Literature DB >> 1066339

The use of environmental variables in the interpretation of genotype-environment interaction.

J T Wood.   

Abstract

The method proposed by Hardwick and Wood (1972) for relating genotype-environment interactions to measures of environmental variables is extended and two examples are discussed.

Mesh：

Year:  1976        PMID： 1066339     DOI： 10.1038/hdy.1976.61

Source DB:  PubMed          Journal:  Heredity (Edinb)        ISSN： 0018-067X            Impact factor:   3.821


  7 in total

1.  Interpreting genotype-by-environment interaction using redundancy analysis.

Authors:  F A van Eeuwijk
Journal:  Theor Appl Genet       Date:  1992-10       Impact factor: 5.699

Review 2.  Genome and Environment Based Prediction Models and Methods of Complex Traits Incorporating Genotype × Environment Interaction.

Authors:  José Crossa; Osval Antonio Montesinos-López; Paulino Pérez-Rodríguez; Germano Costa-Neto; Roberto Fritsche-Neto; Rodomiro Ortiz; Johannes W R Martini; Morten Lillemo; Abelardo Montesinos-López; Diego Jarquin; Flavio Breseghello; Jaime Cuevas; Renaud Rincent
Journal:  Methods Mol Biol       Date:  2022

3.  Genotype x environment interactions in a core collection of French perennial ryegrass populations.

Authors:  G Charmet; F Balfourier; C Ravel; J B Denis
Journal:  Theor Appl Genet       Date:  1993-07       Impact factor: 5.699

4.  Association between the TIMD4-HAVCR1 variants and serum lipid levels, coronary heart disease and ischemic stroke risk and atorvastatin lipid-lowering efficacy.

Authors:  Qing-Hui Zhang; Rui-Xing Yin; Wu-Xian Chen; Xiao-Li Cao; Yu-Ming Chen
Journal:  Biosci Rep       Date:  2018-01-19       Impact factor: 3.840

5.  The effect of MVK-MMAB variants, their haplotypes and G×E interactions on serum lipid levels and the risk of coronary heart disease and ischemic stroke.

Authors:  Liu Miao; Rui-Xing Yin; Feng Huang; Wu-Xian Chen; Xiao-Li Cao; Jin-Zhen Wu
Journal:  Oncotarget       Date:  2017-08-18

6.  The Modern Plant Breeding Triangle: Optimizing the Use of Genomics, Phenomics, and Enviromics Data.

Authors:  Jose Crossa; Roberto Fritsche-Neto; Osval A Montesinos-Lopez; Germano Costa-Neto; Susanne Dreisigacker; Abelardo Montesinos-Lopez; Alison R Bentley
Journal:  Front Plant Sci       Date:  2021-04-16       Impact factor: 5.753

7.  Genomic selection using random regressions on known and latent environmental covariates.

Authors:  Daniel J Tolhurst; R Chris Gaynor; Brian Gardunia; John M Hickey; Gregor Gorjanc
Journal:  Theor Appl Genet       Date:  2022-09-06       Impact factor: 5.574
  7 in total

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