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  • Coefficient of concordance  (1)
  • Phenotypic yield stability  (1)
  • Springer  (2)
  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Theoretical and applied genetics 70 (1985), S. 383-389 
    ISSN: 1432-2242
    Keywords: Mixtures ; Number of components ; Phenotypic yield stability ; Stability parameter: variance
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Summary Theoretical studies on the optimal numbers of components in mixtures (for example multiclonal varieties or mixtures of lines) have been performed according to phenotypic yield stability (measured by the parameter ‘variance’). For each component i, i = 1, 2,..., n, a parameter ui with 0 ≦ ui ≦ 1 has been introduced reflecting the different survival and yielding ability of the components. For the stochastic analysis the mean of each ui is denoted by u 1 and its variance by σ i 2 For the character ‘total yield’ the phenotypic variance V can be explicitly expressed dependent on 1) the number n of components in the mixture, 2) the mean $$\overline {\sigma ^2 } $$ of the σ i 2 3) the variance of the σ i 2 4) the ratio $${{\overline {\sigma ^2 } } \mathord{\left/ {\vphantom {{\overline {\sigma ^2 } } {\lambda ^2 }}} \right. \kern-\nulldelimiterspace} {\lambda ^2 }}$$ and 5) the ratio σ i 2 /χ2 where χ denotes the mean of the u i and σ u 2 is the variance of the u j. According to the dependence of the phenotypic stability on these factors some conclusions can be easily derived from this V-formula. Furthermore, two different approaches for a calculation of necessary or optimal numbers of components using the phenotypic variance V are discussed: A. Determination of ‘optimal’ numbers in the sense that a continued increase of the number of components brings about no further significant effect according to stability. B. A reduction of b % of the number of components but nevertheless an unchanged stability can be realized by an increase of the mean χ of the u i by 1% (with $$\overline {\sigma ^2 } $$ and σ u 2 assumed to be unchanged). Numerical results on n (from A) and 1 (from B) are given. Computing the coefficient of variation v for the character ‘total yield’ and solving for the number n of components one obtains an explicit expression for n dependent on v and the factors 2.-5. mentioned above. In the special case of equal variances, σ i 2 = σ o 2 for each i, the number n depends on v, x = (σ0/χ)2 and y = (σu/χ)2. Detailed numerical results for n = n (v, x, y) are given. For x ≦ 1 and y ≦ 1 one obtains n = 9, 20 and 79 for v = 0.30, 0.20 and 0.10, respectively while for x ≦ 1 and arbitrary y-values the results are n = 11, 24 and 95.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Theoretical and applied genetics 86 (1993), S. 943-950 
    ISSN: 1432-2242
    Keywords: Two-way classification ; Rank orders ; Genotype x environment interaction ; Coefficient of concordance ; Variance components ; Agricultural crops
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract Multilocation trials in plant breeding lead to cross-classified data sets with rows=genotypes and columns=environments, where the breeder is particularly interested in the rank orders of the genotypes in the different environments. Non-identical rank orders are the result of genotype x environment interactions. Not every interaction, however, causes rank changes among the genotypes (rank-interaction). From a breeder's point of view, interaction is tolerable only as long as it does not affect the rank orders. Therefore, the question arises of under which circumstances does interaction become rank-interaction. This paper contributes to our understanding of this topic. In our study we emphasized the detection of relationships between the similarity of the rank orders (measured by Kendall's coefficient of concordance W) and the functions of the diverse variance components (genotypes, environments, interaction, error). On the basis of extensive data sets on different agricultural crops (faba bean, fodder beet, sugar beet, oats, winter rape) obtained from registration trials (1985–1989) carried out in the Federal Republic of Germany, we obtained the following as main result: W ≅ σ 2 g /(σ 2 g + σ 2 v ) where σ 2 g =genotypic variance and σ 2 v = σ 2 ge + σ 2 o /L with σ 2 ge =interaction variance, σ 2 o =error variance and L=number of replications.
    Type of Medium: Electronic Resource
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