Influence of quantitative-genetic and economic parameters on the efficiency of CMS-line development in rye.

A.-M. Tomerius

Institute of Plant Breeding, Seed Science and Population Genetics (350), University of Hohenheim, 70593 Stuttgart, Germany (Germany)

H. H. Geiger

Institute of Plant Breeding, Seed Science and Population Genetics (350), University of Hohenheim, 70593 Stuttgart, Germany (Germany)

Abstrakt

Model calculations were conducted to optimize and compare alternative schemes of CMS-line development in hybrid rye breeding on the basis of their expected selection gain per year assuming a fixed annual budget. Selection gains are predicted using current estimates of the relevant quantitative-genetic and economic parameters. Two alternative schemes are dealt with here. The first scheme (STD) represents a standard procedure in present-day second-cycle breeding. The second scheme (POP) is especially suited for population material that has not undergone intense inbreeding and selection yet. We:(i) give the optimum dimensioning of the schemes and their relative efficiency, (ii) study the effect of alterations in the dominance variance, the genotype × environment-interaction variance, and the budget, and (iii) assess how deviations from the optimum dimensioning affect the selection gain.Assuming identical genotypic variances, scheme STD is clearly superior to POP. It should thus always be used for second-cycle material. If, however, the population material used with scheme POP offers larger genotypic variances than the second-cycle material, POP becomes competitive. Changes in genetic and economic parameters affect the dimensioning but not the ranking of the schemes. Deviations from the optimum dimensioning only slightly reduce the selection gain as long as they are not too severe. This is shown for suboptimum numbers of testers and locations. All in all, the results demonstrate the importance of optimizing breeding schemes with respect to genetic, technical, and economic aspects.

Słowa kluczowe:

hybrid rye breeding, line development, model calculations, optimization