Advertisement

Cereal Research Communications

, Volume 45, Issue 2, pp 326–335 | Cite as

Hybrid Maturity Influence on Maize Yield and Yield Component Response to Plant Population in Croatia and Nebraska

  • J. Milander
  • Ž. Jukić
  • S. MasonEmail author
  • T. Galusha
  • Z. Kmail
Article

Abstract

Maize (Zea mays L.) yield component analysis is limited. Research was conducted in 2012 and 2013 at Zagreb, Croatia and Mead, Nebraska, United States with the objective to determine the influence of environment, hybrid maturity, and plant population (PP) on maize yield and yield components. Three maturity classes of maize hybrids were produced at five PP ranging from 65,000 to 105,000 plants ha−1 under rainfed conditions. Yield, ears m−2, rows ear−1, ear circumference, kernels ear−1, kernels row−1, ear length, and kernel weight were determined. Average yield was 10.7 t ha−1, but was variable for hybrids across PP. The early maturity-hybrids had lesser ear circumference, more kernels ear−1, greater ear length, and fewer rows ear−1 than mid- and late-maturity hybrids. Kernels ear−1 had the highest correlation with yield (r = 0.47; P < 0.01 for early-maturity hybrids; r = 0.55; P < 0.01 for the mid- and late-maturity hybrids). Path analysis indicated that ears m−2, kernels ear−1 and kernel weight had similar direct effects on yield for early-maturity hybrids (R = 0.41 to 0.48) while kernels ear−1 had the largest direct effect (R = 0.58 versus 0.32 to 0.36) for the midand late-maturity hybrids. Rows ear−1 had an indirect effects on yield (R = 0.30 to 0.33) for all hybrids, while kernels row−1 had indirect effect (R = 0.46) on yield for mid- and latematurity hybrids. Yield component compensation was different for early-maturity hybrid than the mid- and late-maturity hybrids, likely due to the proportion of southern dent and northern flint germplasm present in these hybrids.

Keywords

maize yield yield components path analysis 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Supplementary material

42976_2017_4502326_MOESM1_ESM.pdf (144 kb)
Hybrid Maturity Influence on Maize Yield and Yield Component Response to Plant Population in Croatia and Nebraska

References

  1. Abendroth, L.J., Elmore, R.W., Boyer, M.J., Marlay, S.K. 2011. Corn Growth and Development. PMR 1009. Iowa State Univ. Ext., Ames, IA, USA.Google Scholar
  2. Agrama, H.A.S. 1996. Sequential path analysis of grain yield and its components in maize. Plant Breeding 115:343–346.CrossRefGoogle Scholar
  3. Bavec, F., Bavec, M. 2002. Effects of plant population on leaf area index, cob characteristics and grain yield of early maturing maize cultivars (FAO 100-400). Eur. J. Agron. 16:151–159.CrossRefGoogle Scholar
  4. Brown, W.L., Anderson, E. 1947. The northern flint corns. Annuals of the Missouri Botanical Gardens 34:1–8.CrossRefGoogle Scholar
  5. Brown, W.L., Anderson, E. 1948. The southern dent corns. Annuals of the Missouri Botanical Gardens 35:255–276.CrossRefGoogle Scholar
  6. Cox, W.J., Hahn, R.R., Stachowski, P.J. 2006. Time of weed removal with glyphosate affects corn growth and yield components. Agron. J. 98:349–353.CrossRefGoogle Scholar
  7. Doebley, J., Wendel, J.D., Smith, J.S.C., Stuber, C.W., Goodman, M.M. 1988. The origin of corn-belt maize: The isozyme evidence. Economic Bot. 42:120–131.CrossRefGoogle Scholar
  8. Dofing, S.M., Knight, C.W. 1992. Alternative model for path analysis of small-grain yield. Crop Sci. 32:487–489.CrossRefGoogle Scholar
  9. Evans, S., Knezevic, S., Lindquist, J., Shapiro, C., Blankenship, E.E. 2003. Nitrogen application influences the critical period for weed control in corn. Weed Sci. 51:408–417.CrossRefGoogle Scholar
  10. Hammer, G.L., Dong, Z., McLean, G., Doherty, A., Messina, C., Schussler, J., Zinselmeier, C., Paskiewicz, S., Cooper, M. 2009. Can changes in canopy and/or root system architecture explain historical maize yield trends in the U.S. Corn Belt? Crop Sci. 49:299–312.CrossRefGoogle Scholar
  11. Hashemi, A.M., Herbert, S.J., Putnam, D.H. 2005. Yield response of corn to crowding stress. Agron. J. 97:839–846.CrossRefGoogle Scholar
  12. Milander, J.J., Jukic, Z., Mason, S.C., Galusha, T., Kmail, Z. 2016. Plant population influence on maize yield components in Croatia and Nebraska. Crop Sci. 56:2742–2750.CrossRefGoogle Scholar
  13. Mohammadi, S.A., Prasanna, B.M., Singh, N.N. 2003. Sequential path model for determining interrelationships among grain yield and related characters in maize. Crop Sci. 43:1690–1697.CrossRefGoogle Scholar
  14. Novacek. M.J., Mason, S.C., Galusha, T.D., Yaseen, M. 2013. Twin rows minimally impact irrigated maize yield, morphology, and lodging. Agron. J. 105:268–276.CrossRefGoogle Scholar
  15. Novacek. M.J., Mason, S.C., Galusha, T.D., Yaseen, M. 2014. Bt transgenes minimally influence maize grain yields and lodging across plant populations. Maydica 59:90–95.Google Scholar
  16. Reeves, G.W., Cox, W.J. 2013. Inconsistent responses of corn to seeding rates in field-scale studies. Agron. J. 105:693–704.CrossRefGoogle Scholar
  17. SAS Institute. 2014. SAS/STAT 9.3 User’s Guide. SAS Inst., Cary, NC, USA.Google Scholar
  18. Svečnjak, Z., Varga, B., Butorac, J. 2006. Yield components of apical and subapical ear contributing to the grain yield responses of prolific maize at high and low plant populations. J. of Agron. and Crop Sci. 192:37–42.CrossRefGoogle Scholar
  19. Westgate, M.E., Otegui, M.E., Andrade, F.H. 2004. Physiology of the corn plant. In: Smith, C.W., Betrán, J., Runge, E.C.A. (eds), Corn: Origin, History, Technology, and Production. John Wiley & Sons, Inc. Hoboken, NJ, USA. pp. 235–273.Google Scholar

Copyright information

© Akadémiai Kiadó, Budapest 2017

Authors and Affiliations

  • J. Milander
    • 1
  • Ž. Jukić
    • 2
  • S. Mason
    • 1
    Email author
  • T. Galusha
    • 1
  • Z. Kmail
    • 3
  1. 1.Department of Agronomy & HorticultureUniversity of NebraskaLincolnUSA
  2. 2.Department of Field Crops, Forage and Grassland, Faculty of AgricultureUniversity of ZagrebZagrebCroatia
  3. 3.Department of StatisticsUniversity of NebraskaLincolnUSA

Personalised recommendations