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Plant and Soil

, Volume 426, Issue 1–2, pp 227–239 | Cite as

Selection for rapid germination and emergence may improve wheat seedling establishment in the presence of soil surface crusts

  • Monia Anzooman
  • Jack Christopher
  • Michael Mumford
  • Yash P. Dang
  • Neal W. Menzies
  • Peter M. Kopittke
Regular Article
  • 151 Downloads

Abstract

Aims

Semi-arid cropping regions are commonly affected by surface crusting of sodic soils, resulting in reduced seedling emergence and grain yield. Although seedlings of different genotypes potentially differ in their ability to emerge through soil crusts, the underlying reasons for these differences remain unclear.

Methods

Seedling emergence of 38 genotypes of wheat (Triticum aestivum) was investigated in a crusting sodic soil in the glasshouse. Crusts of differing strength (0.78–2.69 kg/cm2 or 76–263 kPa) and thickness (0.51–2.16 cm) were created using simulated rainfall applied to a representative surface soil with 10% exchangeable Na.

Results

Wheat seedling emergence decreased as crust strength and thickness increased. For a strong crust, average emergence was 33%, compared to 87% for a weak crust. However, the rate of emergence differed significantly between the 38 genotypes, and it was found that seedlings that germinated comparatively earlier in non-constrained conditions tended to have a higher emergence through soil surface crusts.

Conclusion

The variability in emergence through soil crusts in seedlings of wheat suggests that genotype selection for improved adaptation may be possible. Rapid seed germination and emergence could potentially be used as a pre-selection criterion for genotypes adapted to soil crust.

Keywords

Genotypes Exchangeable sodium percentage (ESP) Crust simulation Crust strength Seedling 

Abbreviations

CEC

Cation exchange capacity

ESP

Exchangeable sodium percentage

EC

Electrical conductivity

TGW

Thousand grain weight

REML

Residual maximum likelihood

LSD

Least significant difference

eBLUEs

empirical best linear unbiased estimators

Notes

Acknowledgements

The authors wish to acknowledge funding and support from The University of Queensland, Department of Agriculture and Fisheries Queensland, the Australian Grains Research and Development Corporation (GRDC) and the grain producers of Australia. Support from the Australian Government Research Training Program Scholarship (Monia Anzooman) is also acknowledged.

Supplementary material

11104_2018_3609_MOESM1_ESM.docx (1.2 mb)
ESM 1 (DOCX 1178 kb)

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Agriculture and Food SciencesThe University of QueenslandSt LuciaAustralia
  2. 2.Queensland Alliance for Agriculture and Food Innovation, Leslie Research FacilityThe University of QueenslandToowoombaAustralia
  3. 3.Department of Agriculture and Fisheries, Queensland, Leslie Research FacilityToowoombaAustralia

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