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Environment characterisation for the interpretation of environmental effect and genotype × environment interaction

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Abstract

Increasing attention is being paid to environment characterisation as a means of identifying the environmental factors determining grain protein content (GPC) in durum wheat. New insights in crop physiology and agronomy have led to the development of crop simulation models. Those models can reconstruct plant development for past cropping seasons. One major advantage of these models is that they can also indicate the intensity of limiting factors affecting plants during particular developmental stages. The main environmental factors determining GPC in durum wheat can be investigated by introducing the intensity of limiting factors into genotype × environment (G×E) models. In our case, limiting factors corresponding to water deficit and nitrogen availability were calculated for the development period between booting and heading. These variables were then introduced into a clustering model. This model is an extension of factorial regression applied to discrete environment and genotypic variables. This procedure effectively described the environment main effect: around 30.9% of the sum of squares of the environment main effect was accounted for, using less than 33% of the degrees of freedom. It also partially accounted for G×E interaction. Our methodology, coupling the use of crop simulation and G×E analysis models, is of potential value for improving our understanding of the main development stages and identification of environmental limiting factors for the development of GPC.

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References

  • Brancourt-Hulmel M, Biarnès-Dumoulin V, Denis J-B (1997) Points de repère dans l’analyse de la stabilité et de l’interaction génotype-milieu en amélioration des plantes. Agronomie 17:219–246

    Google Scholar 

  • Brancourt-Hulmel M, Denis J-B, Lecomte C (2000) Determining environmental covariates which explain genotype environment interaction in winter wheat through probe genotypes and biadditive factorial regression. Theor Appl Genet 100:285–298

    Article  Google Scholar 

  • Brancourt-Hulmel M, Lecomte C, Denis J-B (2001) Choosing probe genotypes for the analysis of genotype-environment interaction in winter wheat trials. Theor Appl Genet 103:371–382

    Article  CAS  Google Scholar 

  • Brancourt-Hulmel M, Lecomte C (2003) Effect of environmental variates on genotype x environment interaction of winter wheat: a comparison of biadditive factorial regression to AMMI. Crop Sci 43:608–617

    Google Scholar 

  • Decoux G, Denis J-B (1991) Intera. Logiciels pour l’interprétation statistique de l’interaction entre deux facteurs. Laboratoire de biométrie, INRA, 78026 Versailles cedex

  • Denis J-B (1989) Two-way analysis using covariates. Statistics 19:123–132

    Google Scholar 

  • Denis J-B (1991) Ajustement de modèles linéaires et bilinéaires sous contraintes linéaires avec données manquantes. Rev Stat Appl 34:5–24

    Google Scholar 

  • Denis J-B, Vincourt P (1982) Panorama des méthodes statistiques d’analyse des interaction génotype X milieu. Agronomie 2(3):219–230

    Google Scholar 

  • Desclaux D (1996) De l’intérêt de génotypes révélateurs de facteurs limitants dans l’analyse des interaction génotype x milieu chez le soja (Glycine max. L. Merrill). Thèse de doctorat, Institut National Polytechnique de Toulouse

  • Finlay KW, Wilkinson GN (1963) The analysis of adaptation in plant-breeding programme. Aust J Agric Res 14:742–754

    Google Scholar 

  • Foucteau V, El Daouk M, Baril C (2001) Interpretation of genotype by environment interaction in two sunflower experimental networks. Theor Appl Genet 102:327–334

    Article  Google Scholar 

  • Gate P (1995) Ecophysiologie du blé-de la plante à la culture, techniques and Documentation. Lavoisier, Paris, p429

    Google Scholar 

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

    Google Scholar 

  • Gollob HF (1968) A statistical model which combines features of factor analytic and analysis of variance techniques. Psychometrika 3:73–116

    Google Scholar 

  • Mandel J (1969) The partitioning of interaction in analysis of variance. J Res Nat Bur Stand (US) 738(4):309–327

    Google Scholar 

  • Ottman MJ, Doerge TA, Martin EC (2000) Durum grain quality as affected by nitrogen fertilization near anthesis and irrigation during grain fill. Agron J 92:1035–1041

    CAS  Google Scholar 

  • Reynolds MP, Trethowan R, Crossa J, Vargas M, Sayre KD (2002) Physiological factors associated with genotype by environment interaction in wheat. Field Crops Res 75:139–160

    Article  Google Scholar 

  • SAS Institute (1996) SAS/STAT User’s Guide, 2nd edn. SAS Institute Inc., Cary

    Google Scholar 

  • Soltner D (2000) Les bases de la production végétale, Tome1, Le sol et son amélioration, Sciences et techniques agricoles, Saintes-Gemmes-Sur-Loire, p472

  • Strong WM (1982) Effect of late application of nitrogen on the yield and protein content of wheat. Aust J Exp Agric Anim Husb 22:54–61

    Google Scholar 

  • Vargas M, Crossa J, Eeuwijk FA van, Ramirez ME, Sayre K (1999) Using partial least squares, factorial regression, and AMMI models for interpreting genotype × environment interaction. Crop Sci 39:955–967

    Google Scholar 

  • Wuest SB, Cassman KG (1992) Fertilizer-nitrogen use efficiency of irrigates wheat: I. Uptake efficiency of preplant versus late-season application. Agron J 84:682–688

    CAS  Google Scholar 

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

    Google Scholar 

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Acknowledgements

We would like to thank Philippe Gate for his active participation and the Arvalis Institut du Végétal for providing the climatic data and software necessary for the analysis. We also thank Christelle Crespin for providing the experimental data from the CTPS network.

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Correspondence to Xavier Lacaze.

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Communicated by H.C. Becker

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Lacaze, X., Roumet, P. Environment characterisation for the interpretation of environmental effect and genotype × environment interaction. Theor Appl Genet 109, 1632–1640 (2004). https://doi.org/10.1007/s00122-004-1786-6

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  • DOI: https://doi.org/10.1007/s00122-004-1786-6

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