Seventeen medium-maturing lowland rice genotypes along with a check variety were raised in a randomized complete block design of three replications and assessed for yield stability and performance under rain fed lowland conditions at Woreta, Pawe, Maitsebri, Jimma and Assosa. AMMI analysis of variance indicated that environments, genotypes and their interaction accounted for 43.06%, 12.03% and 22.04% of the total sum of squares (SS) for grain yield, respectively. The first four interaction principal component axes were significant and together explained 85.8% of interactions SS. Averaged over environments, genotype G16 had the highest yield of 6.56 t ha-1 , G2 (6.32 t ha-1), G6 (5.49 t ha-1) and G7 (5.49 t ha-). Genotypes G5, G6, G7, G14 and G16 had lower AMMI stability value and yield stability index. In AMMI 1 and AMMI 2 biplots G6, G7 and G16 were found to be high yielding and stable while G2 was less stable but high yielding. Thus, genotypes G2, G6 and G16 were considered as candidate varieties and verified, out of which G16 was approved for release by the name ‘Abay’. Genotypes G2, G6, and G7can be used as potential parent materials in rice breeding program.
lowland rice, GE interaction, AMMI analysis, grain yield
Addis, D., Alemu, D., Assaye, A., Tadesse, T., Tesfaye, A. & Thompson J. (2018) A Historical Analysis of Rice Commercialization in Ethiopia: The Case of the Fogera Plain, Agricultural Policy Research in Africa (APRA). Working Paper 18, Future Agricultures Consortium.
Africa Rice Center (AfricaRice) (2017). Annual Report 2016: Towards rice self-sufficiency in Africa. Abidjan, Côte d’Ivoire.
Akbarzai, D. K., Nisar, S. ., & Mohammadi, L. (2021). Genotype × Environment interaction studies in lentil under Afghanistan environments. Journal of Innovative Agriculture, 8(2), 39-46. https://doi.org/10.37446/jinagri/rsa/8.2.2021.39-46.
Akter. A., Jamil, H.M., Umma, K.M., Islam, M.R., Kamal, H.& Mamunur, R.M. (2014). AMMI Biplot Analysis for Stability of Grain Yield in Hybrid Rice (Oryza sativa L.). J Rice Res., 2, 126. Doi: http://dx.doi.org/10.4172/jrr.1000126.
Akter, A., Jamil HM, Kulsum MU, Rahman MH, Paul AK, Lipi LF, Akter S (2015). Genotype × Environment Interaction and Yield Stability Analysis in Hybrid Rice (Oryza sativa L.) By AMMI Biplot. Bangladesh Rice J. 19(2): 83-90.
Barker, R., Herdt, R.W, & Beth R. (1985). The rice economy of Asia. Resource for the future, Routledge, Washington D.C.
Bose, L.K., Jambhulkar, N.N., Pande, K. & Singh, O.N. (2014). Use of AMMI and other stability statistics in the simultaneous selection of rice genotypes for yield and stability under direct-seeded conditions. Chilean J. Agric. Res., 74(1),1-9.
Crossa, J., Gauch, H.G. & Zobel, R.W. (1990). Additive Main Effects and Multip-A. Seyoum et al. licative Interaction Analysis of Two International Maize Cultivar Trials. Crop Sci., 30, 493-500.
Crossa, J., & Cornelius, P. L. (1997). Sites regression and shifted multiplicative model clustering of cultivar trials sites under heterogeneity of variances. Crop Sci. 37: 406-415. doi: 10.2135/cropsci1997.0011183X0037000 20017x.
CSA (Central Statistical Agency) (2011). Report on area and production of major crops (private peasant holdings, meher season). The Federal Democratic Republic of Ethiopia, ADDIS ABABA.
CSA (Central Statistical Agency) (2020) Report on area and production of major crops (private peasant holdings, meher season). The Federal Democratic Republic of Ethiopia, ADDIS ABABA.
Falconer, D.S. & Mackay, T.F.C. (1996). Introduction to Quantitative Genetics. 4th Edition, Addison Wesley Longman, Harlow.
Farshadfar, E., Mahmodi, N. & Yaghotipoor, Y. (2011). AMMI stability value and simultaneous estimation of yield and yield stability in bread wheat (Triticum aestivum L.). AJCS5, 13, 1837-1844.
Ferreira, D.F., Demétrio, C.G.B., Manly, B.F.J., Machado, A. & Vencovsky, R. (2006). Statistical models in agriculture: biometrical methods for evaluating phenotypic stability in plant breeding. Cerne, Lavras, 12 (4), 373-388.
Gabriel, K.R. (1971). The biplot graphic display of matrices with application to principal component analysis. Biometrika, 58,453-467.
Gauch, H.G. & Zobel, R.W. (1996). AMMI analysis of yield trials. In M.S. Kang & H.G. Gauch. (eds.). Genotype-by-environment interaction, pp: 85-122.
GenStat. (2013). GenStat Statistical software. GenStat for Windows 16th Edition. VSN International, UK.
Lakew, T., Dessie, A., Taeiku, S. & Desta, A. (2017). Evaluation of Performance and Yield Stability Analysis Based on AMMI and GGE Models in Introduced Upland Rice Genotypes. IJRSAS, 3(2),17-24.
Li, W., Yan, Z. H., Wei, Y. M., Lan, X. L. & Zheng, Y. L. (2006). Evaluation of Genotype×Environment Interactions in Chinese Spring Wheat by the AMMI Model, Correlation and Path Analysis. J. Agron. Crop Sci., 192, 221-227.
Lingaiah, N., Chandra, B.S., Venkanna, V., Rukmini, D.K. & Hari, Y. (2020). AMMI Bi plot analysis for genotype x environment interaction on yield in rice (Oryza sativa L.) genotypes. Journal of Pharmacognosy and Phytochemistry, 9(3),1384-1388.
Mahalingam, L., Mahendran, S., Bahu, R.C. & Atlin, G. (2006). AMMI Analysis for stability of Grain Yield in Rice (Oryza sativa L.). International Journal of Botany, 2(2),104-106.
MoARD (Ministry of Agriculture and Rural Development) (2010). National Rice research and Development Strategyof Ethiopia, Ministry of Agriculture, The Federal Democratic Republic of Ethiopia, Addis Ababa, Ethiopia.
Mohammadi, R., Abdulahi, A., Haghparast, R. & Armion, M. (2007). Interpreting genotype- environment interactions for durum wheat grain yields using non-parametric methods. Euphytica, 157,239251.
Mohammadi, R. & Amri, A. (2008). Comparison of parametric and non-parametric methods for selecting stable and adapted durum wheat genotypes in variable environments. Euphytica, 159,419432.
Ohunakin, A. O. (2021). Genetic analysis and genotype x environment interaction for resistance to northern leaf blight disease in tropical maize (Zea mays L.) genotypes. Journal of Innovative Agriculture, 8(2), 67-74. https://doi.org/10.37446/jinagri/rsa/8.2.2021.67-74.
Purchase, J. L.(1997). Parametric Analysis to Describe G×E Interaction and Yield Stability in Winter Wheat. PhD. Thesis, Department of Agronomy, Faculty of Agriculture, University of the Orange Free State, Bloemfontein, Shout Africa.
Purchase ,J.L., Hatting. H. & van Deventer, C.S. (2000). Genotype x environment interaction of wheat in South Africa: stability analysis of yield performance. S. Afr. 1. Plant Soil.. 17(3), 101-107.
SAS Institute Inc. 2002. Version 9.0. SAS Institute Inc., Cary, NC. IRRI (1996). Standard Evaluation System for Rrice. Rice knowledge Bank.IRRI, Philippines.
Sharifi, P., Hashem, A., Rahman, E., Ali, M. & Abouzar, A. (2017). Evaluation of Genotype × Environment Interaction in Rice Based on AMMI Model in Iran. Rice Science, 24(3), 173-180.
Sivapalan, S., Brien, L.O., Ferrana, G.O., Hollamby, G.L. & Barelay, I, (2000). An adaption analysis of Australian and CIMMYT/ ICARDA wheat germplasm in Austrlian production environments. Australian Journal of Agriculture Research, 51, 903-915.
Tumuhimbise, R., Melis, R., Shanahan, P. & Kawuki, R. (2014). Genotype × environment interaction effects on early fresh storage root yield and related traits in cassava. The crop journal, 2, 329-337.
Huang, X., Jang, S., Zhongze, P., Edilberto, R. & Koh, H.J. (2021). Evaluating Genotype x Environment Interactions of Yield Traits and Adaptability in Rice Cultivars Grown under Temperate, Subtropical and Tropical Environments. Agriculture, 11, 558.
Yan, W. (2002). Singular-Value Partitioning in Biplot Analysis of Multienvironment Trial Data. Agron. J., 94,990-996.
Zemede, A. ., & Mekbib , F. (2021). Genotype x environment interaction and stability of drought tolerant durum wheat. Journal of Innovative Agriculture, 8(2), 52-58. https://doi.org/10.37446/jinagri/rsa/8.2.2021.52-58.
Zobel, R.W.,Wright, M.J. & Gauch , H. G. (1988). Statistical analysis of a yield trial. Agronomy Journal, 80, 388-393.