CIMMYT institutional network of scientific datasets and software repositories.
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4,911 to 4,920 of 13,434 Results
EYTBW-DRM-Y20-21_2.csv.gz
Nov 16, 2021 - Phenotypic data from trials conducted by the CIMMYT Bread Wheat Breeding Program
Gzip Archive - 58.0 KB - MD5: ce696cc4846a3840ec4d212106ed3cda
DataPhenotypic data
EYTBW-EHT-Y20-21_2.csv.gz
Nov 16, 2021 - Phenotypic data from trials conducted by the CIMMYT Bread Wheat Breeding Program
Gzip Archive - 58.0 KB - MD5: ab5b02763fc9544de4ae8640c9a69a63
DataPhenotypic data
EYTBW-F5I-1-Y20-21_2.csv.gz
Nov 16, 2021 - Phenotypic data from trials conducted by the CIMMYT Bread Wheat Breeding Program
Gzip Archive - 58.6 KB - MD5: e887fe89ac04946ab04326861b4992bf
DataPhenotypic data
YTBW-B5I-Y20-21_2.csv.gz
Nov 16, 2021 - Phenotypic data from trials conducted by the CIMMYT Bread Wheat Breeding Program
Gzip Archive - 337.6 KB - MD5: 6576244db4a56961c3f7b9c7036f207b
DataPhenotypic data
54IBWSN, 39SAWSN, and 32HRWSN - Gene-based marker data for marker-assisted selection
Nov 16, 2021 - CIMMYT Research Data
Dreisigacker, Susanne, 2021, "54IBWSN, 39SAWSN, and 32HRWSN - Gene-based marker data for marker-assisted selection", https://hdl.handle.net/11529/10548630, CIMMYT Research Data & Software Repository Network, V1
Gene-based marker data from international screening nurseries for marker-assisted selection.
54IBWSN_39SAWYSN_32HRWSN_Results.xlsx.gz
Nov 16, 2021 - 54IBWSN, 39SAWSN, and 32HRWSN - Gene-based marker data for marker-assisted selection
Gzip Archive - 407.3 KB - MD5: bc0bf182b57bdcf91b47541a5b96550e
Replication Data for: Bayesian multi-trait kernel methods improve multi-environment genome based prediction
Nov 15, 2021 - CIMMYT Research Data
Montesinos-López, Osval A.; Montesinos-López, José Cricelio; Montesinos-López, Abelardo; Ramírez-Alcaraz, Juan Manuel; Poland, Jesse; Singh, Ravi; Dreisigacker, Susanne; Crespo Herrera, Leonardo Abdiel; Govindan, Velu; Juliana, Philomin; Huerta Espino, Julio; Shrestha, Sandesh; Varshney, Rajeev K.; Crossa, Jose, 2021, "Replication Data for: Bayesian multi-trait kernel methods improve multi-environment genome based prediction", https://hdl.handle.net/11529/10548629, CIMMYT Research Data & Software Repository Network, V1
When multi-trait data are available and the degree of correlation between phenotypic traits is moderate or large, genomic prediction accuracy can increase when models are used that account for correlations between the phenotypic traits. The data files associated with this dataset...
Data_EYT_Data Set_1.RData.gz
Nov 15, 2021 - Replication Data for: Bayesian multi-trait kernel methods improve multi-environment genome based prediction
Gzip Archive - 4.3 MB - MD5: ae3768523cdc277e0b047178e5748cc7
Data_EYT_Data Set_2.RData.gz
Nov 15, 2021 - Replication Data for: Bayesian multi-trait kernel methods improve multi-environment genome based prediction
Gzip Archive - 4.4 MB - MD5: b360ade23a88d210d668e4ef99ef569d
Data_EYT_Data Set_3.RData.gz
Nov 15, 2021 - Replication Data for: Bayesian multi-trait kernel methods improve multi-environment genome based prediction
Gzip Archive - 6.8 MB - MD5: f66ad2e32d28013e550f1dbb9e63a6e2
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