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1 to 10 of 83 Results
Dataset / Software
Feb 1, 2019
Mondal, Suchismita; Krause, Margaret ; Juliana, Philomin; Poland, Jesse; Dreisigacker, Susanne; Singh, Ravi, 2018, "Use of hyperspectral reflectance-derived relationship matrices for genomic prediction of grain yield in wheat - data for publication", hdl:11529/10548109, CIMMYT Research Data & Software Repository Network, V2
Genomic, pedigree, grain yield and hyperspectral data for the manuscript
Dataset / Software
Sep 21, 2018
Basnet, Bhoja Raj; Crossa, José; Pérez-Rodríguez, Paulino; Manes, Yann; Singh, Ravi ; Rosyara, Umesh; Camarillo-Castillo, Fatima; Murua, Mercedes, 2018, "Supplemental data for hybrid wheat prediction using genomic, pedigree and environmental covariables interaction models", hdl:11529/10548129, CIMMYT Research Data & Software Repository Network, V1
Genomic prediction of hybrids unobserved in field evaluations is crucial. In this study, we used genomic G×E models for hybrid prediction, where similarity between lines was assessed by pedigree and molecular markers, and similarity between environments was accounted for by envir...
Dataset / Software
Jun 25, 2019
Lobell, David B.; Banziger, Marianne; Magorokosho, Cosmos; Vivek, Bindiganavile, 2019, "Replication Data for: Nonlinear heat effects on African maize as evidenced by historical yield trials", hdl:11529/10548190, CIMMYT Research Data & Software Repository Network, V1
This dataset provides supplementary files for the trials and sites described in the 2011 paper in available at
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
Dec 8, 2018
Yuan, Yibing; Cairns, Jill E.; Babu, Raman; Gowda, Manje; Makumbi, Dan; Magorokosho, Cosmos; Zhang, Ao; Liu, Yubo; Wang, Nan; Hao, Zhuanfang; San Vicente, Felix; Olsen, Michael S.; Prasanna, Boddupalli M. ; Lu, Yanli; Zhang, Xuecai, 2018, "Replication Data for: Genome-Wide Association Mapping And Genomic Prediction Analyses Reveal the Genetic Architecture of Grain Yield and Flowering Time Under Drought and Heat Stress Conditions in Maize", hdl:11529/10548156, CIMMYT Research Data & Software Repository Network, V1
Drought stress, heat stress, and combination of drought stress and heat stress have been recognized as the major abiotic constraints to maize yields in the main production regions. The phenotypic data used in the current study had been published by Jill E. Cairns et al in 2013 in...
Dataset / Software
May 16, 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; 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
Oct 22, 2018
Montesinos-López, Osval A ; Martín-Vallejo, Javier; Crossa, Jose; Gianola, Daniel ; Hernández-Suárez, Carlos M.; Montesinos-López, Abelardo; Juliana, Philomin; Singh, Ravi, 2018, "New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes", hdl:11529/10548140, CIMMYT Research Data & Software Repository Network, V1
The seven data sets are wheat data from CIMMYT Global Wheat Breeding program. They comprise different traits, like days to heading, days to maturity, grain yield, grain color, different type of leaf and stripe rust in wheat. Also the trials were run in different environments.
Dataset / Software
Aug 12, 2019
Montesinos-López, Osval A ; Montesinos-López, Abelardo; Tuberosa, Roberto; Maccaferri, Marco; Sciara, Giuseppe; Ammar, Karim; Crossa, Jose, 2019, "Multi-trait multi-environment genomic prediction of durum wheat", hdl:11529/10548262, CIMMYT Research Data & Software Repository Network, V1
In this paper we cover multi-trait prediction of grain yield (GY), days to heading (DH) and plant height (PH) of 270 durum wheat lines that were evaluated in 43 environments (location-year combinations) in Bologna, Italy. The results of the multi-trait deep learning method also w...
Dataset / Software
May 12, 2017
Torres Flores, Jose Luis; Garcia, Beatriz Mendoza; Boddupalli, Maruthi Prasanna; Alvarado, Gregorio; San Vicente, Felix M.; Crossa, Jose, 2017, "Grain yield and stability of white early hybrids in the highland valleys of Mexico", hdl:11529/10934, CIMMYT Research Data & Software Repository Network, V2
Dataset / Software
Oct 5, 2017
Sukumaran, Sivakumar; Reynolds, Matthew P.; Carolina, Sansaloni, 2017, "Genotype x environment interaction and GWAS in a durum panel under yield potential, drought stress, and heat stress conditions", hdl:11529/11053, CIMMYT Research Data & Software Repository Network, V1
GWAS identifies common loci under stressed and non-stressed environments.
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