Theoretical studies on the necessary number of components in mixtures |
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Authors: | M Hühn |
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Institution: | (1) Institut für Pflanzenbau und Pflanzenzüchtung, Universität Kiel, Olshausenstrasse 40, D-2300 Kiel, Federal Republic of Germany |
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Abstract: | Summary Theoretical studies on the necessary numbers of components in mixtures (for example multiclonal varieties or mixtures of lines) have been performed according to risk considerations — using the binomial distribution and the Polya-distribution. The risk r of a mixture has been defined as the probability of catastrophic losses (catastrophe = decrease of productivity of q% or more by susceptibilities of the components). Using 1) the binomial distribution and 2) its generalization, the Polya-distribution, and several simplifying assumptions, the risks r = r (x, a, q, n) have been calculated numerically (n = number of components in the mixture, a = parameter for the intensity of contagion and dispersion of susceptibilities (for example: diseases and epidemics), x = probability of susceptibility). The Polya-model reduces to the binomial case if a = 0. The main results are: 1. For each number n of components the risk r decreases markedly with decreasing x (for each q and for each a). 2. For x < = q the risk r decreases with an increasing number n of components (for each a). 3. For each number n of components and x and q with x < q the risk r increases with increasing a. 4. For given q, x and a the functions r = r(n) are asymptotic for larger numbers n of components with n > n*. In spite of further increasing numbers of components in the mixture the risk remains almost constant. For all situations, where the risk decreases with increasing n these numbers n*, therefore, can be considered as necessary numbers of components in mixtures, n* depends on q, x and a. Nevertheless, a global and rough conclusion can be formulated: In many situations one obtains necessary numbers of 30–40 components for a0 and 20–30 components for a = 0. |
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Keywords: | Mixtures Number of components Risk studies Binomial distribution Polya-distribution |
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