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2 datasets found

• Replication Data for: A comparison between three machine learning methods for... N3 | TTL | RDF/XML | JSON-LD

  CIMMYT Ethiopia

  Genomic selection (GS) provides a new way for plant breeders select the best genotype. It draws upon historical phenotypic and genotypic information for training a statistical machine learning model which is used for predicting phenotypic (or breeding) values of new lines for which only genotypic information is available. Many statistical machine learning...

  Created January 20, 2025 • Updated January 20, 2025
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• Replication Data for: Multi-trait genome prediction of new environments with ... N3 | TTL | RDF/XML | JSON-LD

  CIMMYT Ethiopia

  The genomic selection (GS) methodology has revolutionized plant breeding. This methodology makes predictions for genotyped candidate lines based on statistical machine learning algorithms that are trained with phenotypic and genotypic data of a reference population. GS can save significant resources in the selection of candidate individuals. However,...

  Created January 20, 2025 • Updated January 20, 2025
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