A comparison of classical and machine learning-based phenotype prediction methods on simulated data and three plant species

A comparison of classical and machine learning-based phenotype prediction methods on simulated data and three plant species

Genomic selection is an integral tool for breeders to accurately select plants directly from genotype data leading to faster and more resource-efficient breeding programs. Several prediction methods have been established in the last few years. These range from classical linear mixed models to comple...

Full description

Bibliographic Details
Main Authors: Maura John, Florian Haselbeck, Rupashree Dass, Christoph Malisi, Patrizia Ricca, Christian Dreischer, Sebastian J. Schultheiss, Dominik G. Grimm
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-11-01
Series:Frontiers in Plant Science
Subjects:
phenotype prediction
genomic selection
plant phenotyping
machine learning
Arabidopsis thaliana
Online Access:https://www.frontiersin.org/articles/10.3389/fpls.2022.932512/full

Internet

https://www.frontiersin.org/articles/10.3389/fpls.2022.932512/full

Similar Items