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1 to 10 of 20 Results
Dataset / Software
Nov 3, 2016 - CIMMYT Research Software
Montesinos-López, Osval Antonio; Montesinos-López, Abelardo; Crossa, José; Toledo, Fernando; Pérez-Hernández, Óscar; Eskridge, Kent M.; Rutkoski, Jessica, 2016, "A Genomic Bayesian Multi-trait and Multi-environment Model", hdl:11529/10646, CIMMYT Research Data & Software Repository Network, V4
When plant scientists record information on multiple genotypes evaluated in multiple environments, a multi-environment single trait for assessing genotype × environment interaction (G×E) model is usually employed. Comprehensive models that simultaneously take into account the cor...
Dataset / Software
Jan 25, 2016 - CIMMYT Research Data
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
Nov 8, 2018 - CIMMYT Research Data
Montesinos-López, Osval A; Montesinos-López, Abelardo; Crossa, José; Kismiantini; Ramírez-Alcaraz, Juan Manuel , 2018, "A singular value decomposition Bayesian multiple-trait and multiple-environment genomic model", hdl:11529/10547920, CIMMYT Research Data & Software Repository Network, V2
In this paper, we propose a two-stage analysis for multiple-trait data; in the first stage, we perform a singular value decomposition (SVD) on the resulting matrix of traits responses, and in the second stage, multiple trait analysis on transformed responses is performed. We use...
Dataset / Software
Jul 11, 2018 - CIMMYT Research Software
Rodríguez, Francisco; Alvarado, Gregorio; Pacheco, Ángela; Crossa, José; Burgueño, Juan, 2015, "AGD-R (Analysis of Genetic Designs with R for Windows) Version 5.0", hdl:11529/10202, CIMMYT Research Data & Software Repository Network, V13
A major objective of biometrical genetics is to explore the nature of gene action in determining quantitative traits. This also includes determination of the number of major genetic factors or genes responsible for the traits. Diallel Mating Designs have been designed to deal wit...
Dataset / Software
Sep 21, 2015 - CIMMYT Research Data
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...
Dataset / Software
Sep 12, 2016 - CIMMYT Research Data
Cuevas, Jaime; Crossa, José; Montesinos-López, Osval Antonio; Burgueño, Juan; Pérez-Rodríguez, Paulino; Campos, Gustavo de los, 2016, "Bayesian genomic prediction with genotype × environment interaction kernel models", hdl:11529/10710, CIMMYT Research Data & Software Repository Network, V1
The phenomenon of genotype × environment (G×E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G×E have been recently developed and used in genomic selection of plant breeding...
Dataset / Software
Nov 9, 2018 - CIMMYT Research Data
Granato, Italo; Cuevas, Jaime; Luna, Francisco; Crossa, José; Burgueño, Juan; Fritsche-Neto, Roberto, 2018, "BGGE: A new package for genomic prediction incorporating genotype by environments models", hdl:11529/10548107, CIMMYT Research Data & Software Repository Network, V5
One of the major issues in plant breeding is the occurrence of genotype by environment (GE) interaction. Several models have been created to understand this phenomenon and explore it by selecting the most stable genotypes. In the genomic era, several models were employed to simul...
Dataset / Software
Sep 21, 2015 - CIMMYT Research Data
Crossa, José; Campos, Gustavo de los; Maccaferri, Marco; Tuberosa, Roberto; Burgueño, Juan; Pérez-Rodríguez, Paulino, 2015, "Extending the Marker × Environment Interaction Model for Genomic-Enabled Prediction and Genome Wide Association Analyses in Durum Wheat", hdl:11529/10233, CIMMYT Research Data & Software Repository Network, V6
The marker × environment interaction (M×E) genomic model can be used to generate predictions for untested individuals and identify genomic regions whose effects are stable across environments and others that show environmental specificity. The objectives of this study were: (1) t...
Dataset / Software
Jul 11, 2018 - CIMMYT Research Software
Pacheco, Ángela; Vargas, Mateo; Alvarado, Gregorio; Rodríguez, Francisco; Crossa, José; Burgueño, Juan, 2015, "GEA-R (Genotype x Environment Analysis with R for Windows) Version 4.1", hdl:11529/10203, CIMMYT Research Data & Software Repository Network, V16
In agricultural experimentation, a large number of genotypes are normally tested over a wide range of environments. The occurrence of the genotype (G) X environment (E) interaction (GEI) effect further complicates the selection of superior genoty pes for a target population of en...
Dataset / Software
Dec 14, 2015 - CIMMYT Research Data
González-Camacho, Juan Manuel; Crossa, José; Pérez-Rodríguez, Paulino; Ornella, Leonardo; Gianola, Daniel, 2015, "Genome-enabled prediction using probabilistic neural network classifiers", hdl:11529/10576, CIMMYT Research Data & Software Repository Network, V1
Non-parametric methods have been shown to be effective in genome-enabled prediction, in particular, the multi-layer perceptron (MLP) and the radial basis function neural network (RBFNN). In this study, we evaluated and compared the performance of MLP classifier versus the probabi...
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