Effect of sowing time x seed rate x herbicides on brome grass management in wheat

CC BY 4.0

Research organisatons
Funding source

Trial details

Researcher(s) Ben Fleet
Gurjeet Gill
Year(s) 2019
Contributor School of Agriculture, Food and Wine - The University of Adelaide
Trial location(s) Mallala, SA
Effect of sowing time x seed rate x herbicides on brome grass management in wheat locations

This field trial was undertaken at Mallala (SA) to investigate factorial combinations of sowing time, seed rate and herbicides on the management of brome grass in wheat.

Key messages

A field trial was undertaken at Mallala in 2019 to investigate combinations of wheat sowing time, seed rate and herbicide treatments to control brome grass. The average seedbank of brome grass at this site was 2877 ± 406 seeds/m2. The two week delay in sowing reduced average in-crop brome density from 567 plants/m2 to 352 plants/m2 (38%). Even though the reduction in brome density at Mallala was significant, it was a much lower reduction than that observed in the trial at Riverton (82% reduction). This difference in brome grass density with delayed sowing at these two sites highlights the large differences in seed dormancy between the populations of this weed species. Brome grass panicle density was significantly affected by wheat seed rate (P=0.039), and herbicide treatment (P<0.001) but not by the time of sowing (P=0.152). Increasing seed rate of wheat suppressed brome grass growth and reduced its panicle density. As wheat density increased from 100 seeds/m2 (low) to the highest seed rate (200 seeds/m2 – high) brome panicle density was reduced by 39%. These results support previous findings that higher crop density can be an important part of an integrated weed management program. Wheat grain yield increased consistently with the increase in seed rate or crop density. This trend correlates well with the improved suppression of brome grass panicle density observed in the trial. Not only did higher wheat density achieve superior weed suppression, it also provided a significant increase in grain yield. Herbicide treatments also had a highly significant effect on brome grass panicle density. However, there was no interaction herbicides and TOS or seed rate. This indicates that herbicides performed similarly in both times of sowing and the three seed rates. Sakura + Avadex significantly reduced panicle density as compared to Treflan + Avadex and Intercept (Clearfield technology) was used after pre-emergent Treflan + Avadex, it prevented brome plants from producing panicles (3 panicles/m2). Herbicide treatments had a large and significant effect on grain yield of wheat at Mallala (Figure 5). This is not surprising considering the high weed density present at the site and high competitive ability of brome grass. The treatment of Treflan + Avadex produced only 1.11 t/ha, which was significantly lower than the more expensive pre-emergent herbicide mixture of Sakura + Avadex (1.81 t/ha). However, when Intercept post-emergence herbicide was used, wheat yield increased further to 2.63 t/ha. In this trial, integration of Clearfield technology with pre-emergent herbicides not only prevented brome grass seed set as shown but the panicle density, it also delivered the highest grain yields.

Lead research organisation The University of Adelaide
Host research organisation N/A
Trial funding source GRDC 9175134
Related program N/A

We thank GRDC for funding this research project.

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


Crop types Weed: Brome grass Cereal (Grain): Wheat
Treatment type(s)
  • Herbicide: Type
  • Sowing: Rate
  • Sowing: Timing
Trial type
Trial design

Mallala 2019 Brome grass

Sow date Not specified
Harvest date Not specified
Plot size Not specified
Plot replication Not specified
Other trial notes

Please refer to the attached PDF document for detailed information on the results and discussion.

Mallala 2019 Wheat

Sow date 16 May and 31 May
Harvest date Not applicable
Plot size Not specified
Plot replication Not specified
Other trial notes

Please refer to the attached PDF document for detailed information on the results and discussion.

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
Mallala, SA Not specified
Derived trial site soil information
Australian Soil Classification Source: ASRIS
Trial site Soil order
Mallala, 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 Mallala SA
2019 386.2mm
2018 450.0mm
2017 523.0mm
2016 461.1mm
2015 442.5mm
2014 500.4mm
2013 481.1mm
2012 497.5mm
2011 533.7mm
2010 495.1mm
2009 452.9mm
2008 455.9mm
2007 506.8mm
2006 518.9mm
2005 531.9mm
2004 499.7mm
2003 497.3mm
2002 474.8mm
2001 527.0mm
2000 518.3mm
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



Derived climate information

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

Mallala SA


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 report and links

2019 trial report

Trial last modified: 20-03-2023 16:17pm AEST