Skip to main content
SpringerLink
Log in

Why SR52 is such a great maize hybrid? II. Heritability, correlation and path-coefficient analyses

  • Published:
Euphytica Aims and scope Submit manuscript

Abstract

Although exceptional heterosis for yield in the world’s first commercial single cross maize (Zea mays L.) hybrid SR52 has been confirmed, the role of secondary traits hasn’t been established. Objectives of this study were to establish relationship between grain yield and secondary traits, while assessing heritability and genotypic variation in SR52’s segregating populations. Knowledge on associations between yield and secondary traits would be crucial in extracting productive inbred lines from the population. Traits were subjected to correlation and path-coefficient analyses. Path analysis model accounted for over 70% of variation (R2) in all populations. Consistently high positive correlations with grain yield were observed for ear length and number of kernel rows on ear. Ear girth (0.19), and number of kernels per row (0.48) showed high direct effects on yield in the F2 population and the trend was consistent in the backcrosses. Positive indirect effects of most traits on grain yield were negligible with the exception of kernel per row via total number of kernels on ear, which was above 0.40 in the F2 and BCP1. Ear length can be exploited for indirect selection for yield in SR52’s segregating generations. 100-kernel weight and number of kernel rows on ear can, to a lesser extent, be targeted in selecting for grain yield. High to medium phenotypic variability in segregating generations of SR52 for traits such as ear length, number kernel rows on ear and grain yield should give impetus to selection of productive inbred lines from SR52 hybrid because of presence of diversity in the gene pool.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Abirami SC, Vanniarajan S, Arumugachamy S, Uma D (2007) Correlation and path coefficient analysis for morphological and biochemical traits in maize genotypes. Plant Arch 7:109–113

    Google Scholar 

  • Basalma D (2008) The correlation and path analysis of yield and yield components of different winter rapeseed (Brassica napus ssp. oleifera L.) cultivars. Res J Agric Biol Sci 4:120–125

    Google Scholar 

  • Bello O, Abdulmaliq S, Afolabi M, Ige S (2010) Correlation and path coefficient analysis of yield and agronomic characters among open pollinated maize varieties and their F1 hybrids in a diallel cross. Afr J Biotechnol 9:2633–2639

    Google Scholar 

  • Burton JW, Carver BF (1993) Selection among S1 families versus selfed half-sib or full-sib families in autogamous crops. Crop Sci 33:21–28

    Article  Google Scholar 

  • Cramer CS, Wehner TC, Donaghy SB (1998) PATHSAS: a SAS computer program for path coefficient analysis of quantitative data. J Hered 90:260–262

    Article  Google Scholar 

  • Derera J, Musimwa TR (2015) Why SR52 is such a great maize hybrid? I. Heterosis and generation mean analysis. Euphytica 205:121–135

    Article  CAS  Google Scholar 

  • Dewey DR, Lu K (1959) A correlation and path-coefficient analysis of components of crested wheatgrass seed production. Agron J 51:515–518

    Article  Google Scholar 

  • El-Shouny K, El-Bagoury O, Ibrahim K, Al-Ahmad S (2005) Correlation and path coefficient analysis in four yellow maize crosses under two planting dates. Arab Univ J Agric Sci 13:327–339

    Google Scholar 

  • Falconer DS, Mackay TF, Frankham R (1996) Introduction to quantitative genetics, 4th edn. Longman, London UK

    Google Scholar 

  • FAO (2013) Area of maize harvested (tonnes) and production quantity (ha) in 2012. Food and Agriculture Organisation of the United Nations, Rome

    Google Scholar 

  • Fehr WR (1991) Principles of cultivar development, vol 1., Theory and techniqueMacMillan Publishing Co, New York

    Google Scholar 

  • Fuglie KO (2004) Challenging Bennet’s law: the new economics of starchy staples in Asia. Food Policy 29:187–202

    Article  Google Scholar 

  • Hefny M (2011) Genetic parameters and path analysis of yield and its components in corn inbred lines (Zea mays L.) at different sowing dates. Asian J Crop Sci 3:106–117

    Article  Google Scholar 

  • Hepziba SJ, Geetha K, Ibrahim SM (2013) Evaluation of genetic diversity, variability, character association and path analysis in diverse inbreds of maize (Zea mays L.). Electron J Plant Breed 4:1067–1072

    Google Scholar 

  • Holland JB, Nyquist WE, Cervantes-Martínez CT (2003) Estimating and interpreting heritability for plant breeding: an update. Plant Breed Rev 22:9–112

    Google Scholar 

  • Jayne TS, Zulu B, Nijhoff J (2006) Stabilizing food markets in eastern and southern Africa. Food Policy 31:328–341

    Article  Google Scholar 

  • Kang M (2015) Efficient SAS programs for computing path coefficients and index weights for selection indices. J Crop Improv 29(1):6–22

    Article  Google Scholar 

  • Kumar S, Shahi J, Singh J, Singh S (2006) Correlation and path analyis in early generation inbreds of Maize (Zea mays L.). J Crop Improv 33:156–160

    Google Scholar 

  • Ma X, Tang J, Teng W, Yan J, Meng Y, Li J (2007) Epistatic interaction is an important genetic basis of grain yield and its components in maize. Mol Breed 20:41–51

    Article  Google Scholar 

  • Magorokosho C, Vivek B, Mac Robert J (2009) Characterization of maize germplasm grown in Eastern and Southern Africa: Results of the 2008 regional trials Coordinated by CIMMYT. Harare, Zimbabwe

  • Malvar R, Revilla P, Moreno-González J, Butrón A, Sotelo J, Ordás A (2008) White maize: genetics of quality and agronomic performance. Crop Sci 48:1373–1381

    Article  Google Scholar 

  • Mashingaidze K (1994) Maize Research and Development. In: Eicher MRCK (ed) Zimbabwe’s agricultural revolution. University of Zimbabwe Publications Office, Harare, pp 208–218

    Google Scholar 

  • McCann J (2009) Maize and grace: Africa’s encounter with a new world crop, 1500–2000. Harvard University Press, Cambridge

    Google Scholar 

  • Mohammadi SA, Prasanna BM, Singh NN (2003) Sequential path model for determining interrelationships among grain yield and related characters in maize. Crop Sci 43:1690–1697

    Article  Google Scholar 

  • Ojo D, Omikunle O, Oduwaye O, Ajala M, Ogunbayo S (2006) Heritability, character correlation and path coefficient analysis among six inbred-lines of maize (Zea mays L.). World J Agric Sci 2:352–358

    Google Scholar 

  • Rattray A (1988) Maize breeding and seed production in Zimbabweup to 1970. In:Proceedings of the Eighth South African Maize Breeding Symposium, Technical Communication, pp 14–16

  • Rebourg C, Gouesnard B, Charcosset A (2001) Large scale molecular analysis of traditional European maize populations. Relationships with morphological variation. Heredity 86:574–587

    Article  CAS  PubMed  Google Scholar 

  • Robinson HF, Comstock RE, Harvey PH (1949) Estimates of heritability and degree of corn. J Agron 41:353–359

    Article  Google Scholar 

  • Toebe M (2013) Multicollinearity in path analysis of maize (Zea mays L.). J Cereal Sci 57:453–462

    Article  Google Scholar 

  • VSN International (2011) GenStat for Windows, 14th edn. VSN International, Hemel Hempstead

    Google Scholar 

  • Warner JN (1952) A method for estimating heritability. Agron J 44:427–430

    Article  Google Scholar 

  • Wolf D, Peternelli L, Hallauer A (2000) Estimates of genetic variance in an F2 maize population. J Hered 91:384–391

    Article  CAS  PubMed  Google Scholar 

  • Wray N, Visscher P (2008) Estimating trait heritability. Nat Educ 1:1–16

    Google Scholar 

  • Yan W, Wallace DH (1995) Breeding for negatively associated traits. Plant Breed Rev 13:141–178

    Google Scholar 

Download references

Acknowledgements

We thank the Crop Breeding Institute (CBI) of Zimbabwe for providing germplasm. Ms Fikile N.P. Qwabe is also acknowledged for assisting with managing our winter nurseries at Makhathini Research Station.

Author information

Authors and Affiliations

  1. School of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Scottsville, P. Bag X01, Pietermaritzburg, 3209, South Africa

    Tatenda R. Musimwa & John Derera

Authors
  1. Tatenda R. Musimwa
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. John Derera
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tatenda R. Musimwa.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Musimwa, T.R., Derera, J. Why SR52 is such a great maize hybrid? II. Heritability, correlation and path-coefficient analyses. Euphytica 213, 62 (2017). https://doi.org/10.1007/s10681-017-1851-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10681-017-1851-2

Keywords

Search

Navigation