CIMMYT institutional network of scientific datasets and software repositories.
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7,151 to 7,160 of 13,434 Results
CIMMYT Maize Genetic Resource Lines
CIMMYT Maize Genetic Resource Lines
Nov 13, 2020 - CIMMYT Research Data
Molnar, Terence; Carvalho Andrade, Marcela; Chanona, Enrique Rodriguez; Chepetla Calderon, Daniel; Burgueño, Juan; Crossa, Jose, 2020, "CIMMYT Maize Genetic Resource Lines", https://hdl.handle.net/11529/10548528, CIMMYT Research Data & Software Repository Network, V2
CIMMYT makes available to the public a set of maize inbred lines called CIMMYT Maize Genetic Resource Lines (CMGRL). The CMGRLs are derived from crosses between elite CIMMYT lines and landrace accessions, populations or synthetics from the CIMMYT Germplasm Bank. CMGRLs are intend...
CMGRL Release-1 2.Data for TSC Lines.pdf
CMGRL Release-1 2.Data for TSC Lines.pdf
Nov 13, 2020 - CIMMYT Maize Genetic Resource Lines
Adobe PDF - 442.3 KB - MD5: b211f5dd29d9fde52173490d996cd653
CMGRL Release-1 1.Line Information.pdf
CMGRL Release-1 1.Line Information.pdf
Oct 27, 2020 - CIMMYT Maize Genetic Resource Lines
Adobe PDF - 409.8 KB - MD5: f1f3d821a23690cdcc7f6a8a8f79e0f7
CMGRL Release-1 3.Data for Drought Lines.pdf
CMGRL Release-1 3.Data for Drought Lines.pdf
Oct 27, 2020 - CIMMYT Maize Genetic Resource Lines
Adobe PDF - 439.6 KB - MD5: 86f24b95892517d1f8776b5a2e1da723
CMGRL Release-1 4.Collaborator Acknowledgements.pdf
CMGRL Release-1 4.Collaborator Acknowledgements.pdf
Oct 27, 2020 - CIMMYT Maize Genetic Resource Lines
Adobe PDF - 48.7 KB - MD5: 32964fa6f7603408a220f9f09f4dff33
Replication Data for: A guide for generalized kernel regression methods for genomic-enabled prediction
Oct 24, 2020 - CIMMYT Research Data
Montesinos-López, Abelardo; Montesinos-López, Osval A.; Montesinos-López, José Cricelio; Flores-Cortes, Carlos Alberto; de la Rosa, Roberto; Crossa, Jose, 2020, "Replication Data for: A guide for generalized kernel regression methods for genomic-enabled prediction", https://hdl.handle.net/11529/10548532, CIMMYT Research Data & Software Repository Network, V1
The data contained in these datasets can be used to implement Bayesian generalized kernel regression methods for genome-enabled prediction in the statistical software R, The accompanying paper describes the building process of 7 kernel methods (linear, polynomial, sigmoid, Gaussi...
Data_Toy_EYT.RData.gz
Oct 24, 2020 - Replication Data for: A guide for generalized kernel regression methods for genomic-enabled prediction
Gzip Archive - 10.0 KB - MD5: 3976d1f35394e734911a7a8ad9c4ea5e
Data_Wheat_2019.RData.gz
Oct 24, 2020 - Replication Data for: A guide for generalized kernel regression methods for genomic-enabled prediction
Gzip Archive - 305.5 KB - MD5: 43c83cc75a677aec136d1aa79b1b5f17
AP06 Chasing wheat yields in challenging environments
Oct 20, 2020 - International Wheat Yield Partnership Research Data
Barnard, Annelie, 2020, "AP06 Chasing wheat yields in challenging environments", https://hdl.handle.net/11529/10548421, CIMMYT Research Data & Software Repository Network, V1, UNF:6:jT9p2RrZEAxsc3QR1QJn8A== [fileUNF]
This project makes use of known cloned yield component markers (targeted from Literature), in an attempt to accumulated favourable alleles to increase yield. The traits targeted to date are, grain size, TKM, grain number and tiller number. Recently, new root phenotyping methods w...
Data_AP06_molecular data.tab
Oct 20, 2020 - AP06 Chasing wheat yields in challenging environments
Tabular Data - 8.4 KB - 27 Variables, 56 Observations - UNF:6:BL6KVaCVk4x2exkqB3SLmg==
Molecular data from AP06
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