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Journal ArticleDOI

The measurement and interpretation of genotype-environment interactions

R. Knight
- 01 May 1970 - 
- Vol. 19, Iss: 2, pp 225-235
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TLDR
The regression analysis developed by Finlay and Wilkinson to investigate genotype-environment interactions and to assess genotypes for their adaptation to a range of environments is reviewed and conclusions were extended to consider variation in several environmental factors.
Abstract
The regression analysis developed by Finlay and Wilkinson to investigate genotype-environment interactions and to assess genotypes for their adaptation to a range of environments is reviewed. Their analysis used the mean yield of many genotypes to provide a measure of the environment; it was not measured in physical terms. To reveal aspects of their analysis it was applied to data of the response of genotypes to variation in a single precisely measured environmental factor. The conclusions were extended to consider variation in several environmental factors. The effects on the regression statistics that occur with different samples of genotypes, sub- and super-optimal environmental conditions, differences in periods of growth, changes in the scale of measurement and the occurrence of several stress factors are outlined. The study byBreese (1969) of genotype-environment interaction inDactylis glomerata is considered against a background of these effects.

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Citations
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Journal ArticleDOI

Stability Analysis in Plant Breeding

TL;DR: Article de synthese sur les methodes d'analyse de la stabilite de caracteres genetiques, notamment le rendement en amelioration des plantes.
Journal ArticleDOI

Model selection and validation for yield trials with interaction

Hugh G. Gauch
- 10 Jul 1988 - 
TL;DR: AMMI analysis of yield trial data is a useful extension of the more familiar ANOVA, PCA, and linear regression procedures, particularly given a large genotype-by-environment interaction.
Book ChapterDOI

Statistical analyses of multilocation trials

TL;DR: This chapter presents the statistical analysis of multilocation trials, which implies that a number of genotypes respond to certain environments in a systematic, significant, and interpretable manner, whereas noise suggests that the responses are unpredictable and uninterpretable.
Journal ArticleDOI

The analysis of crop cultivar breeding and evaluation trials: an overview of current mixed model approaches

TL;DR: The most common mixed model approaches for series of variety trials are mixed model versions of the methods summarized by Kempton (1984) as mentioned in this paper, and a general formulation that encompasses all of these methods is described, then individual methods are considered in detail.
Journal ArticleDOI

Phenotypic plasticity as a component of evolutionary change.

TL;DR: It is now clear that genotypes that perform best in one environment usually perform less well than other genotypes in a different environment; hence, their greater response is not an adaptation to environmental variation.
References
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Journal ArticleDOI

Stability Parameters for Comparing Varieties

S. A. Eberhart, +1 more
- 01 Jan 1966 - 
TL;DR: The model, Yij = μ1 + β1Ij + δij, defines stability parameters that may be used to describe the performance of a variety over a series of environments to see whether genetic differences could be detected.
Journal ArticleDOI

The analysis of adaptation in a plant-breeding programme

TL;DR: Varieties from particular geographic regions of the world showed a similarity in type of adaptation, which provides a useful basis for plant introduction and breeding.
Journal ArticleDOI

The analysis of groups of experiments

TL;DR: It is pointed out that the ordinary analysis of variance procedure suitable for dealing with the results of a single experiment may require modification, owing to lack of equality in the errors of the different experiments, and owing to non-homogeneity of the components of the interaction of treatments with places and times.
Journal ArticleDOI

Environmental and genotype-environmental components of variability. 3. Multiple lines and crosses.

TL;DR: Environmental and genotype-environmental components of variability III: multiple lines and crosses.