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Nonparametric phenotypic stability analysis in advanced barley (Hordeum vulgare L.) genotypes

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Abstract

The development of genotypes with adaptation to a wide range of environments is one of the most important goals of plant breeding programs. In order to compare nonparametric stability measures and to identify promising high-yield and stable barley (Hordeum vulgare L.), 20 barley genotypes selected from the Iran/ICARDA joint project and grown in nine environments during 2009-11 in Iran. Four nonparametric statistical tests of significance for genotype × environment (GE) interaction and 10 nonparametric measures of stability were used to identify stable genotypes in nine environments. Results of nonparametric tests of G×E interaction (Kubinger, Hildebrand, and Kroon/ Laan) and a combined ANOVA across environments, indicated the presence of both crossover and non-crossover interactions. Also, only TOP and rank-sum values were positively associated with high yield. Thus, in the simultaneous selection for high yield and stability, only the rank-sum and TOP methods were useful in terms of the principal component analysis results, and correlation analysis of nonparametric stability statistics and yield. According to these stability parameters (TOP and rank-sum), three genotypes (G13, G12, and G17) were the most stable for grain yield. The results also revealed that based on nonparametric test results, stability could be classified into three groups, according to agronomic and biological concepts of stability.

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References

  • Adugna W, Labuschagne M. 2003. Parametric and nonparametric measures of phenotypic stability in linseed (Linum usitatissimum L.). Euphytica 129: 211–218

    Article  CAS  Google Scholar 

  • Ahmadi A, Joudi M, Janmohammadi M. 2009. Late defoliation and wheat yield: little evidence of post-anthesis source limitation. Field Crop. Res. 113: 90–93

    Article  Google Scholar 

  • Baker R. 1990. Crossover genotype-environmental interaction in spring wheat. Genotype-by-environment interaction and plant breeding, Louisiana State University Agricultural Center. Baton Rouge, LA, pp. 42–51

    Google Scholar 

  • Bavei V, Vaezi B, Abdipour M, Jalal Kamali M, Roustaii R. 2011. Screening of tolerant spring barleys for terminal heat stress: Different importance of yield components in barleys with different row type. Int. J. Plant Breed Genet. 5(3): 175–193

    Article  CAS  Google Scholar 

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

    Article  Google Scholar 

  • Bishnoi S. 2015. Statistical models for evaluating genotype × environment interaction in wheat (Triticum aestivum L.). CCSHAU

    Google Scholar 

  • Bortz J, Lienert GA, Boehnke K. 2008. Verteilungsfreie methoden in der biostatistik. Springer-Verlag

    Google Scholar 

  • Ceccarelli S. 1994. Specific adaptation and breeding for marginal conditions, Breeding Fodder Crops for Marginal Conditions. Springer, pp 101–127

    Book  Google Scholar 

  • Comstock R, Moll RH. 1963. Genotype-environment interactions. Stat. Genet. Plant Breed. 982: 164–196

    Google Scholar 

  • FAO. 2015. Production year book. Food and Agricultural Organization

    Google Scholar 

  • Farshadfar E, Mahmudi N, Sheibanirad A. 2014. Nonparametric methods for interpreting genotype × environment interaction in bread wheat genotypes. J. Bio. Env. Sci. 4: 55–62

    Google Scholar 

  • Farshadfar E, Sabaghpour SH, Zali H. 2012. Comparison of parametric and non-parametric stability statistics for selecting stable chickpea (Cicer arietinum L.) genotypes under diverse environments. Aust. J. Crop Sci. 6(3): 514–524

    Google Scholar 

  • Flores F, Moreno M, Cubero J. 1998. A comparison of univariate and multivariate methods to analyze G× E interaction. Field Crop. Res. 56: 271–286

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Hasanuzzaman M, Shabala L, Brodribb TJ, Zhou M, Shabala S. 2017. Assessing the suitability of various screening methods as a proxy for drought tolerance in barley. Funct. Plant Biol. 44: 253–266

    Article  Google Scholar 

  • Hildebrand H. 1980. Asymptotisch verteilungsfreie Rangtests in linearen Modellen, Biometrie—heute und morgen. Springer, pp 344–349

    Google Scholar 

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

    Google Scholar 

  • Huehn M. 1990. Nonparametric measures of phenotypic stability. Part 1: Theory. Euphytica. 47: 189–194

    Google Scholar 

  • Hühn M, Léon J. 1995. Nonparametric analysis of cultivar performance trials: experimental results and comparison of different procedures based on ranks. Agron. J. 87: 627–632

    Article  Google Scholar 

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

    Google Scholar 

  • Kang MS. 1990. Genotype-by-environment interaction and plant breeding. Louisiana State University

    Google Scholar 

  • Khalili M, Pour-Aboughadareh A. 2016. Parametric and nonparametric measures for evaluating yield stability and adaptability in barley doubled haploid lines. J. Agric. Sci. and Technol. 18: 789–803

    Google Scholar 

  • Kroon JD, Laan P. 1981. Distribution-free test procedures in two-way layouts; a concept of rank-interaction. Stat. Neerl. 35: 189–213

    Article  Google Scholar 

  • Kubinger KD. 1986. A note on non-parametric tests for the interaction in two-way layouts. Biom. J. 28: 67–72

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Mekbib F. 2003. Yield stability in common bean (Phaseolus vulgaris L.) genotypes. Euphytica 130: 147–153

    Article  CAS  Google Scholar 

  • Meng Y, Ren P, Ma X, Li B, Bao Q, Zhang H, Wang J, Bai J, Wang H. 2016. GGE Biplot-based evaluation of yield performance of barley genotypes across different environments in China. J. Agr. Sci. Tech. 18: 533–543

    Google Scholar 

  • Mohammadi R. 2016. Efficiency of yield-based drought tolerance indices to identify tolerant genotypes in durum wheat. Euphytica 211: 71–89

    Article  CAS  Google Scholar 

  • Mohammadi R, Abdulahi A, Haghparast R, Aghaee M, Rostaee M. 2007a. Nonparametric methods for evaluating of winter wheat genotypes in multi-environment trials. World J. Agric. Sci. 3: 137–242

    Google Scholar 

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

    Article  CAS  Google Scholar 

  • Mohammadi R, Amri A. 2008. Comparison of parametric and non-parametric methods for selecting stable and adapted durum wheat genotypes in variable environments. Euphytica 159: 419–432

    Article  Google Scholar 

  • Mortazavian, SMM, Azizinia S. 2014. Nonparametric stability analysis in multi-environment trial of canola. Turk. J. Field Crops. 19(1): 108–117

    Article  Google Scholar 

  • Mut Z, Aydin N, Bayramoğlu HO, Özcan H. 2009. Interpreting genotype× environment interaction in bread wheat (Triticum aestivum L.) genotypes using nonparametric measures. Turk. J. Agric. For. 33: 127–137

    Google Scholar 

  • Nassar R, Huehn M. 1987. Studies on estimation of phenotypic stability: Tests of significance for nonparametric measures of phenotypic stability. Biometrics. 45–53

    Google Scholar 

  • Sabaghnia N, Dehghani H, Sabaghpour SH. 2006. Nonparametric methods for interpreting genotype× environment interaction of lentil genotypes. Crop Sci. 46: 1100–1106

    Article  Google Scholar 

  • SAS. 2010. Statistical Analysis Software. Institute Inc. and World Programming Limited, England and Wales High Court (Chancery Division)

    Google Scholar 

  • Segherloo AE, Sabaghpour SH, Dehghani H, Kamrani M. 2008. Non-parametric measures of phenotypic stability in chickpea genotypes (Cicer arietinum L.). Euphytica 162: 221–229

    Article  Google Scholar 

  • Shukla G. 1972. Some statistical aspects of partitioning genotype environmental components of variability. Heredity 29: 237–245

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  • Tiiennarasu K. 1995. On Certain Non-Parametric Procedures For Studying Genotype-Environment interactions and Yield Stability. IARI, Division of Agricultural Statistics: New Delhi

    Google Scholar 

  • Truberg B, Huehn M. 2000. Contributions to the analysis of Genotype× Environment interactions: Comparison of different parametric and nonparametric tests for interactions with emphasis on crossover interactions. J. Agron. Crop Sci. 185: 267–274

    Article  Google Scholar 

  • Verma A, Singh J, Kumar V, Kharab AS, Singh GP. 2017. Nonparametric analysis in multi environmental trials of feed barley genotypes. Int. J. Curr. Microbiol. App. Sci. 6(6): 1201–1210

    Article  Google Scholar 

  • Yan WK, Sheng QL, Hu YG. 2001. GGE biplot-an ideal tool for studying genotype by environment interaction of regional yield trial data. Acta Agron. Sin. 27: 21–28

    CAS  Google Scholar 

  • Yue G, Roozeboom K, Schapaugh W, Liang G. 1997. Evaluation of soybean cultivars using parametric and nonparametric stability estimates. Plant Breed. 116: 271–275

    Article  Google Scholar 

  • Zali H, Farshadfar E, Sabaghpour H. 2011. Non-parametric analysis of phenotypic stability in chickpea (Cicer arietinum L.) genotypes in Iran. Crop Breed. 1: 85–96

    Google Scholar 

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Correspondence to Moslem Abdipour.

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Abdipour, M., Vaezi, B., Younessi-Hamzekhanlu, M. et al. Nonparametric phenotypic stability analysis in advanced barley (Hordeum vulgare L.) genotypes. J. Crop Sci. Biotechnol. 20, 305–314 (2017). https://doi.org/10.1007/s12892-017-0050-0

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  • DOI: https://doi.org/10.1007/s12892-017-0050-0

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