Study of genotype × environment interaction for grain yield of durum wheat genotypes under rainfed and supplemental irrigation conditions by GGE biplot

Document Type : Research Paper

Authors

1 Former M. Sc.Student, Dept. of Agronomy and Plant Breeding, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran

2 Research Assist. Prof., Dryland Agricultural Research Institute, Sararood Branch, Agricultural Research, Education and Extension Organization (AREEO), Kermanshah, Iran

3 Assist. Prof., Dept. of Agronomy and Plant Breeding, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran

Abstract

Determining adaptability and stability of crop varieties is one of the most important stages in plant breeding programs, which it is costly and is not easy to do due to genotype × environment (G×E) interaction effects. To study G×E interaction for grain yield in durum wheat, an experiment with 16 durum wheat genotypes was carried out in a randomized complete block design with three replications under rainfed and supplemental irrigation conditions at research field of Dryland Agricultural Research Sub-Institute (Sararood Station), Kermanshsh, Iran, during three growing seasons (2011-14). The GGE (G + G×E) biplot was applied to study G×E interaction. Combined analysis of variance showed significant differences (P<0.01) between genotypes, environments and G×E interaction effects. The G×E interaction variance was greater about two times than genotypic variance, indicating the possibility of existing environmental groups for genotype adaptation. The GGE biplot analysis indicated that the environments were classified into three mega-environments with winning genotypes. Biplot analyses identified the breeding line G13 (2169 kg.ha-1) as the best genotype with high yielding and stability performance. The breeding lines G3 and G15 with 1960 and 3041 kg.ha-1, respectively,  had the highest mean yield under rainfed and supplemental irrigation conditions, indicating the superiority of these two lines than the check cultivar in the both rainfed and supplemental irrigation conditions. In conclusion, positive increase in yield and yield stability is attributable predominately to genetic improvement in durum wheat breeding lines under variable environments.

Keywords

References

Badu-Apraku, Oyekunle, B., Obeng-Antwik, M., Osuman, A. S. Ado, S. G. Couliba, Y. N. Yallou, C. G. Abdulai, M., Boakyewa, G.A. and Didjeira, A. 2012.Performance of extra-early maize cultivars based on GGE biplot and AMMI analysis. Journal of Agricultural Science (Cambridge) 150: 473-483.##Eberhart, S.A. and Russell, W.A. 1966. Stability parameters for comparing varieties. Crop Science 6: 36-40.##Fan, X.M., Kang, M.S., Chen, H., Zhang, Y., Tan, J. and Xu, C. 2007. Yield stability of maize hybrids evaluated in multi-environment trials in Yunnan, China. Agronomy Journal 99: 220-228.##Finlay, K. W. and Wilkinson, G.N. 1963. The analysis of adaptation in a plant breeding programme. Australian Journal of Agricultural Research 14: 742-754.##Gabriel, K.R. 1971. The biplot graphic display of matrices with application to principal component analysis. Biometrika 58: 453-467.##Gancales, P.S., Bortoletto, N., Mellomartins, A.L., Costa, R.B. and Gallo, P.B. 2003.Genotype-environment interaction and phenotypic stability for girth growth and rubber yield hevea clones in saopaulo state. Brazil. Genetics and Molecular Biology 26(4): 441-448.##Gauch, H.G. 1992. Statistical analysis of regional yield trials: AMMI analysis of factorial designs. Elsevier, Amsterdam, Netherlans. 278 p.##Guzman, C., Autrique, J.E., Mondal, S., Singh, R.P., Govindan, V., Morales-Dorantes, A., Romano, G. P., Crossa, J., Ammar, K. and Pena, R.J. 2016. Response to drought and heat stress on wheat quality, with special emphasis on bread-making quality, in durum wheat. Field Crops Research186: 157-165.##Kang, M.S., Aggarwal V.D. and Chirwa, R.M. 2006. Adaptability and stability of bean cultivars as determined via yield stability statistic and GGE biplot analysis. Journal of Crop Improvement 15: 97-120.##Kearsey, M.J. and Pooni H.S. 1996. The genetical analysis of quantitative traits. Plant genetics group. School of Biological Sciences,The University of Birmangham.##Lin, C.S. and Binns, M.R. 1988. A superiority measure of cultivar performance for cultivar × location data. Canadian Journal of Plant Sciences 68: 193-198.##Mohammadi, R. and Amri, A. 2013.Genotype x environment interaction and genetic improvement for yield and yield stability of rainfed durum wheat in Iran. Euphytica 192: 227-249.##Mohammadi, R., Abdolahi, A., Mohammadi, M. S., Elahi, K. and Yari, S.R. 2016. Evaluation of yield gap of durum wheat genotypes under research and farmer’s fields conditions. Research Achievements for Fields and Horticulture Crops 5(2): 133-141. (In Persian with English Abstract).##Moslemi, M., Roustaii, M. and Rashidi, V. 2012. Evaluation of grain yield and yield components in bread wheat genotypes under different moisture regimes. Seed and Plant Improvement Journal 28(4): 611-630. (In Persian with English Abstract).##Rakshit, S., Ganapathy, K.N.,Gomashe, S.S.,Rathore, A., Ghorade, R.B., Nagesh-Kumar, M.V.,Ganesmurthy, K., Jain, S.K., Kamtar, M.Y.,Sachan, J.S., Ambekar, S.S.,Ranwa, B.R.,Kanawade, D.G.,Balusamy, M.,Kadam, D., Sarkar, A., Tonapi, V.A. and Patil, J. V. 2012. GGE biplot analysis to evaluate genotype, environment and their interactions in sorghum multi-location data. Euphytica85: 465-479.##Rose, I.V.L.W., Das, M.K. and Taliaferro, C.M. 2008. A comparison of dry matter yield stability assessment methods for small numbers of genotypes of bermudagrass. Euphytica 164: 19-25.##Rosielle, A.A. and Hamblin, J. 1981. Theoretical aspects of selection for yield in stress and non-stress environment. Crop Science 21: 943-946.##Samonte, S.O.P.B., Wilson, L.T., McClung, A.M. and Medley, J.C. 2005. Targeting cultivars onto rice growing environments using AMMI and SREG GGE biplot analysis. Crop Science 45: 2414-2424.##Sharma, R.C., Morgounov, A.I.,Braun, H.J., Akin, B., Keser, M., Bedoshvili, D., Bagci, A.,  Martius, C. and  van Ginkel, M. 2010. Identifying high yielding stable winter wheat genotypes for irrigated environments in central and west Asia.Euphytica171: 53-64.##Shukla, G.K. 1972. Some statistical aspects of partitioning genotype-environmental components of variability. Heredity 29: 237-245.##Yan, W. 2002. Singular value partitioning in biplot analysis of multi-environment trial data. Agronomy Journal 94: 990–996.##Yan, W. and Kang, M.S. 2003. GGE Biplot analysis: A graphical tool for breeders, geneticists and agronomists. 1stEd. CRC Press LLC., Boca Roton, Florida. 271 p.##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: 597-605.##Yan, W. and Tinker, N.A. 2006. An integrated system of biplot analysis for displaying, interpreting, and exploring genotype‑by‑environment interactions. Crop Science 45: 1004-1016.##Yan, W. and Rajcan,I.R. 2002. Biplot analysis of test sites and trait relations of soybean in Ontario. Crop Science 42: 11-20.
Cereal Research
Volume 8, Issue 1
June 2018
Pages 73-83

Files

Share

How to cite

Statistics