Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Advanced Search

9,711 to 9,720 of 12,512 Results
Deep learning genomic-enabled prediction of plant traits
Jun 13, 2018 - CIMMYT Research Data
Montesinos-López, Abelardo; Montesinos-López, Osval A.; Gianola, Daniel; Crossa, Jose, 2018, "Deep learning genomic-enabled prediction of plant traits", https://hdl.handle.net/11529/10548082, CIMMYT Research Data & Software Repository Network, V1
Machine learning (ML) is a field of computer science that uses statistical techniques to give computer systems the ability to "learn" (i.e., progressively improve performance on a specific task) from data, without being explicitly programmed to do this. ML is closely related to (...
DataSets_DL.rar
Jun 13, 2018 - Deep learning genomic-enabled prediction of plant traits
RAR Archive - 53.5 MB - MD5: 501f5155e0ace71d010f4132fb3baa18
Identifying high-yield low-emission pathways for the cereal production in South Asia
Jun 7, 2018 - CIMMYT Research Data
Sapkota, Tek B.; Aryal, Jeetendra P.; Khatri-Chhetri, Arun; Shirsath, Paresh B; Arumugam, Ponraj; Stirling, Clare M., 2018, "Identifying high-yield low-emission pathways for the cereal production in South Asia", https://hdl.handle.net/11529/10548077, CIMMYT Research Data & Software Repository Network, V2, UNF:6:5kNA+QcDnMGOgK0NnR9nyQ== [fileUNF]
Household survey was conducted by International Maize and Wheat Improvement Centre (CIMMYT) as part of CGIAR research program on Climate Change Agriculture and Food Security (CCAFS) in Karnal district of Haryana state and Vaishali district of Bihar state in India. The overall aim...
GHG_emission - Dataset-1.tab
Jun 7, 2018 - Identifying high-yield low-emission pathways for the cereal production in South Asia
Tabular Data - 1023.6 KB - 18 Variables, 4564 Observations - UNF:6:vqEUOBmqgrGaUwTz1Kgmzg==
GHG_emission - Metadata.tab
Jun 7, 2018 - Identifying high-yield low-emission pathways for the cereal production in South Asia
Tabular Data - 1.2 KB - 6 Variables, 18 Observations - UNF:6:nh8p1xbhhJL6LtJUeiDrbg==
MAIZEDIALLEL-2LOCS-2YEARS.tab
May 5, 2018 - Program and sample data for SASHAYDIALL: A SAS Program for Hayman’s Diallel Analysis
Tabular Data - 10.3 KB - 6 Variables, 728 Observations - UNF:6:qb2UIHULo/KZ3V04rm33PA==
Sample Dataset
48IDYN_Genotypes_Data.xls
May 4, 2018 - 48th International Durum Yield Nursery
MS Excel Spreadsheet - 6.5 KB - MD5: 35ac7878b2345922d762c34844e91dcf
IWIN Germplasm Data
List of genotypes included on the nursery
48IDYN_GrnYld.xls
May 4, 2018 - 48th International Durum Yield Nursery
MS Excel Spreadsheet - 497.3 KB - MD5: f329fac4191ad06ed16ca390fafb43b7
IWIN Analyzed data
Means for Grain Yield by location
48IDYN_Loc_data.xls
May 4, 2018 - 48th International Durum Yield Nursery
MS Excel Spreadsheet - 5.1 KB - MD5: 42baced8ddf8837540241469e2c11e15
IWIN Summarized Data
Institution, Cooperator and Location where the nurseries were evaluated
48IDYN_MeanVal.xls
May 4, 2018 - 48th International Durum Yield Nursery
MS Excel Spreadsheet - 2.1 MB - MD5: 4447ff3460e535573128a51b1eb5c848
IWIN Summarized Data
Means of phenotypic data values for traits across locations, arrangement by row
Add Data

Sign up or log in to create a dataverse or add a dataset.

Sign Up Log In
Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.