Variable urea rates on sandy loam and deep sand

2011
CC BY 4.0

Research organisaton
Funding sources

Trial details

Researcher(s) Nicole Dimos (SPAA)
Linden Masters (EP Farming Systems)
Year(s) 2011
Contributor Society of Precision Agriculture Australia
Trial location(s) Kimba, SA
Variable urea rates on sandy loam and deep sand locations
Aims
  • To compare the effects of variable urea rate on two soil types.
  • To compare different rates of urea applied at GS30.
Key messages
  • Additional N did not have an economic advantage in this season.
  • Paddock and demonstration site suffered from the dry 6 weeks period mid season.
  • Stem rust devastated potential 3 ton crop reducing yield by 50%. This combination resulted in poor yields, low test weight and high screenings.
  • Good soil showed improved protein over deeper sand regardless of extra N applied.
  • Extra N marginally improved protein but not enough economically to apply more.
Lead research organisation Society of Precision Agriculture Australia
Host research organisation N/A
Trial funding source GRDC SPA000010
Trial funding source SPAA
Related program N/A
Acknowledgments

“The Soaks” property owners Dion, Bert Barb Woolford. Paddock and trial sown by Dion Woolford. Tim Moyle Landmark Kimba pegged trials and applied urea. Linden Masters MAC monitored plots and interpreted results. Leigh Davis and Brenton Spriggs SARDI reapt plots. Trials coordinator and FSG contact is Linden Masters


Other trial partners Not specified
Download the trial report to view additional trial information

Method

Crop type Wheat
Treatment type(s)
  • Fertiliser: Rate
Trial type Precision agriculture
Trial design Not applicable

Kimba 2011

Sow rate or Target density 50kg/ha
Sow date End of May
Harvest date Not specified
Plot size 2m x 20m
Plot replication Not specified
Fertiliser

50kg 18:20 at sowing; Control, 50kg, 100kg and 200kg urea hand spread at GS31

Download the trial report to view additional method/treatment information

Download results

Trial results Table 1

# Treatment 1
Treatment 2
Test weight (kg/hL) Protein (%) Grain yield (t/ha) Moisture (%) Screenings (%)
1 Sandy loam Urea @ 0 kg/ha 66.4 10.4 1.71 11.3 13.1
2 Sandy loam Urea @ 50 kg/ha 70.2 11.2 1.64 11.4 9.4
3 Sandy loam Urea @ 100 kg/ha 68.1 11.5 1.71 11.3 9.2
4 Sandy loam Urea @ 200 kg/ha 71.6 12.5 1.7 11.1 8.7
5 Deep sand Urea @ 0 kg/ha 59.8 10.1 1.49 11.4 141
6 Deep sand Urea @ 50 kg/ha 63.4 10.3 1.64 11.5 15
7 Deep sand Urea @ 100 kg/ha 68.8 10.6 1.51 11.6 7.6
8 Deep sand Urea @ 200 kg/ha 73.4 10.9 1.48 11.3 8.6

Grain yield t/ha


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Moisture %


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Protein %


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Screenings %


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Test weight kg/hL


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Observed trial site soil information
Trial site soil testing
Not specified
Soil conditions
Trial site Soil texture
Kimba, SA Not specified
Derived trial site soil information
Australian Soil Classification Source: ASRIS
Trial site Soil order
Kimba, SA Calcarosol
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 Kimba SA
2011 497.9mm
2010 470.5mm
2009 422.6mm
2008 398.5mm
2007 406.6mm
2006 398.0mm
2005 387.6mm
2004 398.3mm
2003 413.8mm
2002 426.7mm
2001 461.2mm
2000 428.5mm
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

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Climate

Derived climate information

No observed climate data available for this trial.
Derived climate data is determined from trial site location and national weather sources.

Kimba SA

NOTE: Exact trial site locality unknown - Climate data may not be accurate
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Some data on this site is sourced from the Bureau of Meteorology

SILO weather estimates sourced from https://www.longpaddock.qld.gov.au/silo/
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: 30-09-2019 16:18pm AEST