CIMMYT Research Data & Software Repository Network

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Contributor Name: CGIAR Research Program on Wheat (WHEAT) Contributor Name: Global Wheat Program (GWP) Keyword Term: Triticum aestivum Contributor Name: CGIAR Contributor Name: Bill and Melinda Gates Foundation (BMGF) Author Name: Juliana, Philomin

1 to 3 of 3 Results

Dataset / Software Replication Data for: Joint use of genome, pedigree and their interaction with environment for predicting the performance of wheat lines in new environments 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 Phenotypic data from trials conducted by the CIMMYT Bread Wheat Breeding Program May 16, 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; Poland, Jesse, 2016, "Phenotypic data from trials conducted by the CIMMYT Bread Wheat Breeding Program", hdl:11529/10696, CIMMYT Research Data & Software Repository Network, V6 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 Deep kernel of genomic and near infrared predictions in multi-environment breeding trials Jul 18, 2019 - CIMMYT Research Data 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

Replication Data for: Joint use of genome, pedigree and their interaction with environment for predicting the performance of wheat lines in new environments

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

Phenotypic data from trials conducted by the CIMMYT Bread Wheat Breeding Program

May 16, 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; Poland, Jesse, 2016, "Phenotypic data from trials conducted by the CIMMYT Bread Wheat Breeding Program", hdl:11529/10696, CIMMYT Research Data & Software Repository Network, V6

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

Deep kernel of genomic and near infrared predictions in multi-environment breeding trials

Jul 18, 2019 - CIMMYT Research Data

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...

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