Skip to main content
Log in

Comparison of parametric and non-parametric methods for selecting stable and adapted durum wheat genotypes in variable environments

  • Published:
Euphytica Aims and scope Submit manuscript

Abstract

Twenty parametric and non-parametric measures derived from grain yield of 15 advanced durum genotypes evaluated across 12 variable environments during the 2004–2006 growing seasons were used to assess performance stability and adaptability of the genotypes and to study interrelationship among these measures. The combined ANOVA and the non-parametric tests of Genotype × environment interaction indicated the presence of significant crossover and non-crossover interactions, and of significant differences among genotypes. Principal component analysis based on the rank correlation matrix indicated that most non-parametric measures were significantly inter-correlated with parametric measures and therefore can be used as alternatives. The results also revealed that stability measures can be classified into three groups based on static and dynamic concepts of stability. The group related to the dynamic concept and strongly correlated with mean grain yield of stability included the parameters of TOP (proportion of environments in which a genotype ranked in the top third), superiority index (P i) and geometric adaptability index. The second group reflecting the concept of static stability included, Wricke’s ecovalence, the variance in regression deviation (S 2 di), AMMI stability value, the Huehn’s parameters [S (1)i , S (2)i ], Tennarasua’s parameter [NP (1)i ], Kang’s parameter (RS) and yield reliability index (I i) which were not correlated with mean grain yield. The third group influenced simultaneously by grain yield and stability included the measures S (3)i , S (6)i , NP (2)i , NP (3)i , environmental variance (S 2 xi), coefficient of variability and coefficient of regression (b i). Based on the concept of dynamic stability, genotypes G6, G4, and G3 were found to be the most adapted to favorable environments, whereas genotypes G8, G9, and G12 were more stable and are related to the concept of static stability.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig 1

Similar content being viewed by others

References

  • Allard RW, Bradshaw AD (1964) Implications of genotype environment interactions. Crop Sci 4:503–508

    Article  Google Scholar 

  • Annicchiarico P (2002) Defining adaptation strategies and yield stability targets in breeding programmes. In: Kang MS (ed) Quantitative genetics, genomics, and plant breeding. CABI, Wallingford, UK, pp. 365–383

    Google Scholar 

  • Baker RJ (1988) Test for Crossover genotype-environmental interactions. Can J Plant Sci 64:405–410

    Google Scholar 

  • Becker HC, Leon J (1988) Stability analysis in plant breeding. Plant Breed 101:1–23

    Article  Google Scholar 

  • Bredenkamp J (1974) Nonparametric prufung von wechsewirkungen. Psychol Beitr 16:398–416

    Google Scholar 

  • Calinski T (1960) On a certain statistical method of investigating interaction in serial experiments with plant varieties. Pol Acad Sci Bull (Cl II) 8:565–568

    Google Scholar 

  • De Kroon J, van der Laan P (1981) Distribution-free test procedures in two-way layouts: a Concept of rank-interaction. Stat Neeri 35:189–213

    Article  Google Scholar 

  • Eberhart SA, Russell WA (1966) Stability parameters for comparing varieties. Crop Sci 6:36–40

    Article  Google Scholar 

  • Eskridge KM (1990) Selection of stable cultivars using a safety-first rule. Crop Sci 30:369–374

    Article  Google Scholar 

  • Fox PN, Skovmand B, Thompson BK, Braun HJ, Cormier R (1990) Yield and adaptation of hexaploid spring triticale. Euphytica 47:57–64

    Article  Google Scholar 

  • Francis TR, Kannenberg LW (1978) Yield stability studied in short-season maize. I. A descriptive method for grouping genotypes. Can J Plant Sci 58:1029–1034

    Article  Google Scholar 

  • Gauch HG (1992) Statistical analysis of regional yield trials: AMMI analysis of factorial designs. Elsevier, London

    Google Scholar 

  • Gauch HG, Zobel RW (1996) AMMI analysis of yield trials. In: Kang MS, Gauch HG (eds) Genotype by environment ineraction. CRC Press. Boca Raton, FL

    Google Scholar 

  • Huehn M (1979) Beitrage zur erfassung der phanotypischen stabilitat. EDV Med. Biol 10:112–117

    Google Scholar 

  • Huehn M (1990) Non-parametric measures of phenotypic stability: part 1. Theory, Euphytica 47:189–194

    Google Scholar 

  • Huehn M (1996) Non-parametric analysis of genotype x environment interactions by ranks. In: Kang MS, Gauch HG (eds) Genotype by environment interaction. CRC Press, Boca Raton, FL, pp 213–228

    Google Scholar 

  • Huehn M, Leon J (1995) Non-parametric analysis of cultivar performance trials: experimental results and comparison of different procedures based on ranks. Agron J 87:627–632

    Article  Google Scholar 

  • Kang MS (1988) A rank-sum method for selecting high yielding stable corn genotypes. Cereal Res Commun 16:113–115

    Google Scholar 

  • Kang MS, Pham HN (1991) Simultaneous selection for high yielding and stable crop genotypes. Agron J 83:161–165

    Article  Google Scholar 

  • Kataoka S (1963) A stochastic programming model. Econometrika 31:181–196

    Article  Google Scholar 

  • Lin CS, Binns MR (1988) A method for analyzing cultivar x location x year experiments: a new stability parameter. Theor Appl Genet 76:425–430

    Article  Google Scholar 

  • Lin CS, Binns MR, Lefkovitch LP (1986) Stability analysis: where do we stand? Crop Sci 26:894–900

    Article  Google Scholar 

  • Lin CS, Butler G (1990) Cluster analyses for analyzing two-way classification data. Agron J 82:344–348

    Article  Google Scholar 

  • McKeand SE, Li B, Hatcher AV, Weir RJ (1990) Stability parameter estimates for stem volume for loblolly pine families growing in different regions in the southeastern United States. For Sci 26:10–17

    Google Scholar 

  • Mohammadi R, Abdulahi A, Haghparast R, Armion M (2007) Interpreting genotype × environment interactions for durum wheat grain yields using non-parametric methods. Euphytica 157:239–251

    Article  CAS  Google Scholar 

  • Nassar R, Huehn M (1987) Studies on estimation of phenotypic stability: tests of significance for non-parametric measures of phenotypic stability. Biometrics 43:45–53

    Article  Google Scholar 

  • Purchase JL, Hatting H, Van Deventer CS (2000) Genotype x environment interaction of winter wheat in south Africa: II. Stability analysis of yield performance. S Afr J Plant Soil 17(3):101–107

    Google Scholar 

  • Shukla GK (1972) Some aspects of partitioning genotype-environmental components of variability. Heredity 28:237–245

    Google Scholar 

  • Simmonds NW (1991) Selection for local adaptation in a plant breeding programme. Theor Appl Genet 82:363–367

    Article  Google Scholar 

  • Thennarasu K (1995) On certain non-parametric procedures for studying genotype-environment interactions and yield stability. Ph.D. thesis. PJ School, IARI, New Delhi, India

    Google Scholar 

  • Wricke G (1962) Über eine Methode zur Erfassung der ökologischen Streubreite in Feldversuchen. Z. Pflanzenzüchtg 47:92–96

    Google Scholar 

  • Yates F, Cochran WG (1938) The analysis of groups of experiments. J Agric Sci 28:556–580

    Article  Google Scholar 

  • Zobel BJ, Talbert J (1984) Applied forest tree improvement. Wiley, New York, p 505

    Google Scholar 

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

    Article  Google Scholar 

Download references

Acknowledgment

Financial support from the Agricultural Research and Education Organization (AREO) of Iran is highly acknowledged. We are also grateful to the reviewers for valuable comments and discussion relating to the manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Reza Mohammadi.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Mohammadi, R., Amri, A. Comparison of parametric and non-parametric methods for selecting stable and adapted durum wheat genotypes in variable environments. Euphytica 159, 419–432 (2008). https://doi.org/10.1007/s10681-007-9600-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10681-007-9600-6

Keywords

Navigation