CIMMYT Research Data

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

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8,501 to 8,510 of 10,528 Results

DATASET1to3.Maize.rdata Mar 9, 2017 - A variational Bayes genomic-enabled prediction model with genotype × environment interaction Unknown - 376.8 KB - MD5: 0b0889757980aefa3f3bae20d3ecc318 Phenotypic Data Maize data
DATASET4to5.Wheat.rdata Mar 9, 2017 - A variational Bayes genomic-enabled prediction model with genotype × environment interaction Unknown - 459.3 KB - MD5: c59905b897fe95f9d600f78cd42b4fba Phenotypic Data Wheat data
DATASET6.Wheat_Yield1.rdata Mar 9, 2017 - A variational Bayes genomic-enabled prediction model with genotype × environment interaction Unknown - 5.2 MB - MD5: 4a3ec390c48988b3203c50904a8b78da Phenotypic Data Wheat yield data
KDSmart: Training Materials and Sample Files Mar 2, 2017 Hearne, Sarah; Molnar, Terence; Garay, Carlos; Dreher, Kate; Ayala, Claudio, 2016, "KDSmart: Training Materials and Sample Files", https://hdl.handle.net/11529/10669, CIMMYT Research Data & Software Repository Network, V4 KDSmart is an app that can be used for data collection on any Android-based tablet or smartphone. It has many helpful features for capturing data in field and lab settings. This study contains documents and presentations that describe how KDSmart can be used and includes example...
Genomic-enabled prediction in maize using kernel models with genotype × environment interaction Feb 16, 2017 Bandeira e Sousa, Massaine; Cuevas, Jaime; Oliveira Couto, Evellyn Giselly de; Pérez-Rodríguez, Paulino; Jarquín, Diego; Fritsche-Neto, Roberto; Burgueño, Juan; Crossa, Jose, 2017, "Genomic-enabled prediction in maize using kernel models with genotype × environment interaction", https://hdl.handle.net/11529/10887, CIMMYT Research Data & Software Repository Network, V1 ^^
HELdataset.zip Feb 16, 2017 - Genomic-enabled prediction in maize using kernel models with genotype × environment interaction Unknown - 3.2 MB - MD5: 5ec14850d84981924150ab72a73ffd3b Phenotypic Data HEL dataset
USPdataset.zip Feb 16, 2017 - Genomic-enabled prediction in maize using kernel models with genotype × environment interaction Unknown - 8.3 MB - MD5: ea15b012992ef6cfd169e4c2595d2c2b Phenotypic Data UPS dataset
HTMA MPS2 Cycle 2 genotyping for GEBV estimation Feb 6, 2017 Nair, Sudha; Babu, Raman; Zaidi, Pervez; Vinayan, Madhumal Thayil, 2017, "HTMA MPS2 Cycle 2 genotyping for GEBV estimation", https://hdl.handle.net/11529/10752, CIMMYT Research Data & Software Repository Network, V1 Cycle 2 formed by inter mating selected Cycle1 genotypes genotyped with 93 SNPs for GEBV estimation for grain yield
903.600_Pedigree.csv Feb 6, 2017 - HTMA MPS2 Cycle 2 genotyping for GEBV estimation Plain Text - 18.6 KB - MD5: 49a41332d846820f83685010727d4660 Sample pedigree
903.600_Sample details.csv Feb 6, 2017 - HTMA MPS2 Cycle 2 genotyping for GEBV estimation Plain Text - 11.9 KB - MD5: 9927ee236a3be4a4f82ea79ff774cad2 Samples in LGC template

DATASET1to3.Maize.rdata

Mar 9, 2017 - A variational Bayes genomic-enabled prediction model with genotype × environment interaction

Unknown - 376.8 KB -

Phenotypic Data

Maize data

DATASET4to5.Wheat.rdata

Mar 9, 2017 - A variational Bayes genomic-enabled prediction model with genotype × environment interaction

Unknown - 459.3 KB -

Phenotypic Data

Wheat data

DATASET6.Wheat_Yield1.rdata

Mar 9, 2017 - A variational Bayes genomic-enabled prediction model with genotype × environment interaction

Unknown - 5.2 MB -

Phenotypic Data

Wheat yield data

KDSmart: Training Materials and Sample Files

Mar 2, 2017

Hearne, Sarah; Molnar, Terence; Garay, Carlos; Dreher, Kate; Ayala, Claudio, 2016, "KDSmart: Training Materials and Sample Files", https://hdl.handle.net/11529/10669, CIMMYT Research Data & Software Repository Network, V4

KDSmart is an app that can be used for data collection on any Android-based tablet or smartphone. It has many helpful features for capturing data in field and lab settings. This study contains documents and presentations that describe how KDSmart can be used and includes example...

Genomic-enabled prediction in maize using kernel models with genotype × environment interaction

Feb 16, 2017

Bandeira e Sousa, Massaine; Cuevas, Jaime; Oliveira Couto, Evellyn Giselly de; Pérez-Rodríguez, Paulino; Jarquín, Diego; Fritsche-Neto, Roberto; Burgueño, Juan; Crossa, Jose, 2017, "Genomic-enabled prediction in maize using kernel models with genotype × environment interaction", https://hdl.handle.net/11529/10887, CIMMYT Research Data & Software Repository Network, V1

HELdataset.zip

Feb 16, 2017 - Genomic-enabled prediction in maize using kernel models with genotype × environment interaction

Unknown - 3.2 MB -

Phenotypic Data

HEL dataset

USPdataset.zip

Feb 16, 2017 - Genomic-enabled prediction in maize using kernel models with genotype × environment interaction

Unknown - 8.3 MB -

Phenotypic Data

UPS dataset

HTMA MPS2 Cycle 2 genotyping for GEBV estimation

Feb 6, 2017

Nair, Sudha; Babu, Raman; Zaidi, Pervez; Vinayan, Madhumal Thayil, 2017, "HTMA MPS2 Cycle 2 genotyping for GEBV estimation", https://hdl.handle.net/11529/10752, CIMMYT Research Data & Software Repository Network, V1

Cycle 2 formed by inter mating selected Cycle1 genotypes genotyped with 93 SNPs for GEBV estimation for grain yield

903.600_Pedigree.csv

Feb 6, 2017 - HTMA MPS2 Cycle 2 genotyping for GEBV estimation

Plain Text - 18.6 KB -

Sample pedigree

903.600_Sample details.csv

Feb 6, 2017 - HTMA MPS2 Cycle 2 genotyping for GEBV estimation

Plain Text - 11.9 KB -

Samples in LGC template

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