Factor-Analytic Variance-Covariance Structures for Prediction Into a Target Population of Environments.
Biom J
; 66(6): e202400008, 2024 Sep.
Article
em En
| MEDLINE
| ID: mdl-39049627
ABSTRACT
Finlay-Wilkinson regression is a popular method for modeling genotype-environment interaction in plant breeding and crop variety testing. When environment is a random factor, this model may be cast as a factor-analytic variance-covariance structure, implying a regression on random latent environmental variables. This paper reviews such models with a focus on their use in the analysis of multi-environment trials for the purpose of making predictions in a target population of environments. We investigate the implication of random versus fixed effects assumptions, starting from basic analysis-of-variance models, then moving on to factor-analytic models and considering the transition to models involving observable environmental covariates, which promise to provide more accurate and targeted predictions than models with latent environmental variables.
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Bases de dados:
MEDLINE
Assunto principal:
Biometria
Idioma:
En
Revista:
Biom J
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
Alemanha