Volume 6, Issue 3, June 2018, Page: 101-106
Genotype x Environment Interaction and Stability Analysis for Gran Yield of Diallel Cross Maize Hybrids Across Tropical Medium and Highland Ecologies
Alphonse Nyombayire, African Centre for Crop Improvement, University of KwaZulu-Natal, Pietermaritzburg, South Africa; Reaserch Department, Rwanda Agriculture Board, Kigali, Rwanda
John Derera, African Centre for Crop Improvement, University of KwaZulu-Natal, Pietermaritzburg, South Africa
Julia Sibiya, African Centre for Crop Improvement, University of KwaZulu-Natal, Pietermaritzburg, South Africa
Claver Ngaboyisonga, Reaserch Department, Rwanda Agriculture Board, Kigali, Rwanda
Received: Apr. 5, 2018;       Accepted: Apr. 23, 2018;       Published: Aug. 21, 2018
DOI: 10.11648/j.jps.20180603.14      View  1001      Downloads  99
Genotype x environment (G x E) interaction is the differential performance of genotypes across environments, especially in the tropics where seasonal and spatial variability is large. This results in serious challenges of product selection across environments. The objectives of this study were to determine G x E interaction and yield stability of new diallel cross maize hybrids and to identify suitable genotypes for the medium and highland ecologies in Rwanda. Forty- five diallel cross maize hybrids and three commercial checks were evaluated in four locations representing the major agro-ecologies of Rwanda over three seasons. The data were subjected to genotype and genotype by environment interaction (GGE) biplot analysis, using Genstat statistical package. The analysis revealed two mega-environments which discriminated the hybrids. Two genotypes 3 (S1/S4) and 25 (S4/S5) displayed specific adaptation; qualifying them as candidates for further testing in respective mega-environments. Genotypes 3 (S1/S4) and 29 (S4/S9) demonstrated high yield and stability. Overall, the study revealed crossover interaction and there is need to breed for both broad and specific adaptation in these medium and high altitude environments.
Biplot, Genotype by Environment Interaction, Grain Yield, Maize Hybrids, Stability
To cite this article
Alphonse Nyombayire, John Derera, Julia Sibiya, Claver Ngaboyisonga, Genotype x Environment Interaction and Stability Analysis for Gran Yield of Diallel Cross Maize Hybrids Across Tropical Medium and Highland Ecologies, Journal of Plant Sciences. Vol. 6, No. 3, 2018, pp. 101-106. doi: 10.11648/j.jps.20180603.14
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Bänziger, M., and M. Cooper. (2001). Breeding for low input conditions and consequences for participatory plant breeding examples from tropical maize and wheat. Euphytica 122, 503-519.
Bisawas, A., U. Sarker, B. Banik, M. Rohman, and M. Talukder. (2014). Genotype x environment interaction for grain yield of maize (Zea mays L.) inbreds under salinity stress. BJAR 39, 293-301.
Fan, X. M., M. S. Kang, H. Chen, Y. Zhang, J. Tan, and C. Xu. (2007). Yield stability of maize hybrids evaluated in multi-environment trials in Yunnan, China. Agron J 99, 220-228.
Gauch, H., and R W. Zobel. (1997). Identifying mega-environments and targeting genotypes. Crop Sci 37, 311-326.
Kabirigi, M., S. Mugambi, B. S. Musana, G. T. Ngoga, J. C. Muhutu, J. Rutebuka, V. Ruganzu, I. Nzeyimana, N. L. Nabahungu. (2017). Estimation of soil erosion risk, its valuation and economic implications for agricultural production in western part of Rwanda. J Exp Biol and Agric Sci, 5(4).
Kamut, C. N., D. Muungani, D. R. Masvodza, and E. Gasura. (2013). Exploiting genotype x environment interaction in maize breeding in Zimbabwe. Afr. J Agric Res 8, 4058-4066.
Kayaga, H. N., M. Ochwo-Ssemakula, F. Kagoda, B. M. E. Alladassi, G. Asea, P. Gibson, and R. Edema. (2017). Genotype by environment interaction effects on grain yield of highland maize (Zea mays L) hybrids. Maydica, 62-2017.
Meseka, S. K., A. Menkir, and A. E. S. Ibrahim. (2008). Yield potential and yield stability of maize hybrids selected for drought tolerance. J Appl Biosci 3, 82–90.
Mutimura, M., and T. Everson. (2012). The role of gender in livestock rearing in the low rainfall and acidic soil prone areas of Rwanda. Agric J 7(2), 152-159.
Ngaboyisonga, C., F. Nizeyimana, A. Nyombayire, M. Gafish, J. Ininda, and D. Gahakwa. ( 2014). Identification of Elite, High Yielding and Stable Maize Cultivars for Rwandan Mid-altitude Environments. Challenges and Opportunities for Agricultural Intensification of the Humid Highland Systems of Sub-Saharan Africa. Springer. p. 165-176.
Ngaboyisonga, C., A. Nyombayire, M. Gafishi, F. Nizeyimana, A. Uwera, and T. Ndayishimiye. (2016). Adaptability and genotype by environment interaction of maize commercial hybrid varieties from east african seed companies in rwandan environments. GJAR 4, 32-40.
Nyombayire, A., R. Edema, G. Asea, and P. Gibson. (2011). Combining ability of maize inbred lines for performance under low nitrogen and drought stresses. In: J. S. Tenywa, G. Taulya, G. Kawube, R. Kawuki, M. Namugwanya, and L. Santos(eds), Proceedings of 10th african crop science society international conference, 10th-13th October 2011, Maputo-Mozambique, Vol. 10. pp. 577–583.
Nzuve, F., S. Githiri, D. Mukunya, and J. Gethi. (2013). Analysis of genotype x environment interaction for grain yield in maize hybrids. J Agric Sci 5, 75.
Payne, R. W., D. A. Murray, and S. A. Harding. (2014). An Introduction to the GenStat Command Language (17th Edition). VSN International, Hemel Hempstead, UK.
Sallah, P. Y. K., S. Mukakalisa, A. Nyombayire, and P. Mutanyagwa. ( 2009). Response of two maize varieties to density and nitrogen fertilizer in the highland zone of Rwanda. J Appl Biosci 20, 1194 – 1202.
Shi, P., W. Xu, T. Ye, S. Yang, L. Liu, and W. Fang. (2015). World atlas of natural disaster risk. World Atlas of Natural Disaster Risk. Springer. p. 309-323.
Sibiya, J., P. Tongoona, and J. Derera. (2012). Combining ability and GGE biplot analyses for resistance to northern leaf blight in tropical and subtropical elite maize inbred lines. Euphytica 191, 245-257.
Twumasi-Afrriye, S., L. Wolde, Z. Mduruma, G. Ombhakho, D. Kyetere, A. Manirakiza, and C. Ngaboyisonga. (2001). Infusion, development and Improvement of highland maize germplasm in East Africa.
Yan, W. (2002). Singular-value partitioning in biplot analysis of multienvironmental trial data. Agron J 94, 990–996.
Yan, W., L. A. Hunt, Q. Sheng, and Z. Szlavnics. (2000). Cultivar evaluation and mega-environment investigation based on GGE biplot. Crop Sci 40, 596–605.
Yan, W., and M. S. Kang. (2003). GGE Bioplot Analysis, a Graphical Tool for Breeders, Geneticists, and Agronomists. CRC Press LLC, Florida.
Yan, W., M. S. Kang, M. Baoluo, S. Woods, and P. L. Cornelius. (2007). GGE Biplot vs. AMMI Analysis of Genotype-by-Environment Data. Crop Sci 47, 643–655.
Yan, W., D. Pageau, J. Frégeau-Reid, and J. Durand.(2011). Assessing the Representativeness and Repeatability of Test Locations for Genotype Evaluation. Crop Sci 51, 1603-1610.
Yan, W., and N. A. Tinker.(2006). Biplot analysis of multi-environment trial data: Principles and applications. Can J Plant Sci 86, 623-645.
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