CIMMYT Research Data

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

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7,831 to 7,840 of 10,508 Results

Technical Report-FAO-SIAC-Estimating CA adoption in Mexico-03Jun16 to 30....pdf Oct 8, 2018 - Evaluating Radar Satellite Based Remote Sensing for Conservation Agriculture Adoption Detection in North and Central Mexico Adobe PDF - 1.9 MB - MD5: 37f4bdf8baee6dec17d3ca1678950a9c
Supplemental Materials for The Relative Efficiency of Three Constrained Multistage Linear Phenotypic Selection Indices Oct 8, 2018 Cerón-Rojas, J.Jesús; Toledo, Fernando; Crossa, Jose, 2018, "Supplemental Materials for The Relative Efficiency of Three Constrained Multistage Linear Phenotypic Selection Indices", https://hdl.handle.net/11529/10548136, CIMMYT Research Data & Software Repository Network, V1 This dataset provides supplemental information related to an investigation of constrained multistage linear phenotypic selection indices.
Supplementary-Materials-final.docx Oct 8, 2018 - Supplemental Materials for The Relative Efficiency of Three Constrained Multistage Linear Phenotypic Selection Indices MS Word - 358.0 KB - MD5: 02e60fff9e7c5c038887aa8a2dde15c8 This file has supplementary material of the article "The Relative Efficiency of Three Constrained Multistage Linear Phenotypic Selection Indices"
Supplemental data for multi-trait, multi-environment deep learning modeling for genomic-enabled prediction of plant traits Sep 28, 2018 Montesinos-López, Osval A.; Montesinos-López, Abelardo; Crossa, Jose; Gianola, Daniel; Hernández-Suarez, Carlos Moisés; Martín-Vallejo, Javier, 2018, "Supplemental data for multi-trait, multi-environment deep learning modeling for genomic-enabled prediction of plant traits", https://hdl.handle.net/11529/10548134, CIMMYT Research Data & Software Repository Network, V1 This study provides supplemental data to support an investigation of the power of multi-trait deep learning (MTDL) models in terms of genomic-enabled prediction accuracy.
DataSets_Multi_trait.rar Sep 28, 2018 - Supplemental data for multi-trait, multi-environment deep learning modeling for genomic-enabled prediction of plant traits RAR Archive - 41.9 MB - MD5: cdd5ff94aff34916a943fe27c4bb20a6 Supporting data
Supplemental data for hybrid wheat prediction using genomic, pedigree and environmental covariables interaction models Sep 21, 2018 Basnet, Bhoja Raj; Crossa, Jose; Pérez-Rodríguez, Paulino; Manes, Yann; Singh, Ravi; Rosyara, Umesh; Camarillo-Castillo, Fatima; Murua, Mercedes, 2018, "Supplemental data for hybrid wheat prediction using genomic, pedigree and environmental covariables interaction models", https://hdl.handle.net/11529/10548129, CIMMYT Research Data & Software Repository Network, V1 Genomic prediction of hybrids unobserved in field evaluations is crucial. In this study, we used genomic G×E models for hybrid prediction, where similarity between lines was assessed by pedigree and molecular markers, and similarity between environments was accounted for by envir...
Supplemental_files.zip.gz Sep 21, 2018 - Supplemental data for hybrid wheat prediction using genomic, pedigree and environmental covariables interaction models Gzip Archive - 7.8 MB - MD5: 899ad733bc009f213bfdeed4df1cb4bd This zipped folder contains 4 supplemental files and one data dictionary to describe the variables contained in the other files.
36 ESWYT_EnvData.xls Aug 6, 2018 - 36th Elite Spring Wheat Yield Trial MS Excel Spreadsheet - 415.2 KB - MD5: e37c8ccea311bb0bf473a96840bc3378 IWIN Summarized Data Agronomic information by location
36 ESWYT_Genotypes_Data.xls Aug 6, 2018 - 36th Elite Spring Wheat Yield Trial MS Excel Spreadsheet - 4.9 KB - MD5: 85d48e9e612d0468913ea42c6984f8da IWIN Germplasm Data List of genotypes included on the nursery
36 ESWYT_GrnYld.xls Aug 6, 2018 - 36th Elite Spring Wheat Yield Trial MS Excel Spreadsheet - 755.2 KB - MD5: e9627b8bd116f1428c316c8766858c22 IWIN Analyzed data Means for Grain Yield by location

Technical Report-FAO-SIAC-Estimating CA adoption in Mexico-03Jun16 to 30....pdf

Oct 8, 2018 - Evaluating Radar Satellite Based Remote Sensing for Conservation Agriculture Adoption Detection in North and Central Mexico

Adobe PDF - 1.9 MB -

Supplemental Materials for The Relative Efficiency of Three Constrained Multistage Linear Phenotypic Selection Indices

Oct 8, 2018

Cerón-Rojas, J.Jesús; Toledo, Fernando; Crossa, Jose, 2018, "Supplemental Materials for The Relative Efficiency of Three Constrained Multistage Linear Phenotypic Selection Indices", https://hdl.handle.net/11529/10548136, CIMMYT Research Data & Software Repository Network, V1

This dataset provides supplemental information related to an investigation of constrained multistage linear phenotypic selection indices.

Supplementary-Materials-final.docx

Oct 8, 2018 - Supplemental Materials for The Relative Efficiency of Three Constrained Multistage Linear Phenotypic Selection Indices

MS Word - 358.0 KB -

This file has supplementary material of the article "The Relative Efficiency of Three Constrained Multistage Linear Phenotypic Selection Indices"

Supplemental data for multi-trait, multi-environment deep learning modeling for genomic-enabled prediction of plant traits

Sep 28, 2018

Montesinos-López, Osval A.; Montesinos-López, Abelardo; Crossa, Jose; Gianola, Daniel; Hernández-Suarez, Carlos Moisés; Martín-Vallejo, Javier, 2018, "Supplemental data for multi-trait, multi-environment deep learning modeling for genomic-enabled prediction of plant traits", https://hdl.handle.net/11529/10548134, CIMMYT Research Data & Software Repository Network, V1

This study provides supplemental data to support an investigation of the power of multi-trait deep learning (MTDL) models in terms of genomic-enabled prediction accuracy.

DataSets_Multi_trait.rar

Sep 28, 2018 - Supplemental data for multi-trait, multi-environment deep learning modeling for genomic-enabled prediction of plant traits

RAR Archive - 41.9 MB -

Supporting data

Supplemental data for hybrid wheat prediction using genomic, pedigree and environmental covariables interaction models

Sep 21, 2018

Basnet, Bhoja Raj; Crossa, Jose; Pérez-Rodríguez, Paulino; Manes, Yann; Singh, Ravi; Rosyara, Umesh; Camarillo-Castillo, Fatima; Murua, Mercedes, 2018, "Supplemental data for hybrid wheat prediction using genomic, pedigree and environmental covariables interaction models", https://hdl.handle.net/11529/10548129, CIMMYT Research Data & Software Repository Network, V1

Genomic prediction of hybrids unobserved in field evaluations is crucial. In this study, we used genomic G×E models for hybrid prediction, where similarity between lines was assessed by pedigree and molecular markers, and similarity between environments was accounted for by envir...

Supplemental_files.zip.gz

Sep 21, 2018 - Supplemental data for hybrid wheat prediction using genomic, pedigree and environmental covariables interaction models

Gzip Archive - 7.8 MB -

This zipped folder contains 4 supplemental files and one data dictionary to describe the variables contained in the other files.

36 ESWYT_EnvData.xls

Aug 6, 2018 - 36th Elite Spring Wheat Yield Trial

MS Excel Spreadsheet - 415.2 KB -

IWIN Summarized Data

Agronomic information by location

36 ESWYT_Genotypes_Data.xls

Aug 6, 2018 - 36th Elite Spring Wheat Yield Trial

MS Excel Spreadsheet - 4.9 KB -

IWIN Germplasm Data

List of genotypes included on the nursery

36 ESWYT_GrnYld.xls

Aug 6, 2018 - 36th Elite Spring Wheat Yield Trial

MS Excel Spreadsheet - 755.2 KB -

IWIN Analyzed data

Means for Grain Yield by location

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