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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Euphytica 84 (1995), S. 1-7 
    ISSN: 1573-5060
    Keywords: AMMI ; best linear unbiassed prediction ; factorial regression ; genotype by environment interaction ; multiplicative interaction ; reduced rank regression ; two-way table ; variance components ; variety trials
    Source: Springer Online Journal Archives 1860-2000
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Notes: Summary The multi-environment trial, in which a number of genotypes is evaluated over a range of environmental conditions, is a standard experiment in plant breeding in general, and variety testing in particular. Useful statistical models for the analysis of multi-environment trials, with emphasis on the analysis of genotype by environment interaction, can be found in the classes of linear and bilinear models. Statistical properties of the most important representatives of these model classes are shortly reviewed. Structural differences between the models stem from: (1) the inclusion of random model terms in addition to fixed model terms; (2) the representation of the interaction by additive or multiplicative parameters; (3) the incorporation of concomitant variables on the levels of the environmental factor. For models with bilinear multiplicative structure for the interaction it is described how the interaction can be visualized by biplots. An illustration of the application of the models and biplots is given in a companion paper.
    Type of Medium: Electronic Resource
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  • 2
    ISSN: 1573-5060
    Keywords: AMMI ; best linear unbiassed prediction ; factorial regression ; genotype by environment interaction ; maize ; missing values ; multiplicative interaction ; reduced rank regression ; two-way table
    Source: Springer Online Journal Archives 1860-2000
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Notes: Summary As the sequel to a paper that dealt with the theoretical aspects of linear and bilinear models for the analysis of genotype by environment interaction in multi-environment trials, this paper presents an illustration of the application of these models to real life data. The data come from maize trials that were conducted within the ongoing evaluation programme for the Dutch Descriptive Variety List of Field Crops. The variable that is analyzed is dry matter content. It is shown how linear and bilinear models can be used supplementary to each other within a general strategy for dealing with genotype by environment interaction.
    Type of Medium: Electronic Resource
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