To evaluate yield and competition with weeds of new wheat cultivars selected by recurrent selection for early vigour compared to common commercial cereal cultivars.
To evaluate current commercial wheat varieties for their ability to suppress weed seed set and to yield under high weed pressure.
Key messages
Magenta and Baudin barley were the most competitive cultivars at Eradu, reducing ryegrass seed set by 65% compared to Wyalkatchem. UA40 reduced ryegrass seed set by 51% which was a similar result to UA47, Mace and Bonnie Rock. Leaf disease in UA47 reduced its competitive ability. The cultivar UA39 is a very tall variety, and visually it appeared to significantly compete with ryegrass. However, tiller counts and biomass measurements reveal that this cultivar is not as competitive as it appears.
While the UA cultivars may be useful as germplasm for future breeding programs, perhaps the most significant aspect of this research is the competitive ability of currently available cultivars. Magenta is a high yielding, competitive wheat variety that is a useful tool for weedy paddocks. Baudin Barley was very high yielding at Eradu and also very competitive with weeds. This weed competition of barley is consistent with past research. Future research will focus on ribbon / twin row seeding of competitive cultivars at higher seeding rates to maximise yield, profit and weed suppression.
Lead research organisation
Department of Agriculture and Food WA
Host research organisation
West Midlands Group
Trial funding source
GRDC
Related program
N/A
Acknowledgments
Thank you to GRDC for supporting this research. Thank you also to Dr Greg Rebetzke and Dr Gurgeet Gill for their expertise.
Trial source data and summary not available Check the trial
report PDF for trial results.
Climate
Eradu WA 2011
Observed climate information
Rainfall avg gsr (mm)
401mm
Derived climate information
Eradu WA
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.
