Evaluation of Some Promising Rice Genotypes for Grain Yield Stability Using AMMI Model

International Journal of Agriculture & Environmental Science
© 2019 by SSRG - IJAES Journal
Volume 6 Issue 4
Year of Publication : 2019
Authors : Ehirim, B.O ,Bashir, M , Gana, A.S,Salaudeen, M.T ,Tolorunse, K.D,Uyokei, U, Onotugoma, E, Uwuigbe, E.U.
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Ehirim, B.O ,Bashir, M , Gana, A.S,Salaudeen, M.T ,Tolorunse, K.D,Uyokei, U, Onotugoma, E, Uwuigbe, E.U., "Evaluation of Some Promising Rice Genotypes for Grain Yield Stability Using AMMI Model," SSRG International Journal of Agriculture & Environmental Science, vol. 6,  no. 4, pp. 167-171, 2019. Crossref, https://doi.org/10.14445/23942568/IJAES-V6I4P122

Abstract:

Plant breeders are always faced with the difficulty of haven to develop genotypes that are not only high yielding but combined with stability across varied locations (environments). Stability and sensitivity estimate were investigated on grain yield of 13 lowland rice genotypes of which, 2 commercially released rice varieties (FARO 44 and FARO 52)were used as checks, for 4 years; 2013, 2014, 2015 and 2016. The experiments were laid out in a randomized complete block design in three replications. The Analysis of Variance for Additive Main Effect and Multiplicative Interaction (AMMI ANOVA)revealed that grain yield differed significantlyfor both genotypes and environment at P = <0.01 indicating that both the genotypes and the environment (years) of investigation responded differently. The partitioning of GGE through GGE biplot analysis showed that, principal component1 and principal component 2 accounted for 50.46% and 24.78% of GGE sum of squares, respectively, explaining75.24% of the total observable variations noticed. AMMI 2 biplot revealed that, genotype G11 (FAROX521-H137-1) was the most stable across the years investigated, indicating its consistency across the different environments. Hence, the genotype would be considered more adapted to wide ranges of environments than the rest genotypes.

Keywords:

AMMI, Genotype, Stability

References:

[1] Akande S.O (2002) An Overview of the Nigerian Rice Economy, NISER, Ibadan.
[2] F.A.O. (1990). Technical Hand Book for the paddy rice industry in Developing countries [www.fao.org/docrept/t1838e].
[3] GRISP (Global Rice Science Partnership) (2013). Rice almanac, 4th edition. Los Banos (Philippines) International Rice Research Institute: 283.
[4] Shrief, S.A., (2003). Parametric and non-parametric measures of stability in oil seed rape hybrids. Proc. 3rd plant Breed.Conf. April 26, Giza, Egypt. J. plant Breed. 7(1): 689-706
[5] Allard RW, Bradshaw AD (1964). Implications of genotype × environment interaction in applied plant breeding. Crop Sci. 4:503-508.
[6] Finlay, K.W., Wilkinson G.N. (1963). The analysis of adaptation in a plant breeding programmeAust. J. Agric. Res. 14:742-754.
[7] Eberhart SA, Russell WA (1966). Stability parameters for comparing varieties. Crop Sci. 6:36-40.
[8] Yan, W, Hunt, L A, Sheng, Q. and Szlavnics, Z. (2000). Cultivar evaluation and mega environment investigation based on the GGE biplot. Crop Sci., 40: 597- 605.
[9] Yan W, Kang MS (2003) GGE Biplot Analysis: A Graphical Tool for Breeders, Geneticists and Agronomists. 1st Edn., CRC Press LLC., Boca Roton, Florida, pp: 271
[10] Yan W, Tinker NA (2006). Biplot analysis of multi-environmental trial data: Principles and applications. Can. J. Plant Sci. 86:623-645.
[11] Ding M, Tier B, Yan W (2007) Application of GGE biplot analysis to evaluate genotype (G), environment (E) and GxE interaction on P. radiata: A case study. Paper presented to Australasian Forest Genetics Conference Breeding for Wood Quality, 11¬14 April 2007, Hobart, Tasmania, Australia.
[12] Singh S.V., Singh R.B. (1980). Stability of component charactersin relation with the stability of yield. Indian J. Genet.40:93-98
[13] Breeding Management System (BMS). (2015). Breeding management system. Version 3.0.8. Integrated Breeding Platform (IBP), Mexico.
[14] Ishaq M.N., H. Agrama and A. Adeleke (2015). Exploiting Genotype X Environment Interaction in Soybean breeding in Nigeria. Int. J. Adv. Res. Biol. Sci.2(1)2015: 24-32
[15] Maji, A. T., Bashir, M., Odoba, A., Gbanguba, A. U., Audu, S. D., (2015). Genotype × Environment Interaction and Stability Estimate for Grain Yield of Upland Rice Genotypes in Nigeria. J Rice Res3:136.
[16] Crossa, J., 1990. Statistical analyses of multilocation trials. Adv.Agron., 44: 55-85.
[17] Egesi, C.N. and R. Asiedu, (2002). Analysis of yam yields usingthe additive main effects andmultiplicative interaction(AMMI) model. Afr. Crop Sci. J., 10: 195-201.