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|Contributor||West Midlands Group|
In Western Australia, break crop options are currently limited and there is a high proportion of wheat and barley grown in rotation. Cereal crops account for 60-70% of paddocks sown in any one year, with the remaining area sown to a range of crop and pasture types including canola, lupin, clover, volunteer pasture, or left as fallow. In addition, there is an interest in chickpea and lentil to add a high value legume to the crop rotation. The application of these break crops is dependent on the grain price per tonne and on the level of severity of biological constraints present that lead to a reduction in grain yield and which varies from paddock to paddock. The use of a single break crop in rotation has been shown to be an effective tool in managing both weed and diseases that affect wheat production to remove biological constraints to crop production and allow the sustained production of cereal crops. However, with a change in resistance status of many common weeds and diseases, and a change in soilborne pathogens, a single break crop applied to a cropping system that is largely based on cereals has limited effect in reducing the biological constraints, with the longevity of the break crop benefit being reduced. Recent studies into the break crop benefits for highly herbicide resistant weed populations has found that a break of at least two years was needed to prevent grass seed set and substantially reduce grass seedbank numbers.
Considering the high percentage of cereal crops grown in Western Australia, there is the need to evaluate the use of double break crop sequences to improve wheat grain yield and profitability. In particular, the Eastern Wheatbelt region has very limited break crop options, and there is the need to investigate the better use of tools such as fallow periods to improve break crop outcomes.
The success of break crops to increase wheat production in the Eastern Wheatbelt is dependent on firstly addressing any physical and chemical soil constraints to crop production and where the previous land use is a chemical fallow. In this situation, the grain yield of lupin, chickpea, lentil and field pea was 0.97-1.42 t/ha 0.67-1.1 t/ha, 0.3-0.97 t/ha, and 1.2 t/ha respectively in a below average season. The yield of wheat following legume break crops tended to be higher than either canola or wheat planted in the remaining paddock area. The profitability of double break-crop sequences was negative in many of the sequences evaluated in this study compared to a positive profit for continuous wheat. The profitability of double break-crop sequences can be improved by the inclusion of high value legumes as the second break-crop, but further work is required to lower the risk of growing these species of crops.The yield of wheat following legume break crops tended to be higher than either canola or wheat planted in the remaining paddock area. The profitability of double break-crop sequences was negative in many of the sequences evaluated in this study compared to a positive profit for continuous wheat. The profitability of double break-crop sequences can be improved by the inclusion of high value legumes as the second break-crop, but further work is required to lower the risk of growing these species of crops.
|Lead research organisation||
West Midlands Group
|Host research organisation||N/A|
|Trial funding source||GRDC WMG00003_A|
This project is a GRDC investment. Thank you to the Gillett, Harper, Even, Large, and Evans families for hosting trial sites for the lat three years. Thank you to the Corrigin Farm Improvement Group for managing the Corrigin demonstration site.
|Other trial partners||Corrigin Farm Improvement Group|
|Sow date||Not specified|
|Harvest date||Not specified|
|Plot size||Not specified|
|Plot replication||Not specified|
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.