Analysis of Stability and G × E Interaction of Rice Genotypes across Saline and Alkaline Environments in India
Genotype × environment (G×E) interaction effects are of special interest for identifying the most suitable genotypes with respect to target environments, representative locations and other specific stresses. Twenty-two advanced breeding lines contributed by the national partners of the Salinity Tolerance Breeding Network (STBN) along with four checks were evaluated across 12 different salt affected sites comprising five coastal saline and seven alkaline environments in India. The study was conducted to assess the G × E interaction and stability of advanced breeding lines for yield and yield components using additive main effects and multiplicative interaction (AMMI) model. In the AMMI1 biplot, there were two mega-environments (ME) includes ME-A as CARI, KARAIKAL, TRICHY and NDUAT with winning genotype CSR 2K 262; and ME-B as KARSO, LUCKN, KARSA, GOA, CRRI, DRR, BIHAR and PANVE with winning genotypes CSR 36. Genotypes CSR 2K 262, CSR 27, NDRK 11-4, NDRK 11-3, NDRK 11-2, CSR 2K 255 and PNL 1-1-1-6-7-1 were identified as specifically adapted to favorable locations. The stability and adaptability of AMMI indicated that the best yielding genotypes were CSR 2K 262 for both coastal saline and alkaline environments and CSR 36 for alkaline environment. CARI and PANVEL were found as the most discernible environments for genotypic performance because of the greatest GE interaction. The genotype CSR 36 is specifically adapted to coastal saline environments GOA, KARSO, DRR, CRRI and BIHAR and while genotype CSR 2K 262 adapted to alkaline environments LUCKN, NDUAT, TRICH and KARAI. Use of most adapted lines could be used directly as varieties. Using them as donors for wide or specific adaptability with selection in the target environment offers the best opportunity for widening the genetic base of coastal salinity and alkalinity stress tolerance and development of adapted genotypes. Highly stable genotypes can improve the rice productivity in salt-affected areas and ensure livelihood of the resource poor farming communities.
KeywordsAMMI G×E interaction rice salinity alkalinity
Unable to display preview. Download preview PDF.
Authors sincerely thank the Bill and Melinda Gates Foundation for funding support under the STRASA project (IRRI-ICAR collaborative project) the Directors of all the partner Institutes for encouragement and CRIL, IRRI for helping in data analysis.
- Anandan, A., Eswaran, R., Sabesan, T., Prakash, M. 2009. Additive main effects and multiplicative interactions analysis of yield performances in rice genotypes under coastal saline environments. Adv. Biol. Res. 3:43–47.Google Scholar
- Bajpai, P.K., Prabhakaran, V.T. 2000. A new procedure of simultaneous selection for high yielding and stable crop genotypes. Indian J. Genet. 60:141–146Google Scholar
- Eskridge, K.M. 1990. Selection of stable cultivars using a safety-first rule. Crop Sci. 30:369–374.Google Scholar
- FAO 2013. Global cereals forecast to increase by 7 percent in 2013. http://www.fao.org/asiapacifc/rap/home/news/detail/en/?news_uid=180032
- Gauch, H.G., Zobel, R.W. 1996. AMMI analysis of yield trials. In: Kang, M.S., Gauch, H.G. (eds), Genotype-by-environment Interaction. CRC Press. Boca Raton, FL, USA. pp. 85–122.Google Scholar
- Kumar, D.B.M., Shadakshari, Y.G., Krishnamurthy, S.L. 2010. Genotype×Environment interaction and stability analysis for grain yield and its components in Halugidda local rice mutants. Electronic J. Pl. Breed. 1:1286–1289.Google Scholar
- Kumar, D.B.M., Gangaprsad, S., Krishnamurthy, S.L., Mallikarjunaiah, H. 2011. Stability analysis of puttabatta rice mutants. Karnataka J. Agril. Sci. 24:527–528.Google Scholar
- Maas, E.V., Hoffman, G.J. 1977. Crop salt tolerance: Current assessment. J. Irrig. Drain. Eng. 103:115–134.Google Scholar
- Mishra, B. 2005. More Crop per Drop. Survey of Indian Agriculture. The Hindu, Kasthuri Publishers. Chennai, India, pp. 41–46.Google Scholar
- Muthuramu, S., Jebara, J.S., Gnanasekaran, M. 2011. AMMI biplot analysis for drought tolerance in rice (Oryza sativa L.). Res. J. Agril. Sci. 2:98–100.Google Scholar
- OECD/FAO 2012. OECD-FAO Agricultural Outlook 2012–2021. OECD Publishing and FAO. http://dx.doi. org/10.1787/agr_outlook-2012-en.Google Scholar
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.