Evaluation of yield stability of covered oat genotypes based on the results of preliminary trials

Krzysztof Ukalski

krzysztof_ukalski@sggw.edu.pl
Katedra Ekonometrii i Statystyki, Zakład Biometrii, Szkoła Główna Gospodarstwa Wiejskiego w Warszawie (Poland)

Tadeusz Śmiałowski


Instytut Hodowli i Aklimatyzacji Roślin — PIB, Zakład Roślin Zbożowych w Krakowie (Poland)

Abstract

The analysis of yield of covered grain oat strains was described in the paper. The data came from preliminary trials performed in 2007. In total 30 covered grain oat genotypes and 2 standards were examined in 6 environments. The biplot method for GGE, AMMI, SREG i GREG models has been applied for data analysis. Genotypes with highest GGE effect (i.e. sum of main genotype effects G and genotype-environment effects GE) in each environment were indicated on the basis of biplots. Among 30 covered grain oat lines, STH 657, STH 5242, STH 123, POB 483/03, STH 289, CHD 1193/04, CHD 1601/04, CHD 1382/03, CHD 1263/04 were with the highest yield across environments. The most stable covered grain oat lines were: CHD 1382/03, CHD 1263/04, STH 5071, CHD 1430/02 and the most unstable: STH 5244 i CHD 1534/04. The biplot for GREG showed that three mega-environments concentrated the 6 environments tested in this study.


Keywords:

AMMI, GGE, GREG, SREG, genotype-environment interaction, covered grain oat, stability

Cornelius P. L., Crossa J., Seyedsadr M. S. 1996. Statistical tests and estimators of multiplicative models for genotype-by-environment interaction. In M. S. Kang and H. G. Gauch (ed.) Genotype-by-environment interaction. CRC Press, Boca Raton, FL: 199 — 234.
Google Scholar

Cornelius P. L., Seyedsadr M. S. 1997. Estimation of general linear-bilinear models for two-way tables. J. Statist. Comput. Simulation 58: 287 — 322.
Google Scholar

Crossa J., Cornelius P. L. 1997. Site regression and shifted multiplicative model clustering of cultivar trials sites under heterogeneity of error variances. Crop Sci. 37: 406 — 415.
Google Scholar

Gabriel, K. R. 1971. The biplot graphic display of matrices with application to principal component analysis. Biometrika 58: 453-467.
Google Scholar

Gauch H. G. 1992. Statistical analysis of regional yield trials: AMMI analysis of factorial designs. Elsevier, Amsterdam, The Netherlands.
Google Scholar

Gauch H. G. 2006. Statistical analysis of yield trials by AMMI and GGE. Crop Sci. 46:1488 — 1500.
Google Scholar

Gauch H. G., Piepho H. P., Annicchiarico P. 2008. Statistical analysis of yield trials by AMMI and GGE: Further considerations. Crop Sci. 48:866 — 889.
Google Scholar

Gauch G. H., Zobel R. W. 1997. Interpreting mega-environments and targeting genotypes. Crop Sci. 37, 311-326.
Google Scholar

Gollob H. F. 1968. A statistical model which combines features of factor analytic and analysis of variance. Psychometrika 33: 73 — 115.
Google Scholar

SAS Institute Inc. 2008. SAS/STAT® 9.2 User’s Guide. Cary, NC: SAS Institute Inc.
Google Scholar

Ukalski K., Śmiałowski T., Ukalska J. 2010 a. Analysis of oat yield environments using graphical GGE method. Colloquium Biometricum 40: 81 — 93.
Google Scholar

Ukalski K., Śmiałowski T., Ukalska J. 2010 b. Analiza plonowania i stabilności genotypów owsa za pomocą metody graficznej typu GGE. Żywność. Nauka, Technologia, Jakość, R. 17, 3: 127 — 140.
Google Scholar

Yan W. 2002. Singular-value partitioning in biplot analysis of multienvironment trial data. Agron. J. 94: 990 — 996.
Google Scholar

Yan W., Cornelius P.L., Crossa J., Hunt L. A. 2001. Two types of GGE biplots for analyzing multi-environment trial data. Crop Sci. 41: 656 — 663.
Google Scholar

Yan W., Hunt L.A. 2001. Interpretation of genotype × environment interaction for winter wheat yield in Ontario. Crop Sci. 41: 19 — 25.
Google Scholar

Yan W., Hunt L.A., Sheng Q., Szlavnics Z. 2000. Cultivar evaluation and mega environment investigation based on the GGE biplot. Crop Sci. 40: 597 — 605.
Google Scholar

Yan W., Kang M. S. 2003. GGE biplot analysis: a graphical tool for breeders, genetics and agronomists. CRC Press, Boca Raton, FL.
Google Scholar

Yan W., Kang M. S., Ma B., Woods S., Cornelius P. L. 2007. GGE biplot vs. AMMI analysis of genotype-by-environment data. Crop Sci. 47: 643 — 655.
Google Scholar

Yan W., Rajcan I. 2002. Biplot analysis of test sites and trait relations of soybean in Ontario. Crop Sci. 42: 11 — 20.
Google Scholar

Yan W., Tinker N. A. 2005. An integrated system of biplot analysis for displaying, interpreting, and exploring genotype-by-environment interactions. Crop Sci. 45: 1004 — 1016.
Google Scholar


Published
2012-06-28

Cited by

Ukalski, K. and Śmiałowski, T. (2012) “Evaluation of yield stability of covered oat genotypes based on the results of preliminary trials”, Bulletin of Plant Breeding and Acclimatization Institute, (264), pp. 157–167. doi: 10.37317/biul-2012-0065.

Authors

Krzysztof Ukalski 
krzysztof_ukalski@sggw.edu.pl
Katedra Ekonometrii i Statystyki, Zakład Biometrii, Szkoła Główna Gospodarstwa Wiejskiego w Warszawie Poland

Authors

Tadeusz Śmiałowski 

Instytut Hodowli i Aklimatyzacji Roślin — PIB, Zakład Roślin Zbożowych w Krakowie Poland

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Copyright (c) 2012 Krzysztof Ukalski, Tadeusz Śmiałowski

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