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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9,481 to 9,490 of 13,434 Results

06CHTTEW-Locations.xls Aug 11, 2019 - International Early White Hybrid Trial - IEWH0611 MS Excel Spreadsheet - 28.5 KB - MD5: 7b8fcaaad89932368b3922c72118c17c Locations
Long-term tillage and residue management experiment in San Luis Potosí, Mexico Aug 4, 2019 - CIMMYT Research Data Verhulst, Nele; Fonteyne, Simon; Martinez Gamiño, Miguel-Angel; Saldivia Tejeda, Abel, 2019, "Long-term tillage and residue management experiment in San Luis Potosí, Mexico", https://hdl.handle.net/11529/10548248, CIMMYT Research Data & Software Repository Network, V1, UNF:6:IoKHUBaC8wFwyZ40ygz99g== [fileUNF] An experiment initiated in 1996 in the highlands of the state of San Luis Potosí, Mexico, evaluated different tillage methods and levels of soil cover under permanent raised beds for their effects on yield, profitability, and soil quality in an irrigated, summer maize- winter oat...
DAT-PUB-Soledad.tab Aug 4, 2019 - Long-term tillage and residue management experiment in San Luis Potosí, Mexico Tabular Data - 3.8 KB - 5 Variables, 86 Observations - UNF:6:IoKHUBaC8wFwyZ40ygz99g==
Deep kernel of genomic and near infrared predictions in multi-environment breeding trials Jul 18, 2019 - CIMMYT Research Data Cuevas, Jaime; Montesinos-López, Osval A.; Juliana, Philomin; Pérez-Rodríguez, Paulino; Burgueño, Juan; Guzman, Carlos; Montesinos-López, Abelardo; Crossa, Jose, 2019, "Deep kernel of genomic and near infrared predictions in multi-environment breeding trials", https://hdl.handle.net/11529/10548180, CIMMYT Research Data & Software Repository Network, V4 In genomic prediction deep learning artificial neural network are part of machine learning methods that incorporate parametric, non-parametric and semi-parametric statistical models. Kernel methods are seeing more flexible, and easier to interpret than neural networks. Kernel met...
MAIZE2 DATA SET.rar Jul 18, 2019 - Deep kernel of genomic and near infrared predictions in multi-environment breeding trials RAR Archive - 5.6 MB - MD5: d6c9b7e9394f946bdec40c119a09f821
MAIZE3 DATA SET.rar Jul 18, 2019 - Deep kernel of genomic and near infrared predictions in multi-environment breeding trials RAR Archive - 13.4 MB - MD5: 293ec3553210607db6c9e18f87bfadc4
WHEAT1 DATA SET.rar Jul 18, 2019 - Deep kernel of genomic and near infrared predictions in multi-environment breeding trials RAR Archive - 280.2 KB - MD5: 4873ac1274ab0e4423c224ceee651c73
WHEAT4 DATA SET.rar Jul 18, 2019 - Deep kernel of genomic and near infrared predictions in multi-environment breeding trials RAR Archive - 6.0 MB - MD5: 629ebcd9f3f625eb8505e6764371e491
Replication Data for: Joint use of genome, pedigree and their interaction with environment for predicting the performance of wheat lines in new environments Jul 12, 2019 - CIMMYT Research Data Howard, Reka; Gianola, Daniel; Montesinos-López, Osval A.; Juliana, Philomin; Singh, Ravi; Poland, Jesse; Shrestha, Sandesh; Pérez-Rodríguez, Paulino; Crossa, Jose; Jarquín, Diego, 2019, "Replication Data for: Joint use of genome, pedigree and their interaction with environment for predicting the performance of wheat lines in new environments", https://hdl.handle.net/11529/10548169, CIMMYT Research Data & Software Repository Network, V3 In this study, we evaluated genome-based prediction using 35,403 wheat lines from the Global Wheat Breeding Program of the International Maize and Wheat Improvement Center (CIMMYT). We implemented eight statistical models that included genome-wide molecular marker and pedigree in...
SUPPLEMENTARY MATERIAL.docx Jul 12, 2019 - Replication Data for: Joint use of genome, pedigree and their interaction with environment for predicting the performance of wheat lines in new environments MS Word - 555.5 KB - MD5: 3ab27a8128954bc2aea9ab3611dd97f3 Supplementary materials including figures S1 and S2

06CHTTEW-Locations.xls

Aug 11, 2019 - International Early White Hybrid Trial - IEWH0611

MS Excel Spreadsheet - 28.5 KB -

Locations

Long-term tillage and residue management experiment in San Luis Potosí, Mexico

Aug 4, 2019 - CIMMYT Research Data

Verhulst, Nele; Fonteyne, Simon; Martinez Gamiño, Miguel-Angel; Saldivia Tejeda, Abel, 2019, "Long-term tillage and residue management experiment in San Luis Potosí, Mexico", https://hdl.handle.net/11529/10548248, CIMMYT Research Data & Software Repository Network, V1, UNF:6:IoKHUBaC8wFwyZ40ygz99g== [fileUNF]

An experiment initiated in 1996 in the highlands of the state of San Luis Potosí, Mexico, evaluated different tillage methods and levels of soil cover under permanent raised beds for their effects on yield, profitability, and soil quality in an irrigated, summer maize- winter oat...

DAT-PUB-Soledad.tab

Aug 4, 2019 - Long-term tillage and residue management experiment in San Luis Potosí, Mexico

Tabular Data - 3.8 KB - 5 Variables, 86 Observations -

Deep kernel of genomic and near infrared predictions in multi-environment breeding trials

Jul 18, 2019 - CIMMYT Research Data

Cuevas, Jaime; Montesinos-López, Osval A.; Juliana, Philomin; Pérez-Rodríguez, Paulino; Burgueño, Juan; Guzman, Carlos; Montesinos-López, Abelardo; Crossa, Jose, 2019, "Deep kernel of genomic and near infrared predictions in multi-environment breeding trials", https://hdl.handle.net/11529/10548180, CIMMYT Research Data & Software Repository Network, V4

In genomic prediction deep learning artificial neural network are part of machine learning methods that incorporate parametric, non-parametric and semi-parametric statistical models. Kernel methods are seeing more flexible, and easier to interpret than neural networks. Kernel met...

MAIZE2 DATA SET.rar

Jul 18, 2019 - Deep kernel of genomic and near infrared predictions in multi-environment breeding trials

RAR Archive - 5.6 MB -

MAIZE3 DATA SET.rar

Jul 18, 2019 - Deep kernel of genomic and near infrared predictions in multi-environment breeding trials

RAR Archive - 13.4 MB -

WHEAT1 DATA SET.rar

Jul 18, 2019 - Deep kernel of genomic and near infrared predictions in multi-environment breeding trials

RAR Archive - 280.2 KB -

WHEAT4 DATA SET.rar

Jul 18, 2019 - Deep kernel of genomic and near infrared predictions in multi-environment breeding trials

RAR Archive - 6.0 MB -

Replication Data for: Joint use of genome, pedigree and their interaction with environment for predicting the performance of wheat lines in new environments

Jul 12, 2019 - CIMMYT Research Data

Howard, Reka; Gianola, Daniel; Montesinos-López, Osval A.; Juliana, Philomin; Singh, Ravi; Poland, Jesse; Shrestha, Sandesh; Pérez-Rodríguez, Paulino; Crossa, Jose; Jarquín, Diego, 2019, "Replication Data for: Joint use of genome, pedigree and their interaction with environment for predicting the performance of wheat lines in new environments", https://hdl.handle.net/11529/10548169, CIMMYT Research Data & Software Repository Network, V3

In this study, we evaluated genome-based prediction using 35,403 wheat lines from the Global Wheat Breeding Program of the International Maize and Wheat Improvement Center (CIMMYT). We implemented eight statistical models that included genome-wide molecular marker and pedigree in...

SUPPLEMENTARY MATERIAL.docx

Jul 12, 2019 - Replication Data for: Joint use of genome, pedigree and their interaction with environment for predicting the performance of wheat lines in new environments

MS Word - 555.5 KB -

Supplementary materials including figures S1 and S2

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