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1 to 10 of 15 Results
Dataset / Software
Oct 8, 2018 - CIMMYT Research Data
Cerón-Rojas, J.Jesús; Toledo, Fernando; Crossa, Jose, 2018, "Supplemental Materials for The Relative Efficiency of Three Constrained Multistage Linear Phenotypic Selection Indices", hdl:11529/10548136, CIMMYT Research Data & Software Repository Network, V1
This dataset provides supplemental information related to an investigation of constrained multistage linear phenotypic selection indices.
Dataset / Software
Sep 28, 2018 - CIMMYT Research Data
Montesinos-López, Osval A ; Montesinos-López, Abelardo; Crossa, Jose; Gianola, Daniel ; Hernández-Suárez, Carlos M.; Martín-Vallejo, Javier, 2018, "Supplemental data for multi-trait, multi-environment deep learning modeling for genomic-enabled prediction of plant traits", hdl:11529/10548134, CIMMYT Research Data & Software Repository Network, V1
This study provides supplemental data to support an investigation of the power of multi-trait deep learning (MTDL) models in terms of genomic-enabled prediction accuracy.
Dataset / Software
Mar 24, 2020 - CIMMYT Research Data
Jarquin, Diego; Howard, Reka; Beyene, Yoseph; Gowda, Manje; Burgueño, Juan; Martini, Johannes; Pacheco, Angela; Covarrubias, Eduardo G.; Crossa, Jose, 2020, "Sparse designs for genomic selection using multi-environment data", hdl:11529/10548369, CIMMYT Research Data & Software Repository Network, V3
This research study the genomic-enabled prediction accuracy of the composition of the following sparse testing allocation design: (1) all non-overlapping (0 overlapping) lines in environments, (2) all overlapping (0 non-overlapping) lines tested in all the environments, and (3) c...
Dataset / Software
May 2, 2020 - CIMMYT Research Data
Villar-Hernández, Bartolo de Jesús; Crossa, Jose; Pérez-Elizalde, Sergio; García-Calvillo, Irma Delia; Toledo, Fernando; Perez-Rodriguez, Paulino, 2020, "Replication Data for: Multi-trait Bayesian decision for parental selection", hdl:11529/10548420, CIMMYT Research Data & Software Repository Network, V1
The files included in this study contains the data used with three promising multivariate loss functions: Kullback-Leibler (KL); the Energy Score; and the Multivariate Asymmetric Loss (MALF); to select the best performing parents for the next breeding cycle in two extensive real...
Dataset / Software
Jul 12, 2019 - CIMMYT Research Data
Howard, Reka; Gianola, Daniel; Montesinos-López, Osval; Juliana, Philomin; Singh, Ravi; Poland, Jesse; Shrestha, Sandesh; Perez-Rodriguez, Paulino; Crossa, Jose; Jarquin, Diego, 2019, "Replication Data for: Joint use of genome, pedigree and their interaction with environment for predicting the performance of wheat lines in new environments", hdl:11529/10548169, CIMMYT Research Data & Software Repository Network, V3
In this study, we evaluated genome-based prediction using 35,403 wheat lines from the Global Wheat Breeding Program of the International Maize and Wheat Improvement Center (CIMMYT). We implemented eight statistical models that included genome-wide molecular marker and pedigree in...
Dataset / Software
May 11, 2020 - CIMMYT Research Data
Ibba, Maria Itria; Crossa, Jose; Montesinos-López, Osval A.; Montesinos-López, Abelardo; Juliana, Philomin; Guzman, Carlos; Dolorean, Emily; Dreisigacker, Susanne ; Poland, Jesse, 2020, "Replication Data for: Genome-based prediction of multiple wheat quality traits in multiple years", hdl:11529/10548423, CIMMYT Research Data & Software Repository Network, V1
The use of genomic prediction could greatly help to increase the efficiency of selecting for wheat quality traits by reducing the cost and time required for this analysis. This study contains data used to evaluate the prediction performances of 13 wheat quality traits under two m...
Dataset / Software
May 24, 2020 - CIMMYT Research Data
Cuevas, Jaime; Montesinos-López, Osval A.; Martini, Johannes; Pérez-Rodríguez, Paulino; Lillemo, Morten; Crossa, Jose, 2020, "Replication Data for: Approximate kernels for large data sets In genome-based prediction", hdl:11529/10548425, CIMMYT Research Data & Software Repository Network, V1
The rapid development of molecular markers and sequencing technologies has made it possible to use genomic selection (GS) and genomic prediction (GP) in animal and plant breeding. However, computational difficulties arise when the number of observations is large. This five datase...
Dataset / Software
May 30, 2020 - CIMMYT Research Data
Montesinos-López, Osval A ; Montesinos-López, José Cricelio; Singh, Pawan; Lozano-Ramirez, Nerida; Barrón-López, Alberto; Montesinos-López, Abelardo; Crossa, Jose, 2020, "Replication Data for: A multivariate Poisson deep learning model for genomic prediction of count data", hdl:11529/10548438, CIMMYT Research Data & Software Repository Network, V1
Genomic selection (GS) is an important method used in plant and animal breeding. The experimental data provided in this study contain counting data. These datasets were used to support research on efficient methodologies for multivariate count data outcomes including a multivaria...
Dataset / Software
Mar 26, 2019 - CIMMYT Research Data
Guzman, Carlos, 2019, "PPO activity in bread wheat breeding lines from C53IBWSN", hdl:11529/10548173, CIMMYT Research Data & Software Repository Network, V1
Breeding lines cultivated in CENEB (C. Obregon) during cropping cycle 17-18 were analyzed for PPO activity
Dataset / Software
Dec 17, 2019 - CIMMYT Research Data
Singh, Ravi; Mondal, Suchismita; Crespo, Leonardo; Kummar, Uttam; Imtiaz, Muhammad; Lan, Caixia; Randhawa, Mandeep; Bhavani, Sridhar; Singh, Pawan K.; Huerta, Julio; He, Xinyao; Rahman, Mokhles; Pinto, Francisco; Perez Gonzalez, Lorena; Juliana, Philomin; Singh, Daljit; Lucas, Mark; Kumar Bhati, Pradeep; Altschuler, Josiah; Poland, Jesse, 2016, "Phenotypic data from trials conducted by the CIMMYT Bread Wheat Breeding Program", hdl:11529/10696, CIMMYT Research Data & Software Repository Network, V7, UNF:6:3VbaGOICYWiowZjh8EN+lA==
Phenotypic data were collected in on-station field trials for advanced breeding lines from the CIMMYT Bread Wheat breeding program over several years.
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