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1 to 10 of 17 Results
Dataset / Software
Jan 17, 2018
Ammar, Karim; Guzman, Carlos; Dreisigacker, Susanne; Huerta, Julio; Bekele, Abeyo; Badebo, Ayele; Yahyaoui, Amor, 2018, "Phenotypic and genotypic data from the CIMMYT Durum Wheat Breeding Program", hdl:11529/10944, CIMMYT Research Data & Software Repository Network, V1
Phenotypic data collected in on-station field trials and genotypic data for breeding materials from the CIMMYT Durum Wheat breeding program are included in this study.
Dataset / Software
Sep 28, 2018
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
Oct 8, 2018
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
Nov 12, 2018
Battenfield, Sarah; Sheridan, Jaime; Silva, Luciano ; Miclaus, Kelci; Dreisigacker, Susanne; Wolfinger, Russell; Peña, Roberto; Singh, Ravi; Jackson, Eric; Fritz, Allan; Guzmán, Carlos; Poland, Jesse, 2018, "Grain quality data from CIMMYT bread wheat breeding program (2010-2015)", hdl:11529/10548148, CIMMYT Research Data & Software Repository Network, V1
Bread wheat breeding lines from yield and elite yield trials are analyzed annually for grain quality traits at the Wheat Chemistry and Quality Laboratory of CIMMYT. The analysis done are the following: grain morphology (test weight and thousand kernel weight), grain hardness and...
Dataset / Software
Mar 26, 2019
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
Jul 12, 2019
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
Jul 18, 2019
Cuevas, Jaime; Montesinos-López, Osval A; Juliana, Philomin; Pérez-Rodríguez, Paulino; Burgueño, Juan; Guzman, Carlos; Montesinos-López, Abelardo; Crossa, Jose, 2019, "Deep kernel of genomic and near infrared predictions in multi-environment breeding trials", hdl:11529/10548180, CIMMYT Research Data & Software Repository Network, V4
In genomic prediction deep learning artificial neural network are part of machine learning methods that incorporate parametric, non-parametric and semi-parametric statistical models. Kernel methods are seeing more flexible, and easier to interpret than neural networks. Kernel met...
Dataset / Software
Dec 6, 2019
Cerón-Rojas, J. Jesus; Crossa, Jose, 2019, "Combined Multistage Linear Genomic Selection Indices to Predict the Net Genetic Merit in Plant Breeding", hdl:11529/10548356, CIMMYT Research Data & Software Repository Network, V1
Multistage selection is a cost-saving strategy for improving several traits because it is not necessary to measure all traits at each stage. A combined linear genomic selection index is a linear combination of phenotypic and genomic estimated breeding values useful to predict the...
Dataset / Software
Dec 17, 2019
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.
Dataset / Software
Jan 31, 2020
Sehgal, Deepmala; Rosyara, Umesh; Mondal, Suchismita; Singh, Ravi; Poland, Jesse; Dreisigacker, Susanne, 2020, "Genomic selection models based on integration of GWAS loci and epistatic interactions", hdl:11529/10548366, CIMMYT Research Data & Software Repository Network, V1
The potential to integrate consistent associations identified from GWAS as fixed variables in GP models to improve prediction accuracy for complex traits (for example, grain yield) has not been investigated comprehensively in wheat. Here, we untangled the genetic architecture of...
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