Department of Primary Industries and Regional Development WA
Trial location(s)
Grass Patch, WA
Aims
To determine the optimum sowing date and variety combinations to maximise yield and quality of wheat in WA.
Key messages
The highest yielding treatment was Calibre (RAC2721) sown on 28 April, achieving just over 4.6t/ha.
Yields of over 4t/ha were consistently achieved by mid-slow to slow maturing spring wheats sown on 14 April and quick to mid maturing spring wheats sown 28 April. This coincided with flowering occurring during August.
Despite being sown onto field pea stubble with 75kg N/ha applied, high yielding (4+ t/ha) treatments rarely met APW1 protein specifications, indicating that at these high yields greater nitrogen applications are required to achieve premium milling grades.
Lead research organisation
Department of Primary Industries and Regional Development WA
Host research organisation
N/A
Trial funding source
DPIRD WA
Related program
N/A
Acknowledgments
This experiment has been conducted through the Crop Sowing Guide project, funded by DPIRD. Thanks to Chris Matthews and Helen Cooper from DPIRD Esperance for providing technical assistance.
Other trial partners
Not specified
Method
Crop type
Cereal (Grain): Wheat
Treatment type(s)
Sowing : Timing
Trial type
Experimental
Trial design
Replicated
Grass Patch 2021
Sow date
Not specified
Harvest date
Not specified
Plot size
Not specified
Plot replication
Not specified
Trial source data and summary not available Check the trial
report PDF for trial results.
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.
Grass Patch WA
NOTE: Exact trial site locality unknown - Climate data may not be accurate
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.