ANALISIS INTERAKSI GENOTIP x LINGKUNGAN MENGGUNAKAN STRUCTURAL EQUATION MODELING

Authors

  • I Made Sumertajaya Departemen Statistika, FMIPA Institut Pertanian Bogor
  • Ahmad Ansori Matjjik Departemen Statistika, FMIPA Institut Pertanian Bogor
  • I Gede Nyoman Mindra Jaya Jurusan Statistika, FMIPA Universitas Padjadjaran

DOI:

https://doi.org/10.21831/pg.v4i1.684

Abstract

Additive Main Effect and Multiplicative Model (AMMI Model) nowadays is used to asses in plant breeding, especially to asses the Genotype í— Environment Interaction (GEI) on multi-environment trial. The presence of genotype í— environment interaction (GEI) creates difficulties in modeling complex trait that involve sequence biological process. Coupling Structural equation modeling with AMMI was developed to analyzed genotype í— environment interaction (GEI). Structural equation modeling allows us to account for underlying sequential process in plant development by incorporating intermediate variables associated with those processes in the model. With this method we can incorporating genotypic and environmental covariate in the model and explain how those covariates influence grain yield. SEM-AMMI useful when both environments and genotype are fixed and the purpose of the multi-environment trials (MET) is to assess the combined effect genotypic and environmental covariate on yield and yield components  Keywords : AMMI Model, Structural equation modeling 

References

Aastveit H., and H. Martens. 1986. ANOVA Interactions Interpreted by Partial Least Squares Regression.Biometrics42 : 829-844

Alberts Martin J. A. 2004.A Comparison of Statistical Method To Describe Genotypeï‚´Environment Interaction and Yield Stability In Multilocation Maize Trials. Thesis.University of The Free State Bloemfontein

Arbuckle. J.L.2006. Amosâ„¢ 7.0 User's Guide, Amos Development Corporation, United States of America.

Bollen, K.A. 1989. Structural Equation With Latent Variables. New York: John Wiley and Sons.

Cambell, B. T. 2002.Quantitative Trait Loci and Environmental Interactions Associated With Agronomic Performance of Wheat.Ph.D. Dissertation. Nebraska: University of Nebraska-Lincoln.

Dhungana, P. 2004. Structural Equation Modelingof Genotype X Environment Interaction. Ph. D. Dissertation. University of Nebraska-Lincoln, Lincoln, Nebraska.

Ghozali, Imam. 2004. Model Persamaan Structural Konsep dan Aplikasi dengan Program AMOS Versi 5.0. Semarang: Badan Penerbit Universitas Diponogoro,

Gauch, H.G. JR. 1982. Noise reduction by eigenvector ordination. Ecology63:1643-1649

Gauch, H.G. JR. 1982. Model selection and validation for yield trials with interaction. Biometrics44: 705-715

Joreskog, K. G. Sorbom, D.1989. LISREL 7 : User's reference guide. Scientific Software Inc., Mooresville, IN.

Johnson, R.A.D.W. Wichern. 1996.Applied Multivariate Statistical Analysis 3rded. New Jersey: Prentice-Hall.

Mattjik, A.A.& Sumertajaya,I.M.2000. Perancangan Percobaan dengan Aplikasi SAS dan Minitab jilid 1. Bogor: IPB Press.

Tai, G.C.C. 1979. Analysis of Genotype-Environment Interactions of Potato Yield. Crop Sci. 19:434-438

______2002.Manual SEM-AMOS.

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How to Cite

Sumertajaya, I. M., Matjjik, A. A., & Mindra Jaya, I. G. N. (2012). ANALISIS INTERAKSI GENOTIP x LINGKUNGAN MENGGUNAKAN STRUCTURAL EQUATION MODELING. PYTHAGORAS Jurnal Matematika Dan Pendidikan Matematika, 4(1). https://doi.org/10.21831/pg.v4i1.684

Issue

Vol. 4 No. 1: Juni 2008

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Articles

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Based on a work at http://journal.uny.ac.id/index.php/pythagoras.