CIMMYT Research Data & Software Repository Network

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9,611 to 9,620 of 12,512 Results

Data_Wheat_Iranian_Set_3.RData.gz Oct 26, 2018 - A Bayesian genomic multi-output regressor stacking model for predicting multi-trait multi-environment plant breeding data Gzip Archive - 41.1 MB - MD5: fd6c1e6305f656eb8476209bba629a03
Data_Wheat_Set_2.RData.gz Oct 26, 2018 - A Bayesian genomic multi-output regressor stacking model for predicting multi-trait multi-environment plant breeding data Gzip Archive - 458.8 KB - MD5: bdebf18268314e8e14812abb2b1751d0
ADEL-R. Analysis and design of experiments with R for Windows. Version 2.0 Oct 26, 2018 - CIMMYT Research Software Pacheco-Gil, Rosa Ángela; Rodríguez, Francisco; Alvarado, Gregorio; Burgueño, Juan, 2017, "ADEL-R. Analysis and design of experiments with R for Windows. Version 2.0", https://hdl.handle.net/11529/10857, CIMMYT Research Data & Software Repository Network, V3 ADEL-R is a set of R programs that create and analyze experimental designs, in order to make field books and map fields when you create a design and if you analyze a design you can obtain the ANOVA table and comparison means graph. ADEL-R analyze designs like: random complete blo...
ADEL-R_v2.0_BASE_setup.exe Oct 26, 2018 - ADEL-R. Analysis and design of experiments with R for Windows. Version 2.0 Windows Executable - 307.1 MB - MD5: 90afaca602228cc3eafb8e2fcb3ea427
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_Wheat_Iranian_Set_3.RData.gz

Oct 26, 2018 - A Bayesian genomic multi-output regressor stacking model for predicting multi-trait multi-environment plant breeding data

Gzip Archive - 41.1 MB -

Data_Wheat_Set_2.RData.gz

Oct 26, 2018 - A Bayesian genomic multi-output regressor stacking model for predicting multi-trait multi-environment plant breeding data

Gzip Archive - 458.8 KB -

ADEL-R. Analysis and design of experiments with R for Windows. Version 2.0

Oct 26, 2018 - CIMMYT Research Software

Pacheco-Gil, Rosa Ángela; Rodríguez, Francisco; Alvarado, Gregorio; Burgueño, Juan, 2017, "ADEL-R. Analysis and design of experiments with R for Windows. Version 2.0", https://hdl.handle.net/11529/10857, CIMMYT Research Data & Software Repository Network, V3

ADEL-R is a set of R programs that create and analyze experimental designs, in order to make field books and map fields when you create a design and if you analyze a design you can obtain the ANOVA table and comparison means graph. ADEL-R analyze designs like: random complete blo...

ADEL-R_v2.0_BASE_setup.exe

Oct 26, 2018 - ADEL-R. Analysis and design of experiments with R for Windows. Version 2.0

Windows Executable - 307.1 MB -

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 -

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