Software
Sep 21, 2015
Cerón-Rojas, J. Jesús; Crossa, José; Arief, Vivi N.; Basford, Kaye; Rutkoski, Jessica; Jarquín, Diego; Alvarado, Gregorio; Beyene, Yoseph; Semagn, Kassa; DeLacy, Ian, 2015, "Application of a Genomics Selection Index to Real and Simulated Data", hdl:11529/10199, CIMMYT Research Data & Software Repository Network, V10
We apply a Genomic Selection Index (GSI) to simulated and real data sets with four traits and numerically we compared its efficiency with that of the phenotypic selection index (PSI) using the ratio of the GSI response over the PSI response. In addition, we used two additional cr...
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