Advertisement

Springer Nature is making Coronavirus research free. View research | View latest news | Sign up for updates

Hybrid maize breeding with doubled haploids: I. One-stage versus two-stage selection for testcross performance

  • 497 Accesses

  • 28 Citations

Abstract

Optimum allocation of resources is of fundamental importance for the efficiency of breeding programs. The objectives of our study were to (1) determine the optimum allocation for the number of lines and test locations in hybrid maize breeding with doubled haploids (DHs) regarding two optimization criteria, the selection gain ΔG k and the probability P k of identifying superior genotypes, (2) compare both optimization criteria including their standard deviations (SDs), and (3) investigate the influence of production costs of DHs on the optimum allocation. For different budgets, number of finally selected lines, ratios of variance components, and production costs of DHs, the optimum allocation of test resources under one- and two-stage selection for testcross performance with a given tester was determined by using Monte Carlo simulations. In one-stage selection, lines are tested in field trials in a single year. In two-stage selection, optimum allocation of resources involves evaluation of (1) a large number of lines in a small number of test locations in the first year and (2) a small number of the selected superior lines in a large number of test locations in the second year, thereby maximizing both optimization criteria. Furthermore, to have a realistic chance of identifying a superior genotype, the probability P k of identifying superior genotypes should be greater than 75%. For budgets between 200 and 5,000 field plot equivalents, P k > 75% was reached only for genotypes belonging to the best 5% of the population. As the optimum allocation for P k (5%) was similar to that for ΔG k , the choice of the optimization criterion was not crucial. The production costs of DHs had only a minor effect on the optimum number of locations and on values of the optimization criteria.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3

References

  1. Becker H (1993) Pflanzenzüchtung (in German). Verlag Eugen Ulmer, Stuttgart, pp 129–132

  2. Bernardo R (2002) Breeding for quantitative traits in plants. Stemma Press, Woodbury, p 205

  3. Berry DA, Lindgren BW (1996) Statistics. Duxbury Press, New York, p 371

  4. Bordes J, de Vaulx RD, Lapierre A, Pollacsek M (1997) Haplodiploidization of maize (Zea mays L.) through induced gynogenesis assisted by glossy markers and its use in breeding. Agronomie 17:291–297

  5. Choo TM, Kannenberg LW (1988) Selection response and efficiency of doubled-haploid recurrent selection in a cross-fertilized species. Theor Appl Genet 75:410–414

  6. Cochran WG (1951) Improvement by means of selection. In: Proc second Berkeley symp math stat prob, pp 449–470

  7. Finney DJ (1966) An experimental study of certain screening processes. J Roy Stat Soc B 28:88–109

  8. Gallais A (1991) A general approach for the study of a population of test-cross progenies and consequences for the recurrent selection. Theor Appl Genet 81:493–503

  9. Gordillo GA, Geiger HH (2004) Estimating quantitative-genetic parameters of European maize populations to optimize hybrid breeding methods by model calculations. In: Poster abstract XVIIth EUCARPIA general congress 2004, Tulln, Austria

  10. Grüneberg WJ, Abidin E, Ndolo P, Pereira CA, Hermann M (2004) Variance component estimations and allocation of resources for breeding sweetpotato under East African conditions. Plant Breed 123:311–315

  11. Hanson WD, Brim CA (1963) Optimum allocation of test material for two-stage testing with an application to evaluation of soybean lines. Crop Sci 3:43–49

  12. Johnson B (1989) The probability of selecting genetically superior S2 lines from a maize population. Maydica 34:5–14

  13. Keuls M, Sieben JW (1955) Two statistical problems in plant selection. Euphytica 4:34–44

  14. Knapp SJ (1998) Marker-assisted selection as a strategy for increasing the probability of selecting superior genotypes. Crop Sci 38:1164–1174

  15. Mihaljevic R, Utz HF, Melchinger AE (2004) Congruency of quantitative trait loci detected for agronomic traits in testcrosses of five populations of european maize. Crop Sci 44:114–124

  16. Pearson ES, Hartley HO (1972) Biometrika tables for statisticians, 2nd edn. Cambridge University Press, London

  17. R Development Core Team (2004) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-00-3, URL http://www.R-project.org

  18. Röber FK (1999) Fortpflanzungsbiologische und genetische Untersuchungen mit RFLP-Markern zur in-vivo Haploideninduktion bei Mais. (in German). Ph.D. thesis, University of Hohenheim, Stuttgart, Germany

  19. Robson DS, Powers L, Urquhart NS (1967) The proportion of genetic deviates in the tails of a normal population. Theor Appl Genet 37:205–216

  20. Schmidt W (2004) Hybridmaiszüchtung bei der KWS SAAT AG (in German). In: Bericht über die 54. Tagung der Vereinigung der Pflanzenzüchter und Saatgutkaufleute Österreichs 2003, Gumpenstein, Austria, pp 1–6

  21. Schön CC, Utz HF, Groh S, Truberg B, Openshaw S, Melchinger AE (2004) Quantitative trait locus mapping based on resampling in a vast maize testcross experiment and its relevance to quantitative genetics for complex traits. Genetics 167:485–498

  22. Seitz G (2005) The use of doubled haploids in corn breeding. In: Proceedings of the forty first annual Illinois Corn Breeders’ School 2005, Urbana—Champaign, Illinois, USA, pp 1–8

  23. Sprague GF, Federer WT (1951) A comparison of variance components in corn yield trials: II. Error, year × variety, location × variety and variety components. Agron J 42:535–541

  24. Tomerius AM (2001) Optimizing the development of seed-parent lines in hybrid rye breeding. Ph.D. thesis, University of Hohenheim, Stuttgart, Germany (http://opus-ho.uni-stuttgart.de/hop/volltexte/2001/10/pdf/tomerius.pdf)

  25. Utz HF (1969) Mehrstufenselektion in der Pflanzenzüchtung (in German). Arbeiten der Universität Hohenheim, vol 49. Verlag Eugen Ulmer, Stuttgart, Germany

  26. Young JC (1976) Varietal screening from finite normal populations. J Am Stat Assoc 71:87–92

Download references

Acknowledgements

This research was supported by funds from DFG, Grant No 1070/1, International Research Training Group “Sustainable Resource Use in North China” to C. F. H. Longin. The authors appreciate the editorial work of Dr. J. Muminović whose suggestions considerably improved the style of the manuscript. In addition, the authors thank Dr. F. Laidig, Bundessortenamt Hannover, Germany, and Dr. G. Seitz, AgReliant Genetics, Westfield, IN, USA for their valuable suggestions. We greatly appreciate the helpful comments and suggestions of two anonymous reviewers.

Author information

Correspondence to Albrecht E. Melchinger.

Additional information

C. Friedrich H. Longin and H. Friedrich Utz contributed equally to this work.

Communicated by H. Becker

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Longin, C.F.H., Utz, H.F., Reif, J.C. et al. Hybrid maize breeding with doubled haploids: I. One-stage versus two-stage selection for testcross performance. Theor Appl Genet 112, 903–912 (2006). https://doi.org/10.1007/s00122-005-0192-z

Download citation

Keywords

  • Optimum allocation
  • Selection gain
  • Probability
  • Superior genotype
  • Monte Carlo simulation