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Accuracy and selection success in yield trial analyses

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Summary

Yield trials serve research purposes of estimation and selection. Order statistics are used here to quantify the successes or problems to be expected in selection tasks commonly encountered in breeding and agronomy. Greater accuracy of yield estimates implies greater selection success. A New York soybean yield trial serves as a specific example. The Additive Main effects and Multiplicative Interaction (AMMI) statistical model is used to increase the accuracy of these soybean yield estimates, thereby increasing the probability of successfully selecting, on the basis of the empirical yield data, that genotype which has the maximum true mean. The statistical strategy for increasing accuracy is extremely cost effective relative to the alternative strategy of increasing the number of replications. Better selections increase the speed and effectiveness of breeding programs, and increase the reliability of variety recommendations. Selection tasks are frequently more difficult than may be suspected.

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References

  • Acton FS (1970) Numerical methods that work. Harper and Row, New York

    Google Scholar 

  • Bradley JP, Knittle KH, Troyer AF (1988) Statistical methods in seed corn product selection. J Prod Agric 1:34–38

    Google Scholar 

  • Bradu D, Gabriel KR (1978) The biplot as a diagnostic tool for models of two-way tables. Technometrics 20:47–68

    Google Scholar 

  • Gauch HG (1987) MATMODEL. Microcomputer Power, Ithaca, New York

    Google Scholar 

  • Gauch HG (1988) Model selection and validation for yield trials with interaction. Biometrics 44:705–715

    Google Scholar 

  • Gauch HG, Zobel RW (1988) Predictive and postdictive success of statistical analyses of yield trials. Theor Appl Genet 76:1–10

    Google Scholar 

  • Gibbons JD, Olkin I, Sobel M (1977) Selecting and ordering populations: A new statistical methodology. Wiley, New York

    Google Scholar 

  • Gupta SS, Berger JO (1988a) Statistical decision theory and related topics IV, vol 1. Springer, New York Heidelberg Berlin

    Google Scholar 

  • Gupta SS, Berger JO (1988b) Statistical decision theory and related topics IV, vol 2. Springer, New York Heidelberg Berlin

    Google Scholar 

  • Gupta SS, Panchapakesan S (1979) Multiple decision procedures: Theory and methodology of selecting and ranking populations. Wiley, New York

    Google Scholar 

  • Kempton RA (1984) The use of biplots in interpreting variety by environment interactions. J Agric Sci 103:123–135

    Google Scholar 

  • Patterson HD, Silvey V, Talbot M, Weatherup STC (1977) Variability of yields of cereal varieties in UK trials. J Agric Sci 89:239–245

    Google Scholar 

  • Snedecor GW, Cochran WG (1980) Statistical methods, 7th edn. Iowa State University Press, Ames/IA

    Google Scholar 

  • Talbot M (1984) Yield variability of crop varieties in the UK. J Agric Sci 102:315–321

    Google Scholar 

  • Zobel RW, Wright MJ, Gauch HG (1988) Statistical analysis of a yield trial. Agron J 80:388–393

    Google Scholar 

Download references

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Communicated by A. R. Hallauer

This research was supported by the Rhizobotany Project of the USDA-ARS

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Gauch, H.G., Zobel, R.W. Accuracy and selection success in yield trial analyses. Theoret. Appl. Genetics 77, 473–481 (1989). https://doi.org/10.1007/BF00274266

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  • DOI: https://doi.org/10.1007/BF00274266

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