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dBASE Table for ESRI Shapefile - 426.2 KB -
MD5: f1e52250f63299c0c1f2e9a4995598ca
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ESRI Shapefile - 403 B -
MD5: 4c991c1c8821aa7684ad21a34d769c8c
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ESRI Spatial Index - 61.1 KB -
MD5: 988df612b365503f528c9d0adff8b6e8
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ESRI Spatial Index - 5.2 KB -
MD5: c0b11abbbd02339e0772579ce6ac7647
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Shape - 968.7 KB -
MD5: 1d36dd064e6785667aca7fba2043e9e0
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XML - 27.5 KB -
MD5: 9e6a2cf57e5b708cbca844bb375fa948
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Shape - 48.1 KB -
MD5: aa24a6cb0379022d0d108bd8c776453f
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Dec 3, 2021
Lopez-Cruz, Marco; Dreisigacker, Susanne; Crespo-Herrera, Leonardo; Bentley, Alison R.; Singh, Ravi; Mondal, Suchismita; Perez-Rodriguez, Paulino; Crossa, Jose, 2021, "Replication Data for: Sparse kernel models provide optimization of training set design for genome-based prediction in multi-year wheat breeding data", https://hdl.handle.net/11529/10548635, CIMMYT Research Data & Software Repository Network, V1
When genomic selection (GS) is used in breeding schemes, data from multiple generations can provide opportunities to increase sample size and thus the likelihood of extracting useful information from the training data. The Sparse Selection Index (SSI), is is a method for optimizi... |
R Data - 66.4 MB -
MD5: 550d81fe28e3f8c74e7c511eeeb5f7c8
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R Data - 204.0 KB -
MD5: 3151877174ccecf0f3fe442113c85aa2
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