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The expected efficiencies of half-sib, testcross and S1 progeny testing methods in single population improvement
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  • Original Article
  • Published: 01 December 1980

The expected efficiencies of half-sib, testcross and S1 progeny testing methods in single population improvement

  • A J Wright1 

Heredity volume 45, pages 361–376 (1980)Cite this article

  • 2441 Accesses

  • 14 Citations

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Summary

Expressions are given for the expected rate of response to selection using half-sib, S1 or testcross progeny tests for biallelic loci with arbitrary dominance and epistatic properties. It is shown that the value of a tester is not necessarily expected to be a simple function of either its phenotype or of the number of recessive alleles it carries, and that neither downward selection nor inbreeding are expected to be consistently successful in isolating superior testers. Calculation of expected annual responses to selection under a variety of genetic models shows that, while mass selection is the most efficient method at high heritabilities, S1 testing is expected to be the best method for low heritabilities when replicated block trials are used. Conventional half-sib testing may have an advantage with complete randomisation of large families, especially for genetic models involving overdominance, deleterious recessives or epistasis in biennial or perennial crops. The use of the lowest homozygote tester was inferior to S1 testing for all models including simple directional dominance. Assumptions of low environmental homoeostasis of S1 material did not alter the general conclusions.

Monte Carlo simulations of breeding procedures confirmed the overall superiority of S1 testing in terms of response per cycle, and a system of mass selection followed by S1 testing gave a higher average response per year than did either mass selection or S1 testing alone.

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References

  • Allison, J C S, and Curnow, R N. 1966. On the choice of tester parent for the breeding of synthetic varieties of maize. Crop Sci, 6, 541–544.

    Article  Google Scholar 

  • Carangal, V R, Ali, S M, Koble, A F, Rinke, E H, and Sentz, J C. 1971. Comparison of S1 with testcross evaluation for recurrent selection in maize. Crop Sci, 11, 658–661.

    Article  Google Scholar 

  • Choo, T M, and Kannenberg, L W. 1979a. Relative efficiencies of population improvement methods in corn: a simulation study. Crop Sci, 19, 179–185.

    Article  Google Scholar 

  • Choo, T M, and Kannenberg, L W. 1979b. Changes in gene frequency during mass, modified ear-to-row SI selection: a simulation study. Crop Sci, 19, 503–509.

    Article  Google Scholar 

  • Comstock, R E, Robinson, H F, and Harvey, P H. 1949. A breeding procedure designed to make maximum use of both general and specific combining ability. Agronomy Journal, 41, 360–367.

    Article  Google Scholar 

  • Cress, C E. 1967. Reciprocal recurrent selection and modifications in simulated populations. Crop Sci, 7, 561–567.

    Article  Google Scholar 

  • Falconer, D S. 1960. Introduction to Quantitative genetics. Oliver&Boyd, London.

    Google Scholar 

  • Genter, C F. 1973. Comparison of S1 and testcross evaluation after two cycles of recurrent selection in maize. Crop Sci, 13, 524–527.

    Article  Google Scholar 

  • Genter, C F, and Alexander, M W. 1966. Development and selection of productive S1 inbred lines of corn. Crop Sci, 6, 429–431.

    Article  Google Scholar 

  • Horner, E S, Lundy, H W, Lutrick, M C, and Wallace, R W. 1963. Relative efficiencies of recurrent selection for specific and for general combining ability in corn. Crop Sci, 3, 63–66.

    Article  Google Scholar 

  • Horner, E S, Lundy, H W, Lutrick, M C, and Chapman, W H. 1973. Comparison of three methods of recurrent selection in maize. Crop Sci, 13, 485–489.

    Article  Google Scholar 

  • Hull, F H. 1947. Cryptic homozygous lines. J Am Soc Agron, 39, 438–439.

    Article  Google Scholar 

  • Kojima, K. 1959. Role of epistasis and overdominance in stability of equilibria with selection. US National Academy of Sciences, 45, 984–989.

    Article  CAS  Google Scholar 

  • Lonnquist, J H. 1968. Further evidence on testcross versus line performance in maize. Crop Sci, 8, 50–53.

    Article  Google Scholar 

  • Lonnquist, J H, and Lindsay, M F. 1964. Topcross versus S1 line performance in corn. Crop Sci, 4, 580–584.

    Article  Google Scholar 

  • Lonnquist, H H, and Lindsay, M F. 1970. Tester performance level for the evaluation of lines for hybrid performance. Crop Sci, 10, 602–604.

    Article  Google Scholar 

  • Mather, K, and Jinks, J L. 1972. Biometrical Genetics, 2nd ed. Chapman&Hall, London.

    Google Scholar 

  • Moreno-Gonzalez, J, and Grossman, M. 1976. Theoretical modification of reciprocal recurrent selection. Genetics, 84, 95–111.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Rawlings, J O, and Thompson, D L. 1962. Performance level as a criterion for the choice of maize testers. Crop Sci, 2, 217–220.

    Article  Google Scholar 

  • Russell, W A, and Eberhart, S A. 1975. Hybrid performance of selected maize lines from reciprocal recurrent and testcross selection programmes. Crop Sci, 15, 1–4.

    Article  Google Scholar 

  • Wricke, G. 1976. Comparison of selection based on yield of half-sib progenies and of 11 lines per se in rye. Theoretical and Applied Genetics, 47, 265–269.

    Article  CAS  Google Scholar 

  • Wright, A J. 1977. Annual Report of Plant Breeding Institute, Cambridge, England.

  • Wright, A J. 1979. The use of differential coefficients in the development and interpretation of quantitative genetic models. Heredity, 43, 1–8.

    Article  Google Scholar 

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Authors and Affiliations

  1. Plant Breeding Institute, Cambridge

    A J Wright

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  1. A J Wright
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Wright, A. The expected efficiencies of half-sib, testcross and S1 progeny testing methods in single population improvement. Heredity 45, 361–376 (1980). https://doi.org/10.1038/hdy.1980.78

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  • Received: 12 May 1980

  • Issue date: 01 December 1980

  • DOI: https://doi.org/10.1038/hdy.1980.78

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