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Euphytica

, Volume 208, Issue 2, pp 391–400 | Cite as

Heterosis and combining ability of elite maize inbred lines under northern corn leaf blight disease prone environments of the mid-altitude tropics

  • Wende Abera
  • Shimelis Hussein
  • John Derera
  • Mosisa Worku
  • Mark Laing
Article

Abstract

Yields of maize (Zea mays L.) are remarkably low in sub-Saharan Africa and yet farmers have limited access to improved varieties. The objective of this study was to determine combining ability and heterosis of 18 elite maize inbred lines in environments prone to northern corn leaf blight (NCLB) disease in the mid-altitude tropics. Nine elite inbred lines were crossed as females with nine male lines using the North Carolina Design II mating scheme and 81 hybrids were generated. The hybrids, parents and three standard check varieties were evaluated using an alpha lattice design with two replications across seven environments in the mid-altitude sub-humid agro-ecologies in Ethiopia. The new top ranking hybrids displayed up to 250 % high-parent heterosis and mid-parent heterosis for grain yield and up to −25 % high-parent mid-parent heterosis for NCLB reaction. The specific combining ability (SCA) by site interaction was not significant, suggesting that the top yielding hybrids were relatively stable across environments. Inbred lines such as CML 395, 30H83-7-1, ILO’OE-1-9, 124-b (113), CML202, CML312, and Gibe-1-91 resulted in significant SCA effects for grain yield were selected as promising parents. Lines CML395 and ILO’OE-1-9 had negative and significant general combining ability (GCA) effects for NCLB reaction, implying the resistance of the inbred lines for NCLB. The most performing experimental hybrids such as CML-312 × CML395, CML197 × CML395, CML443 × DE-78-Z-126-3 had high SCA effects and produced mean grain yields of >8 t ha−1. The new hybrids may be used directly for production or as testers in hybrid development with resistance to NCLB.

Keywords

General combining ability Heterosis Hybrid Maize Specific combining ability 

Notes

Acknowledgments

The Alliance for a Green Revolution in Africa (AGRA) is sincerely thanked for financial support of the study. The Ethiopian Institute of Agricultural Research (EIAR) is acknowledged for providing the first author’s leave of absence and for hosting the field research. The all-round support provided by the national maize research program of Ethiopia is highly appreciated. The International Maize and Wheat Improvement Center (CIMMYT) is sincerely thanked for providing some of the inbred lines.

Supplementary material

10681_2015_1619_MOESM1_ESM.docx (42 kb)
Supplementary material 1 (DOCX 42 kb)

References

  1. Ahmad A, Saleem M (2003) Combining ability analysis in maize. Int J Agric Biol 5:239–244Google Scholar
  2. Alam A, Ahmed S, Begum M, Sultan M (2008) Heterosis and combining ability for grain yield and its contributing characters in maize. Bangladesh J Agric Res 33:375–379Google Scholar
  3. Banziger M, Cooper M (2001) Breeding for low input conditions and consequences for participatory plant breeding: examples from tropical maize and wheat. Euphytica 122:503–519CrossRefGoogle Scholar
  4. Bayisa A, Hussein M, Habtamu Z (2008) Combining ability of transitional highland maize inbred lines. East Afr J Sci 2:19–24Google Scholar
  5. CSA (2012) Report on area and production of crops. Agricultural sample survey on private peasant holdings. Central Statistic Authority, Addis Ababa, EthiopiaGoogle Scholar
  6. Dabholkar AR (1999) Elements of biometrical genetics. Kalyani Publishers, New DelhiGoogle Scholar
  7. Dagne W (2002) Combining ability analysis for traits of agronomic importance in maize (Zea mays L.) inbred lines with different levels of resistance to grey leaf spot (Cercospora zea maydis). MSc Thesis, Haramaya University, EthiopiaGoogle Scholar
  8. Dagne W, Vivek BS, Birhanu T, Koste A, Mosisa W, Legesse W (2010) Combining abilitiy and heterotic relationship between CIMMYT and Ethiopian maize inbred lines. Ethiopian J Agric Sci 20:82–93Google Scholar
  9. Dagne W, Labuschagne MT, Vivek B (2012) The influence of water stress on yield and related characteristics in inbred quality protein maize lines and their hybrid progeny. Agric Water Manag 85:112–115Google Scholar
  10. Falconer DS (1989) Introduction to quantitative genetics. Oliver and Boyd, LondonGoogle Scholar
  11. Girma T, Fekede A, Temam H, Tewabech T, Eshetu B, Melkamu A, Girma D. Kiros M (2008) Review of maize, sorghum and millet pathology research. In: Tadesse A, Ali K (Eds.) Proceedings of the 14th Conference of the Plant Protection Society of Ethiopia, 19–22 December 2006, Addis Ababa, Ethiopia, p. 49–55Google Scholar
  12. Hallauer AR, Miranda JB (1988) Quantitative genetics in maize breeding. Iowa State University Press, AmesGoogle Scholar
  13. Kanyamasoro MG, Karungi J, Asea G, Gibson P (2012) Determination of the heterotic groups of maize inbred lines and the inheritance of their resistance to the maize weevil. Afr Crop Sci J 20:23–34Google Scholar
  14. Legesse W, Pixley KV, Botha AM (2009) Combining ability and heterotic grouping of highland transition maize inbred lines. Maydica 54:1–9Google Scholar
  15. Meseka S, Menkir A, Ibrahim A, Ajala S (2006) Genetic analysis of performance of maize inbred lines selected for tolerance to drought under low nitrogen. Maydica 51:487–494Google Scholar
  16. Mosa H (2010) Estimation of combining ability of maize inbred lines using a top cross mating design. J Agric Res 36:13–16Google Scholar
  17. Mosisa W, Banziger M, Friesen D, Erley Schulte Ayfm, Horst WJ, Vivek BS (2008) Relative importance of general combining ability and specific combining ability among tropical maize (Zea mays L.) inbreds under contrasting nitrogen environments. Maydica 53:279–288Google Scholar
  18. Rahman HZ, Shah S, Shah M, Khalil I (2012) Evaluation of maize S2 lines in test crosses combinations II: yield and yield components. Pak J Bot 44:187–192Google Scholar
  19. Rojas BA, Sprague GF (1952) A comparison of variance components in corn yield traits; general and specific combining abilities and their interaction with locations and years. Agron J 44:462–466CrossRefGoogle Scholar
  20. SAS (2002) Statistical Analysis System, Version 9.0, SAS Institute, Inc., Cary, NC, USAGoogle Scholar
  21. Sharma JR (1998) Statistical and biometrical methods in plant breeding. New Age International, New DehliGoogle Scholar
  22. Singh RK, Chaudhary BD (1985) Biometrical methods in quantitative genetics analysis. Kalyani Publishers, New Delhi-LudhianaGoogle Scholar
  23. Wende A, Hussein S, Derera J, Mosisa W, Laing MD (2013) Preferences and constraints of maize farmers in the development and adoption of improved varieties in the mid-altitude, sub-humid agro-ecology of western Ethiopia. Afr J Agric Res 8:1245–1254Google Scholar
  24. Wheeler BEJ (1969) An introduction to plant diseases. Wiley and Sons, London 347 Google Scholar
  25. Worku M, Tuna H, Nigussie M, Deressa A (2001) Maize production trends and research in Ethiopia. In: Nigise M, Tanner D (Eds.). Enhancing the contribution of maize to food security in Ethiopia. Proceedings of the 2nd national maize work shop of Ethiopia, 12–16 November 2001, EARO/CIMMYT, Addis Ababa, Ethiopia, pp. 47–50Google Scholar
  26. Xingming F, Jing T, Bihua H, Feng L (2001) Analyses of combining ability and heterotic groups of yellow grain quality protein maize inbreds. In: Friesen DK, Palmer FAE (Eds.). Integrated Approach to Higher Maize Productivity in the New Millennium. Proceeding of the 7th Eastern Southern Africa Regional Maize Conference. 5–11 February 2002, CIMMYT/KARI, Nairobi, Kenya, pp. 143–148Google Scholar
  27. Zeleke H, Tuna H (2010) Combining ability analysis for yield and related traits in quality protein maize (Zea mays L.) inbred lines. Int J Biol Sci 2:2010–2015Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • Wende Abera
    • 1
    • 2
  • Shimelis Hussein
    • 1
  • John Derera
    • 1
  • Mosisa Worku
    • 3
  • Mark Laing
    • 1
  1. 1.African Center for Crop ImprovementUniversity of KwaZulu-NatalPietermaritzburgSouth Africa
  2. 2.IITA-NigeriaIbadanNigeria
  3. 3.CIMMYT-KenyaNairobiKenya

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