Skip to main content
Log in

Estimating gene action, combining ability and heterosis for grain yield and agronomic traits in extra-early maturing yellow maize single-crosses under three agro-ecologies of Ghana

  • Published:
Euphytica Aims and scope Submit manuscript

Abstract

Maize (Zea mays L.) is the most important cereal crop produced in Ghana. However, yield of the crop is generally low, producing just about 1.7 t/ha. The low yield is attributed to continuous use of local/unimproved varieties. Generally, hybrid varieties have proven to out-yield the local/unimproved varieties due to improved vigour. Development of hybrid varieties depend on good understanding of combining ability and inheritance of important quantitative traits such as grain yield (GY). 45 half-diallel crosses generated from 10 extra-early maturing yellow inbred lines were evaluated in 2015 under rain-fed conditions. The objectives were to determine the genetic control, breeding value and estimate heritability for GY and agronomic traits of the inbred lines under contrasting growing environments in Ghana. General combining ability (GCA) and specific combining ability (SCA) were important in the inheritance of GY and agronomic traits of the inbred lines. However, GCA was more important than SCA across environments to suggest that additive gene action was more important than non-additive gene action in the inheritance of GY and agronomic traits in the inbred lines. High broad-sense heritability, for GY and other agronomic traits indicated preponderance of additive gene action in trait expression, thus, selection based on phenotypic expression could be feasible. Inbred lines P1, P4 and P8 were good combiners for high GY. The genotype, P4 × P8, was identified as the ideal and most yielding single-cross hybrid across research environments and should be further tested on-farm before commercialization.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  • Akbar M, Shakoor MS, Hussain A, Sarwar M (2008) Evaluation of maize 3-way crosses through genetic variability, broad sense heritability, characters association and path analysis. J Agric Res 46(1):39–45

    Google Scholar 

  • Akinwale RO, Badu-Apraku B, Fakorede MAB, Vroh-Bi I (2014) Heterotic grouping of tropical early-maturing maize inbred lines based on combining ability in Striga-infested and Striga-free environments and the use of SSR markers for genotyping. Field Crops Res 156:48–62

    Article  Google Scholar 

  • Allard R (1964) Principles of plant breeding. Wiley, New York

    Google Scholar 

  • Badu-Apraku B, Oyekunle M (2012) Genetic analysis of grain yield and other traits of extra-early yellow maize inbreds and hybrid performance under contrasting environments. Field Crops Res 129:99–110

    Article  Google Scholar 

  • Badu-Apraku B, Twumasi-Afriyie S, Sallah PYK, Haag W, Asiedu E, Marfo KA, Dapaah S, Dzah BD (2006) Registration of “Obatanpa GH” maize. Crop Sci 46:1393–1394

    Article  Google Scholar 

  • Badu-Apraku B, Fakorede MAB, Lum AF (2007) Evaluation of experimental varieties from recurrent selection for Striga resistance in two extra-early maize populations in the savannas of West and Central Africa. Exp Agric 43:183–200

    Article  Google Scholar 

  • Badu-Apraku B, Lum AF, Fakorede MAB, Menkir A, Chabi Y, Thé C, Abdulai M, Jacob S, Agbaje S (2008) Performance of cultivars derived from recurrent selection for grain yield and Striga resistance in early maize. Crop Sci 48:99–112

    Article  Google Scholar 

  • Badu-Apraku B, Fontem LA, Akinwale RO, Oyekunle M (2011) Biplot analysis of diallel crosses of early maturing tropical yellow maize inbreds in stress and nonstress environments. Crop Sci 51(1):173–188

    Article  Google Scholar 

  • Badu-Apraku B, Oyekunle M, Fakorede MAB, Vroh I, Akinwale RO, Aderounmu M (2013) Combining ability and genetic diversity of extra-early yellow inbreds under contrasting environments. Euphytica 192:413–433

    Article  CAS  Google Scholar 

  • Badu-Apraku B, Annor B, Oyekunle M, Akinwale RO, Fakorede MAB, Talabi AO, Akaogu IC, Melaku G, Fasanmade Y (2015) Grouping of early maturing quality protein maize inbreds based on SNP markers and combining ability under multiple environments. Field Crops Res 183:169–183

    Article  Google Scholar 

  • Baker RJ (1978) Issues in diallel analysis. Crop Sci 18:533–536

    Article  Google Scholar 

  • Bello OB, Ige SA, Azeez MA, Afolabi MS, Abdulmaliq SY, Mahamood J (2012) Heritability and genetic advance for grain yield and its component characters in maize (Zea mays L.). International. J Plant Res 2(5):138–145

    Article  Google Scholar 

  • Bhatnagar S, Betrán FJ, Rooney LW (2004) Combining ability of quality protein maize inbreds. Crop Sci 44:1997–2005

    Article  Google Scholar 

  • Cenacchi N, Koo J (2011) Effects of drought tolerance on maize yield in Sub-Saharan Africa. Increasing Agricultural Productivity and Enhancing Food Security in Africa, New Chall Oppor, pp 1–19

    Google Scholar 

  • Edgerton MD (2009) Increasing crop productivity to meet global needs for feed, food, and fuel. Plant Physiol 149(1):7–13

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Falconer DS, Mackay TFC (1996) Introduction to quantitative genetics. Pearson Prentice Hall, Harlow

    Google Scholar 

  • FAOSTAT (2006) All longitudinal production and population data. http://faostat.fao.org/. Retrieved 4 Sept 2006

  • Griffing B (1956) Concept of general and specific combining ability in relation to diallel crossing systems. Aust J Biol Sci 9:463–493

    Article  Google Scholar 

  • Gutiérrez OA, Basu S, Saha S, Jenkins JN, Shoemaker DB, Cheatham CL, McCarty JC (2002) Genetic distance among selected cotton genotypes and its relationship with F performance. Crop Sci 42(6):1841–1847

    Article  Google Scholar 

  • Hallauer AR, Miranda JB (1981) Quantitative genetics in maize breeding. Iowa State University Press, Ames

    Google Scholar 

  • Hallauer AR, Miranda JB (1988) Quantitative genetics in plant breeding. Iowa State University Press, Ames

    Google Scholar 

  • IFPRI (2000) 2020 projections. International Food Policy Research Institute, Washington, DC

  • Kashiani P, Saleh G, Abdullah NAP, Abdullah SN (2010) Variation and genetic studies on selected sweet corn inbred lines. Asian J Crop Sci 2(2):78–84

    Article  Google Scholar 

  • La Rovere RK, Abdoulaye G, Dixon T, Mwangi J, Guo WM, Bänziger MZ (2010) Potential impact of investments in drought tolerant maize in Africa. CIMMYT, Addis Ababa

    Google Scholar 

  • Ludlow MM, Muchow RC (1990) A critical evaluation of traits for improving crop yields in water-limited environments. Adv Agron 43:107–153

    Article  Google Scholar 

  • MoFA (2010) Agriculture in Ghana: facts and figures. Ministry of Food and Agriculture, Statistics, Research, and Information Directorate (SRID), Accra

    Google Scholar 

  • National Research Council (1988) Quality protein maize. National Academic Press, Washington, DC

    Google Scholar 

  • Pixley K, Bänziger M, Cordova H, Dixon J, Kanampiu F, Srivastava A, Waddington S, Warburton M (2009) Past and future innovations of tropical maize improvement. CIMMYT report, Mexico

  • Prasanna BM (2012) Diversity in global maize germplasm: characterization and utilization. J Biosci 37(5):843–855

    Article  CAS  PubMed  Google Scholar 

  • Sprague GF, Tatum LA (1942) General versus specific combining ability in single crosses of corn. J Am Soc Agron 34:923–932

    Article  Google Scholar 

  • SRID (2010) Agriculture in Ghana. Facts and figures. Ministry of Food and Agriculture, Statistics Research and Information Directorate, Accra

    Google Scholar 

  • STAR (2014) Biometrics and breeding informatics. PBGB Division, International Rice Research Institute, Los Baños, Laguna, Version 2.0.1

  • Sumathi P, Nirmalakumari A, Mohanraj K (2005) Genetic variability and traits interrelationship studies in industrially utilized oil rich CIMMYT lines of maize (Zea mays L). Madras Agric J 92(10–12):612–617

    Google Scholar 

  • UNSD (2008) United Nations Statistics Division National accounts estimates of main aggregates. http://data.un.org/Data.aspxq_2008_&d

  • USDA (2011) United States Development Agency. Agricultural statistics report

  • Wynne JC, Emery DA, Rice PM (1970) Combining ability estimates in Arachis hypogeae L. II. Field performance of F1 hybrids. Crop Sci 10(6):713–715

    Article  Google Scholar 

  • Zhang Y, Kang MS, Lamkey KR (2005) DIALLEL-SAS: a comprehensive program for Griffing’s and Gardner-Eberthart analyses. Agron J 97:1097–1106

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to G. A. Owusu.

Ethics declarations

Conflict of interest

This research article is an account of our own research and has not been be published elsewhere. The works of other researchers which served as references have duly been acknowledged.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Owusu, G.A., Nyadanu, D., Obeng-Antwi, K. et al. Estimating gene action, combining ability and heterosis for grain yield and agronomic traits in extra-early maturing yellow maize single-crosses under three agro-ecologies of Ghana. Euphytica 213, 287 (2017). https://doi.org/10.1007/s10681-017-2081-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10681-017-2081-3

Keywords

Navigation