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  • Effective population size  (2)
  • Separability  (2)
  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Theoretical and applied genetics 77 (1989), S. 153-161 
    ISSN: 1432-2242
    Keywords: Seed regeneration ; Sample size ; Random genetic drift ; Effective population size ; Allele frequency
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Summary The main purpose of germplasm banks is to preserve the genetic variability existing in crop species. The effectiveness of the regeneration of collections stored in gene banks is affected by factors such as sample size, random genetic drift, and seed viability. The objective of this paper is to review probability models and population genetics theory to determine the choice of sample size used for seed regeneration. A number of conclusions can be drawn from the results. First, the size of the sample depends largely on the frequency of the least common allele or genotype. Genotypes or alleles occurring at frequencies of more than 10% can be preserved with a sample size of 40 individuals. A sample size of 100 individuals will preserve genotypes (alleles) that occur at frequencies of 5%. If the frequency of rare genotypes (alleles) drops below 5%, larger sample sizes are required. A second conclusion is that for two, three, and four alleles per locus the sample size required to include a copy of each allele depends more on the frequency of the rare allele or alleles than on the number. Samples of 300 to 400 are required to preserve alleles that are present at a frequency of 1%. Third, if seed is bulked, the expected number of parents involved in any sample drawn from the bulk will be less than the number of parents included in the bulk. Fourth, to maintain a rate of breeding (F) of 1 %, the effective population size (N e) should be at least 150 for three alleles, and 300 for four alleles. Fifth, equalizing the reproductive output of each family to two progeny doubles the effective size of the population. Based on the results presented here, a practical option is considered for regenerating maize seed in a program constrained by limited funds.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Theoretical and applied genetics 85 (1993), S. 577-586 
    ISSN: 1432-2242
    Keywords: Genotype-environment interaction ; Crossover interaction ; Separability ; Shifted multiplicative model ; Distance measure ; Cluster analysis ; Zea mays L
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Summary The shifted multiplicative model (SHMM) is used with a cluster method to identify subsets of sites in an international maize (Zea mays L.) trial without genotypic rank-change. For cluster analysis, distance between two sites is defined as the residual sum of squares after fitting SHMM with one multiplicative term (SHMM1) if SHMM1 does not show genotypic rank-change. However, if SHMM1 does show genotypic rank-change, the distance between two sites is defined as the smaller of the sums of squares owing to genotypes within each of the two sites. Calculation of distance between two sites is facilitated by using the site regression model with one multiplicative term (SREG1), which can be reparameterized as SHMM1 when only two sites are considered. The dichotomous splitting procedure, used on the dendrogram obtained from cluster analysis, will first perform SHMM analyses on each of the last two cluster groups to join (end of the dendrogram). If SHMM1 does not give an adequate fit, the next step is to move down the branches of the tree until groups of sites (clusters) are found to which SHMM1 provides an adequate fit and primary effects of sites are all of the same sign. Five final groups of sites to which SHMM1 provides an adequate fit and primary effects of sites are all of the same sign were obtained. The procedure appears to be useful in identifying subsets of sites in which genotypic rank-change interactions are negligible.
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  • 3
    Electronic Resource
    Electronic Resource
    Springer
    Theoretical and applied genetics 89 (1994), S. 936-942 
    ISSN: 1432-2242
    Keywords: Effective population size ; Variance of the number of contributed gametes ; Genetic resources preservation ; Monoecious species
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract The concept of variance effective population size [Ne(v)] and other expressions are reviewed and described for specific sampling steps in germplasm collection and regeneration of monoecious species. Special attention is given to procedures for computing the variance of the number of contributed gametes [V(k)] to the next generation. Drift, as it occurs between generations, was considered to contain a component due to the sampling of parents and a subsequent component due to the sampling of gametes. This demonstrates that drift, caused by reduction of seed viability, damages the genetic integrity of accessions stored in germplasm banks. The study shows how mating designs, such as plant-to-plant or chain crossings with additional female gametic control, can partially alleviate this problem. Optimal procedures for increasing Ne(v) when collecting germplasm in the field are also discussed. The effect of different female and male gametic control strategies on Ne(v) is considered under several situations. Practical examples illustrating the use of V(k) and Ne(v) expressions are given.
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  • 4
    Electronic Resource
    Electronic Resource
    Springer
    Theoretical and applied genetics 84 (1992), S. 161-172 
    ISSN: 1432-2242
    Keywords: Genotype x environment interaction ; Shifted multiplicative model ; Separability ; Concurrent regression model ; Crossover interaction ; Qualitative interaction
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Summary The shifted multiplicative model (SHMM) is used in an exploratory step-down method for identifying subsets of environments in which genotypic effects are “separable” from environmental effects. Subsets of environments are chosen on the basis of a SHMM analysis of the entire data set. SHMM analyses of the subsets may indicate a need for further subdivision and/or suggest that a different subdivision at the previous stage should be tried. The process continues until SHMM analysis indicates that a SHMM with only one multiplicative term and its “point of concurrence” outside (left or right) of the cluster of data points adequately fits the data in all subsets. The method is first illustrated with a simple example using a small data set from the statistical literature. Then results obtained in an international maize (Zea mays L.) yield trial with 20 sites and nine cultivars is presented and discussed.
    Type of Medium: Electronic Resource
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