Managing wheat yield and quality risks through plant density and nitrogen application

CC BY 4.0

Research organisatons
Funding sources

Trial details

Researcher(s) Melanie Kupsch (DAFWA)
Anne Smith (DAFWA)
Christine Zaicou-Kunesch (DAFWA)
Year(s) 2012
Contributor West Midlands Group
Trial location(s) Badgingarra, WA
Managing wheat yield and quality risks through plant density and nitrogen application locations

To determine value of agronomic management (sowing rate and nitrogen) on production of quality grain for profitable wheat systems.

Key messages
  • Cobra and Mace were significantly higher yielding than Emu Rock at all seeding densities (P<0.05). There was a yield increase for Emu Rock and Cobra when plant density increased from 83 plants/m2 to 130 plants/m². Further  increases in plant density did not improve or reduced grain yield of these varieties. There was a yield increase for Mace from 130 plants/m2 162 plants/m2. Increasing plant density did not influence grain screenings which were less than 2% for all varieties.
  • At Badgingarra, nitrogen application at seeding (14, 30, 60 and 90 kg/ha) did not affect grain yield at either seeding densities (data not provided).   The soil was a red sandy loam with nitrate levels in the top 20 cm of soil at 55mg/kg.   Protein levels in the grain were in excess of 12.5% for all treatments and varieties.  The higher split nitrogen application did significantly increase protein by 0.4% however without a yield increase the late N application was not economical.   This may be a strategy to consider for high yielding varieties such as Mace.  At the higher plant density, and higher yield, Mace had lower protein than Cobra and Emu Rock.  
Lead research organisation Department of Agriculture and Food WA
Host research organisation West Midlands Group
Trial funding source GRDC
Trial funding source DAFWA
Related program Tactical wheat agronomy for the west

Appreciate the support of the West Midlands Group with trial planning and preparation.   DAFWA’s technical services team for terrific trial management.  GRDC and DAFWA jointly support this research aiming to improve profitability of wheat production through the Wheat Agronomy Project DAW 218.

Other trial partners Not specified
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Crop type Wheat
Treatment type(s)
  • Sowing
Trial type Experimental
Trial design Replicated

Badgingarra 2012

Sowing machinery

Cone seeder.

Sow date 5 June 2012
Harvest date Not specified
Plot size 1.54m x 20m
Plot replication 3

100kg/ha Agstar Extra drilled and 25 kg/ha Muriate Potash topdressed at seeding.


2L/ha Sprayseed +1L/ha @100 L/ha Irrigator Extend +118 g/ha Sakura + 1.5 L/ha Treflan IBS.

Download the trial report to view additional method/treatment information
Trial source data and summary not available
Check the trial report PDF for trial results.
Observed trial site soil information
Trial site soil testing
Not specified
Soil conditions
Trial site Soil texture
Badgingarra, WA Brown red sandy loam
Derived trial site soil information
Australian Soil Classification Source: ASRIS
Trial site Soil order
Badgingarra, WA Chromosol
Soil Moisture Source: BOM/ANU
Average amount of water stored in the soil profile during the year, estimated by the OzWALD model-data fusion system.
Year Badgingarra WA
2012 236.0mm
2011 224.8mm
2010 209.6mm
2009 228.5mm
2008 246.8mm
2007 198.9mm
2006 196.0mm
2005 242.6mm
2004 204.2mm
2003 230.9mm
2002 212.7mm
2001 192.5mm
2000 206.7mm
National soil grid Source: CSIRO/TERN
NOTE: National Soil Grid data is aggregated information for background information on the wider area
Actual soil values can vary significantly in a small area and the trial soil tests are the most relevant data where available

Soil properties



Badgingarra WA 2012

Observed climate information

Rainfall trial gsr (mm) 332mm

Derived climate information

Badgingarra WA

NOTE: Exact trial site locality unknown - Climate data may not be accurate

Some data on this site is sourced from the Bureau of Meteorology

SILO weather estimates sourced from
Jeffrey, S.J., Carter, J.O., Moodie, K.B. and Beswick, A.R. (2001). Using spatial interpolation to construct a comprehensive archive of Australian climate data , Environmental Modelling and Software, Vol 16/4, pp 309-330. DOI: 10.1016/S1364-8152(01)00008-1.

Trial last modified: 09-07-2019 15:45pm AEST