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  • 1
    ISSN: 1573-5060
    Keywords: Cannabis ; cannabinoids ; evaluation ; hemp ; variation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Notes: Summary Ninety seven Cannabis accessions were evaluated for cannabinoid content and non-chemical plant characters. Variation within populations for cannabinoid content, and consistency of chemical characters at the population level were investigated. The relationship between chemical and other plant characters was very limited. Leaflet width and phenological data can be used for a rough prediction of the chemical phenotype on a population level. Various combinations of cannabinoid content and other economic plant characters were observed, thus a breeding programme will not be hampered by strict linkage. For a selection programme a direct analysis of cannabinoids will be inevitable.
    Type of Medium: Electronic Resource
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  • 2
    ISSN: 1573-5060
    Keywords: AMMI ; biadditive model ; factorial regression ; multiplicative interaction ; potato ; variety trials ; Solanum tuberosum
    Source: Springer Online Journal Archives 1860-2000
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Notes: Summary Genotype by environment interaction was investigated for yield data from the official Dutch Variety List trials for potato. The data set included 64 genotypes by 26 environments, where environments consisted of year by soil type combinations. Factorial regression models incorporating genotypic and environmental covariates in the interaction were used to analyse the data. The merits of factorial regression models were compared with those of biadditive models. Factorial regression models and biadditive models described comparable amounts of interaction, but factorial regression models provided a better basis for biological interpretation of the interaction.
    Type of Medium: Electronic Resource
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  • 3
    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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  • 4
    ISSN: 1573-5060
    Keywords: AMMI ; biadditive model ; factorial regression ; multiplicative interaction ; potato ; variety trials ; Solanum tuberosum
    Source: Springer Online Journal Archives 1860-2000
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Notes: Summary Genotype by environment interaction was investigated for yield data from the official Dutch Variety List trials for potato. The data set included 64 genotypes by 26 environments, where environments consisted of year by soil type combinations. Factorial regression models incorporating genotypic and environmental covariates in the interaction were used to analyse the data. The merits of factorial regression models were compared with those of biadditive models. Factorial regression models and biadditive models described comparable amounts of interaction, but factorial regression models provided a better basis for biological interpreration of the interaction.
    Type of Medium: Electronic Resource
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