, Volume 185, Issue 3, pp 385–394 | Cite as

Genetic effects and genetic relationships among shrunken (sh2) sweet corn lines and F1 hybrids

  • K. F. Solomon
  • I. Martin
  • A. Zeppa


The objectives of this study were to quantify the components of genetic variance and the genetic effects, and to examine the genetic relationship of inbred lines extracted from various shrunken2 (sh2) breeding populations. Ten diverse inbred lines developed from sh2 genetic background, were crossed in half diallel. Parents and their F1 hybrids were evaluated at three environments. The parents were genotyped using 20 polymorphic simple sequence repeats (SSR). Agronomic and quality traits were analysed by a mixed linear model according to additive-dominance genetic model. Genetic effects were estimated using an adjusted unbiased prediction method. Additive variance was more important than dominance variance in the expression of traits related to ear aspects (husk ratio and percentage of ear filled) and eating quality (flavour and total soluble solids). For agronomic traits, however, dominance variance was more important than additive variance. The additive genetic correlation between flavour and tenderness was strong (r = 0.84, P < 0.01). Flavour, tenderness and kernel colour additive genetic effects were not correlated with yield related traits. Genetic distance (GD), estimated from SSR profiles on the basis of Jaccard’s similarity coefficient varied from 0.10 to 0.77 with an average of 0.56. Cluster analysis classified parents according to their pedigree relationships. In most studied traits, F1 performance was not associated with GD.


Correlation Diallel Genetic distance SSR Sweet corn Variance 



This study was funded by Horticulture Australia Limited (HAL) and Queensland Government as part of the project, VG07198. The assistance of Mrs. Veronique Keating in trial maintenance and data collection, and Dr. Jerome Franckowiak for useful comments on the manuscript is gratefully acknowledged.


  1. Alonso-Ferro RC, Malvar RA, Revilla P, Ordas A, Castro P, Moreno-Gonzalez J (2008) Genetics of quality and agronomic traits in hard endosperm maize. J Agri Sci 146:551–560CrossRefGoogle Scholar
  2. Amorim EP, Almeida CCD, Sereno M, Bered F, Neto JFB (2003) Genetic variability in sweet corn using molecular markers. Maydica 48:177–181Google Scholar
  3. Assuncao A, Brasil EM, de Oliveira JP, Reis AJD, Pereira AF, Bueno LG, Ramos MR (2010) Heterosis performance in industrial and yield components of sweet corn. Crop Breed Appl Biotechnol 10:183–190CrossRefGoogle Scholar
  4. Azanza F, Tadmor Y, Klein BP, Rocheford TR, Juvik JA (1996) Quantitative trait loci influencing chemical and sensory characteristics of eating quality in sweet corn. Genome 39:40–50PubMedCrossRefGoogle Scholar
  5. Badu-Apraku B, Fakorede MAB, Menkir A, Kamara AY, Adam A (2004) Effects of drought screening methodology on genetic variances and covariances in Pool 16 DT maize population. J Agri Sci 142:445–452CrossRefGoogle Scholar
  6. Benchimol LL, de Souza CL, Garcia AAF, Kono PMS, Mangolin CA, Barbosa AMM, Coelho ASG, de Souza AP (2000) Genetic diversity in tropical maize inbred lines: heterotic group assignment and hybrid performance determined by RFLP markers. Plant Breed 119:491–496CrossRefGoogle Scholar
  7. Betran FJ, Ribaut JM, Beck D, de Leon DG (2003) Genetic diversity, specific combining ability, and heterosis in tropical maize under stress and nonstress environments. Crop Sci 43:797–806CrossRefGoogle Scholar
  8. Brewbaker JL (2003) Corn production in the tropics: the Hawaii experience. University of Hawaii, ManoaGoogle Scholar
  9. Chen G, Zhu J, Wu J, Xu H, Lu Y (2004) QGAStation Version 1.0. Zhejiang University, HangzhouGoogle Scholar
  10. Doyle JJ, Doyle JL (1987) A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Photochem Bull 19:11–15Google Scholar
  11. Falconer DS, Mackay TFC (1996) Introduction to quantitative genetics, 4th edn. Longman Group Ltd., LondonGoogle Scholar
  12. Franco-Dixon MA (2009) An ex-post economic analysis of the Hybrix5 sweet corn breeding program in Queensland. Annual Conference of the Australian Agricultural and Resource Economics Society, Australia, CairnsGoogle Scholar
  13. Gerdes JT, Tracy WF (1994) Diversity of historically important sweet corn inbreds as estimated by RFLPs, morphology, isozymes, and pedigree. Crop Sci 34:26–33CrossRefGoogle Scholar
  14. Hallauer AR, Miranda JB (1988) Quantitative genetics in maize breeding. Iowa State University, AmesGoogle Scholar
  15. Has V (2003) Heritability of some yield components and kernel quality in sweet corn. Maize Genet Coop Newsletter 77:74–75Google Scholar
  16. Has V (2007) Genetic analysis of some yield components and kernel quality in sweet corn. Studium Press LLC, HoustonGoogle Scholar
  17. Has V, Has I (2009) Genetic inheritance of some important characters of sweet corn. Notulae Botanicae, Horti Agrobotanici, Cluj-Napoca 37:244–248Google Scholar
  18. Hintze JL (2000) Number cruncher statistical systems (NCSS). NCSS, KaysvilleGoogle Scholar
  19. Jaccard P (1908) Nouvelles recherches sur la distribution florale. Bull Soc Voud Sci Nat 44:223–270Google Scholar
  20. Jumbo MB, Carena MJ (2008) Combining ability, maternal, and reciprocal effects of elite early-maturing maize population hybrids. Euphytica 162:325–333CrossRefGoogle Scholar
  21. Kashiani P, Saleh G (2010) Estimation of genetic correlations on sweet corn inbred lines using SAS mixed model. Am J Agri Biol Sci 5:309–314CrossRefGoogle Scholar
  22. Khanduri A, Prasanna BM, Hossain F, Lakhera PC (2010) Genetic analyses and association studies of yield components and kernel sugar concentration in sweet corn. Indian J Genet Plant Breed 70:257–263Google Scholar
  23. Kwabiah AB (2004) Growth and yield of sweet corn (Zea mays L.) cultivars in response to planting date and plastic mulch in a short-season environment. Sci Hortic 102:147–166CrossRefGoogle Scholar
  24. Lertrat K, Pulam T (2007) Breeding for increased sweetness in sweet corn. Intl J Plant Breeding 1:27–30Google Scholar
  25. Liang W, Zhang S, Qi T, Qiu F, Tuo H, Liu Y, Zheng Y, Xu S (2006) Dissection of heritability and genetic variance components for yield traits in tropical and temperate maize populations. Sci Agric Sinica 39:2178–2185Google Scholar
  26. Marsan PA, Castiglioni P, Fusari F, Kuiper M, Motto M (1998) Genetic diversity and its relationship to hybrid performance in maize as revealed by RFLP and AFLP markers. Theor Appl Genet 96:219–227CrossRefGoogle Scholar
  27. Medici LO, Pereira MB, Lea PJ, Azevedo RA (2004) Diallel analysis of maize lines with contrasting responses to applied nitrogen. J Agri Sci 142:535–541CrossRefGoogle Scholar
  28. Melchinger AE, Boppenmaier J, Dhillon BS, Pollmer WG, Herrmann RG (1992) Genetic diversity for RFLPs in European maize inbreds:II. Relation to performance of hybrids within versus between heterotic groups for forage traits. Theor Appl Genet 84:672–681CrossRefGoogle Scholar
  29. Menkir A, Adetimirin VO, Yallou CG, Gedil M (2010) Relationship of genetic diversity of inbred lines with different reactions to Striga hermonthica (Del.) Benth and the performance of their crosses. Crop Sci 50:602–611CrossRefGoogle Scholar
  30. Miller RG (1974) The jackknife: a review. Biometrika 61:1–15Google Scholar
  31. Olsen JK, Blight GW, Gillespie D (1990) Comparison of yield. Aust J Exp Agric 30:387–393CrossRefGoogle Scholar
  32. Rana MK, Vinod K (2003) Combining ability analysis for yield and some growth characters in maize (Zea mays L.). Indian J Agric Res 37:219–222Google Scholar
  33. Rupp JV, Mangolin CA, Scapim CA, Machado MFD (2009) Genetic structure and diversity among sweet corn (su1-germplasm) progenies using SSR markers. Maydica 54:125–132Google Scholar
  34. SAS Institute (1999) SAS software version 6.12. SAS Institute, CaryGoogle Scholar
  35. Xu SX, Liu H, Liu GS (2004) The use of SSRs for predicting the hybrid yield and yield heterosis in 15 key inbred lines of Chinese maize. Hereditas 141:207–215PubMedCrossRefGoogle Scholar
  36. Yousef GG, Juvik JA (2002) Enhancement of seedling emergence in sweet corn by marker-assisted backcrossing of beneficial QTL. Crop Sci 42:96–104PubMedCrossRefGoogle Scholar
  37. Zhu J, Weir BS (1996) Mixed model approaches for diallel analysis based on a bio-model. Genet Res 68:233–240PubMedCrossRefGoogle Scholar
  38. Zivanovic T, Secanski M, Prodanovic S, Momirovic GS (2006) Combining ability of silage maize ear length. J Agri Sci 51:15–24CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.Department of Employment, Economic Development and Innovation (DEEDI)Hermitage Research Facility604 Yangan RdAustralia
  2. 2.Department of Employment, Economic Development and Innovation (DEEDI)Kairi Research FacilityKairiAustralia

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