International Journal of Innovative Approaches in Agricultural Research
Abbreviation: IJIAAR | ISSN (Online): 2602-4772 | DOI: 10.29329/ijiaar

Original article | International Journal of Innovative Approaches in Agricultural Research 2021, Vol. 5(3) 257-268

Genotypes x Environment Interaction and Stability of Bread Wheat (Triticum Aestivum L.) Cultivar Under Rainfed Conditions

İrfan Öztürk

pp. 257 - 268   |  DOI: https://doi.org/10.29329/ijiaar.2021.378.1

Published online: September 30, 2021  |   Number of Views: 5  |  Number of Download: 27


Abstract

The significant genotype (G) and environment (E) interaction and genetic diversity in the breeding programs are essential issues for the breeder to develop new cultivars. The experiment was conducted in the experimental area of Trakia Agriculture Research Institute Edirne, Turkey at eight environments from 2006-2007 to 2013-2014 growing cycles. In the study, nine released cultivars were used in randomized complete block design with four replications. Grain yield data were subjected to analysis of variance (ANOVA), the additive main effect, and multiplicative interaction (AMMI) and genotype and genotype-by-environment (GGE) biplot analyses. Stable genotypes were identified with GGE biplot and AMMI models. ANOVA and AMMI analysis revealed highly significant (p < 0.01) differences among test environments (E), genotypes (G), and their interaction (G×E). The graphical result from PCI showed that the first principal component PC1 explained 49.43% of the interaction while the second principal component, PC2 explained 29.08% of some of the square interaction. The result of PCA revealed that the 2 principal components (PC1, PC2) contributed 78.51% of the total variability. The environmental effect was responsible for the greatest part of the variation, followed by genotype and genotype by location interaction effects. Genotypes, when tested across eight environmental conditions, showed significant variation in grain yield. The highest grain yield was performed by cultivar Bereket (G8) and followed by Selimiye (G7) and Gelibolu (G4). Environment E4 and E1was found near the ideal test environment of the average environment coordination. It was determined that cultivars G7 (Selimiye) and G8 (Bereket) were well adaptable to all environmental conditions. Cultivar G4 (Gelibolu) was well adaptable to well fertile environmental conditions.

Keywords: Bread wheat, Environment, GGE Biplot, GE interaction, Yield stability


How to Cite this Article?

APA 6th edition
Ozturk, I. (2021). Genotypes x Environment Interaction and Stability of Bread Wheat (Triticum Aestivum L.) Cultivar Under Rainfed Conditions . International Journal of Innovative Approaches in Agricultural Research, 5(3), 257-268. doi: 10.29329/ijiaar.2021.378.1

Harvard
Ozturk, I. (2021). Genotypes x Environment Interaction and Stability of Bread Wheat (Triticum Aestivum L.) Cultivar Under Rainfed Conditions . International Journal of Innovative Approaches in Agricultural Research, 5(3), pp. 257-268.

Chicago 16th edition
Ozturk, Irfan (2021). "Genotypes x Environment Interaction and Stability of Bread Wheat (Triticum Aestivum L.) Cultivar Under Rainfed Conditions ". International Journal of Innovative Approaches in Agricultural Research 5 (3):257-268. doi:10.29329/ijiaar.2021.378.1.

References
  1. Cooper, M,, and Byth, D.E. (1996). Understanding plant adaptation to achieve systematic applied crop improvement: A fundamental challenge. In: Cooper, M and Hammer, GL (eds.) Plant adaptation and crop Wallingford: CABI Publishing. [Google Scholar]
  2. Eberhart, S.A., & Russell, W.A. (1966). Stability parameters for comparing varieties. Crop. Sci.6:36-40. [Google Scholar]
  3. Eberhart, S.A., & Russell, W.A. (1969). Yield stability for a 10-line diallel of single-cross and double-cross maize hybrids. Crop Sci. 9, 357-361. [Google Scholar]
  4. Finlay, K.W., & Wilkinson, G.N. (1963). The Analysis of Adaptation in a Plant Breeding Programme. Aust. J. Agric. Res., 14: 742-754. [Google Scholar]
  5. Gauch, H.G. (1992). Statistical analysis of regional yield trials: AMMI analysis of factorial designs. Elsevier, Amsterdam, Netherlans. [Google Scholar]
  6. Gauch, H.G. (2006). Statistical analysis of yield trials by AMMI and GGE. Crop Science 46, 1488-1500. doi: 10.2135/cropsci2005.07-0193 [Google Scholar] [Crossref] 
  7. Gomez, K.A., & Gomez, A.A. (1984). Statistical Procedures for Agricultural Research. 2nd Ed. John Willey and Sons, Inc. New York. 641. [Google Scholar]
  8. Kang, M.S. (1993). Simultaneous selection for yield and stability in crop performance trials: consequences for growers. Agronomy Journal 85, 754-757. [Google Scholar]
  9. Lin, C.S., Binns, M.R., and Lefkovitch, L.P. (1986). Stability analysis: where do we stand? Crop Sci. 26: 894-900. [Google Scholar]
  10. Naroui, M.R.R., Kadir, M.A., Rafii, M.Y., Hawa Jaafar, Z.E., Naghavi, M.R., and Ahmadi, F. (2013). Genotype × environment interaction by AMMI and GGE biplot analysis in three consecutive generations of wheat (Triticum aestivum) under normal and drought stress conditions. AJS 7 (7):956-961. [Google Scholar]
  11. Öztürk, İ., and Korkut, Z.K. (2018). Evaluation of Drought Tolerance Indices and Relationship with Yield in Bread Wheat Genotypes under Different Drought Stress Conditions. Journal of International Scientific Publications. Agriculture & Food. Volume 6, p: 359-367. [Google Scholar]
  12. Patel, B.C., Y.M. Rojasara., V.R. Akbari., and J.A. Patel. (2014). Stability analysis for grain yield in bread wheat (Triticum aestivum L.) for irrigated ecosystems. Journal of Wheat Research 6(2):160-162 [Google Scholar]
  13. Piepho, H.P. (1998). Methods for comparing the yield stability of cropping systems’ a review. J. of Agron. and Crop Sci. 180: 193-213. [Google Scholar]
  14. Rad, M.R., Naroui-Abdul, M., Rafii, M.Y., Jaafar, H., Naghavis, M.R., Ahmadi, F. (2013). Genotype × environment interaction by AMMI and GGE biplot analysis in three consecutive generations of wheat (Triticum aestivum L.) under normal and drought stress conditions. - Aust. J. Crop Science 7: 956-96. [Google Scholar]
  15. Sharma, R.C., Morgounov, A.I., Braun, H.J., Akin, B., Keser, M., Bedoshvili, D., Bagci, A., Martius. C., van Ginkel, M. (2010). Identifying high yielding stable winter wheat genotypes for irrigated environments in Central and West Asia. Euphytica 171: 53-64. [Google Scholar]
  16. Tai, G.C.C. (1971). Genotypic stability analysis and its application to potato regional trials. Crop Sci. 11: 184-190. [Google Scholar]
  17. Vargas, M., Crossa, J., van Eeuwijk, F.A., Ramirez, M.E., Sayre, K. (1999). Using partial least squares regression, factorial regression, and AMMI models for interpreting genotypeenvironment interaction. Crop Science 39, 955-967. [Google Scholar]
  18. Yan, W., Hunt, L.A., Sheng, Q., and Szlavnics, Z. (2000). Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Science 40(3):597-605. [Google Scholar]
  19. Yan, W., and Rajcan, I.R. (2002). Biplot analysis of test sites and trait relations of soybean in Ontario. Canadian Journal of Plant Science 42:11-20. [Google Scholar]
  20. Yan, W., and Kang, M.S. (2002). GGE Biplot Analysis: A Graphical Tool for Breeders, Geneticists, and Agronomists. New York, NY, USA: CRC Press. [Google Scholar]
  21. Yan, W., and Kang, M.S. (2003). GGE biplot analysis: a graphical tool for breeders, geneticists, and agronomists (CRC Press: Boca Raton, FL). [Google Scholar]
  22. 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: 643-653. [Google Scholar]
  23. Yan, W., and Hunt, L.A. (2001). Interpretation of genotype×environment interaction for winter wheat yield in Ontario. Crop Science 41: 19-25. [Google Scholar]
  24. Yan, W., and Tinker, N.A. (2005). An integrated biplot analysis system for displaying, interpreting, and exploring genotype×environment interaction. Crop Science 45(3):1004-1016. [Google Scholar]
  25. Yan, W., and Tinker, N.A. (2006). Biplot analysis of multi-environment trial data: Principles and applications. Can. J. Plant Sci. 86: 623-645. [Google Scholar]
  26. Zobel, R.W. (1990). A powerful statistical model for understanding genotype by environment interaction. In ‘Genotype by environment interaction and plant breeding’. (Ed.MSKang) pp. 126-140. (Louisiana State University: Baton Rouge, FL). [Google Scholar]
  27. Zobel, R.W., Wright, M.J., and Gauch, H.G. (1988). Statistical analysis of a yield trial. Agronomy Journal 80, 388-393. [Google Scholar]