Free, open access repository of research studies developed by CIMMYT scientists.
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

7,031 to 7,040 of 10,510 Results
Deep kernel and deep learning for genomic-based prediction
Aug 15, 2019
Crossa, Jose; Martini, Johannes; Gianola, Daniel; Pérez-Rodríguez, Paulino; Burgueño, Juan; Singh, Ravi; Juliana, Philomin; Montesinos-López, Osval A.; Cuevas, Jaime, 2019, "Deep kernel and deep learning for genomic-based prediction", https://hdl.handle.net/11529/10548273, CIMMYT Research Data & Software Repository Network, V1
Deep learning (DL) is a promising method in the context of genomic prediction for selecting individuals early in time without measuring their phenotypes. iI this paper we compare the performance in terms of genome-based prediction of the DL method, deep kernel (arc-cosine kernel,...
Geno_eyt1516_1052linesand8402markers.7z
Aug 15, 2019 - Deep kernel and deep learning for genomic-based prediction
7Z Archive - 1.1 MB - MD5: ed49e029b92a168c4711b550b670e91b
Genotypic data_EYT1516
Geno_eyt1617_1040linesand8312markers.7z
Aug 15, 2019 - Deep kernel and deep learning for genomic-based prediction
7Z Archive - 1.0 MB - MD5: 35fa8334623ef10d5e87760c48f53630
Genotypic data_EYT1617
PHENOTYPIC DATA.7z
Aug 15, 2019 - Deep kernel and deep learning for genomic-based prediction
7Z Archive - 130.4 KB - MD5: d873938a21d1df115b0133fecb95509a
Phenotypic data
TAMASA_NOTs_Database_Nigeria_2015_2016.tab
Aug 15, 2019 - NG 2015 2016 NOTs soil leaf yield database
Tabular Data - 3.3 KB - 5 Variables, 24 Observations - UNF:6:8WnI5ertrYb+cnu08o0gxQ==
Nigeria PT Maize database 04022019.tab
Aug 15, 2019 - Nigeria Performance Trials 2016
Tabular Data - 3.1 KB - 5 Variables, 24 Observations - UNF:6:m584cAFq8CYyhkLLCAcFqA==
TAMASA_TZ_APS_CS_2016
Aug 15, 2019
Chamberlin, Jordan; Craufurd, Peter; Masuki, Kenneth, 2019, "TAMASA_TZ_APS_CS_2016", https://hdl.handle.net/11529/10548231, CIMMYT Research Data & Software Repository Network, V1
This dataset consists of community-level data on 42 communities in 25 maize-growing districts in Tanzania.
TAMASA_TZ_APS_CS_2016.xlsx
Aug 15, 2019 - TAMASA_TZ_APS_CS_2016
MS Excel Spreadsheet - 63.2 KB - MD5: c51f2e9989e61684b0555fa83da14dd4
TAMASA NOTs Ethiopia 2015-2016
Aug 15, 2019
Rurinda, Jairos; Kebede, Mesfin, 2019, "TAMASA NOTs Ethiopia 2015-2016", https://hdl.handle.net/11529/10548239, CIMMYT Research Data & Software Repository Network, V1
Nutrient Omission Trials (NOTs) conducted in two zones (West Showa and Jimma) in Ethiopia in 2015 and 2016. Trials comprise six nutrient management treatments, namely Control (zero fertilizer), PK, NK, PK, NPK, NPK+Ca+Mg+Zn+B. Trials were conducted on-farm with six plots per farm...
TAMASA_NOTs_Database_Ethiopia_2015_2016.xlsx
Aug 15, 2019 - TAMASA NOTs Ethiopia 2015-2016
MS Excel Spreadsheet - 815.3 KB - MD5: 6ab1dda0aa305a293ee316cc3594b9aa
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.