CIMMYT Research Data & Software Repository Network

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CIMMYT institutional network of scientific datasets and software repositories.

Cereal Systems Initiative for South Asia (CSISA) Research Data

CIMMYT Research Data

CIMMYT Research Software

International Wheat Yield Partnership Research Data

Sustainable and Resilient Farming Systems Intensification in the Eastern Gangetic Plains (SRFSI) Research Data

Crops to End Hunger (CtEH) Data

CIMMYT Seeds of Discovery

BNI-CropSustaiN Research Data and Protocols

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10,221 to 10,230 of 13,433 Results

Zero-Tillage adoption and its welfare impacts at the farm household level Oct 24, 2018 - CIMMYT Research Data Keil, Alwin; Michalski, Joel, 2016, "Zero-Tillage adoption and its welfare impacts at the farm household level", https://hdl.handle.net/11529/10840, CIMMYT Research Data & Software Repository Network, V3 The purpose of the study was (1) to assess the performance of ZT wheat as compared to conventional-tillage wheat in farmers' fields in six CSISA target districts in Bihar; (2) to assess farmers’ resource endowment, risk exposure, risk preferences, and risk management practices; (...
New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes Oct 22, 2018 - CIMMYT Research Data Montesinos-López, Osval A.; Martín-Vallejo, Javier; Crossa, Jose; Gianola, Daniel; Hernández-Suarez, Carlos Moisés; Montesinos-López, Abelardo; Juliana, Philomin; Singh, Ravi, 2018, "New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes", https://hdl.handle.net/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.
Data_Set_1.RData.gz Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes Gzip Archive - 4.3 MB - MD5: 231fdf85ad051b494deacd4886d55708
Data_Set_2.RData.gz Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes Gzip Archive - 4.4 MB - MD5: 74cf012e823cf8ff5eff6a51f10d592c
Data_Set_3.RData.gz Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes Gzip Archive - 6.8 MB - MD5: 4c158d81032c889c280f1918b5d1b16f
Data_Set_4.RData.gz Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes Gzip Archive - 7.0 MB - MD5: bc2a4fce307e769e24b9f477e14592f6
Data_Set_5.RData.gz Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes Gzip Archive - 6.8 MB - MD5: 0af143aab2914c4d065ef8ef9037632d
Data_Set_6.RData.gz Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes Gzip Archive - 153.6 KB - MD5: d891bbd1db0577097ef9ce267581237f
Data_Set_7.RData.gz Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes Gzip Archive - 261.2 KB - MD5: f0396ede52b49e1a91090a95e299bc31
SUPPLEMENTARY MATERIAL.docx Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes MS Word - 358.9 KB - MD5: 6bfa2583115c2816b2945150fb882e77

Zero-Tillage adoption and its welfare impacts at the farm household level

Oct 24, 2018 - CIMMYT Research Data

Keil, Alwin; Michalski, Joel, 2016, "Zero-Tillage adoption and its welfare impacts at the farm household level", https://hdl.handle.net/11529/10840, CIMMYT Research Data & Software Repository Network, V3

The purpose of the study was (1) to assess the performance of ZT wheat as compared to conventional-tillage wheat in farmers' fields in six CSISA target districts in Bihar; (2) to assess farmers’ resource endowment, risk exposure, risk preferences, and risk management practices; (...

New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes

Oct 22, 2018 - CIMMYT Research Data

Montesinos-López, Osval A.; Martín-Vallejo, Javier; Crossa, Jose; Gianola, Daniel; Hernández-Suarez, Carlos Moisés; Montesinos-López, Abelardo; Juliana, Philomin; Singh, Ravi, 2018, "New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes", https://hdl.handle.net/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.

Data_Set_1.RData.gz

Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes

Gzip Archive - 4.3 MB -

Data_Set_2.RData.gz

Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes

Gzip Archive - 4.4 MB -

Data_Set_3.RData.gz

Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes

Gzip Archive - 6.8 MB -

Data_Set_4.RData.gz

Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes

Gzip Archive - 7.0 MB -