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761 to 770 of 1,058 Results
6TH SATYN.xls.gz
May 25, 2020 - 6th Stress Adapted Trait Yield Nurseries
Gzip Archive - 68.5 KB - MD5: f8bfc2094f1631ef4e4e33ca48705b2d
IWIN Summarized Data
Means of phenotypic data values for traits
7TH SATYN-Empty FieldBook.xlsx.gz
May 25, 2020 - 7th Stress Adapted Trait Yield Nurseries
Gzip Archive - 63.5 KB - MD5: fdc698bbfc027f3eee4d09b7588d4a7f
Fieldbook
An empty Fieldbook designed for collecting trial data
7TH SATYN_EnvData.xls
May 25, 2020 - 7th Stress Adapted Trait Yield Nurseries
MS Excel Spreadsheet - 123.7 KB - MD5: d51718a8a71e0cd3bd1c961cbc69c281
IWIN Summarized Data
Agronomic information by location
7TH SATYN_Genotypes_Data.xls
May 25, 2020 - 7th Stress Adapted Trait Yield Nurseries
MS Excel Spreadsheet - 2.5 KB - MD5: a289cc1c5075a1ed6f90d013a489d6c8
IWIN Germplasm Data
List of genotypes included on the nursery
7TH SATYN_GrnYld.xls
May 25, 2020 - 7th Stress Adapted Trait Yield Nurseries
MS Excel Spreadsheet - 109.9 KB - MD5: 60936a7d39c0f2e5e8cc1fee21a1d1a5
IWIN Analyzed data
Means for Grain Yield by location
7TH SATYN_Loc_data.xls
May 25, 2020 - 7th Stress Adapted Trait Yield Nurseries
MS Excel Spreadsheet - 2.7 KB - MD5: e9ecc85829b0669985aa3187334b872a
IWIN Summarized Data
Institution, Cooperator and Location where the nurseries were evaluated
7TH SATYN_MeanVal.xls
May 25, 2020 - 7th Stress Adapted Trait Yield Nurseries
MS Excel Spreadsheet - 598.8 KB - MD5: a80d72699487eb49f2808f8c3e702677
IWIN Summarized Data
Means of phenotypic data values for traits across locations, arrangement by row
7TH SATYN_RawData.xls
May 25, 2020 - 7th Stress Adapted Trait Yield Nurseries
MS Excel Spreadsheet - 1.5 MB - MD5: 2405bfb07fbeab5d9bd36c8c8ea75011
IWIN Raw Data
Phenotypic traits raw data for all locations
Replication Data for: Approximate kernels for large data sets In genome-based prediction
May 24, 2020 - CIMMYT Research Data
Cuevas, Jaime; Montesinos-López, Osval A.; Martini, Johannes; Pérez-Rodríguez, Paulino; Lillemo, Morten; Crossa, Jose, 2020, "Replication Data for: Approximate kernels for large data sets In genome-based prediction", https://hdl.handle.net/11529/10548425, CIMMYT Research Data & Software Repository Network, V1
The rapid development of molecular markers and sequencing technologies has made it possible to use genomic selection (GS) and genomic prediction (GP) in animal and plant breeding. However, computational difficulties arise when the number of observations is large. This five datase...
Data13_14.Rdata.gz
May 24, 2020 - Replication Data for: Approximate kernels for large data sets In genome-based prediction
Gzip Archive - 19.0 MB - MD5: a4e0999fb674132112eda1b59bf88724
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