Helen McMillan (CWFS): Co-operator, Jeff Bennett
|Contributor||Central West Farming Systems|
Mumbil Creek, NSW
To investigate the impact that stubble treatments (burning, cultivation, harrowed/flattened or standing stubble) imposed towards the end of the fallow have on the yield of winter crops.
Key Points from 2016
Burning or cultivating 2015 stubbles tended to produce higher yields, however this was only significant at Ungarie.
High rainfall and a soft finish removed the benefit of stored soil moisture that stubble retained systems may have provided.
Nitrogen was the limiting factor for both yield and protein for 2016.
Key Points from the Stubble Initiative
Growers cannot let stubble negatively impact on weed control and timely sowing.
Growers should use crop rotation to their advantage by aiming to sow the right crop into the least antagonistic stubble.
Stubble retained systems can require more nitrogen due to increased nitrogen tie-up.
|Lead research organisation||
Central West Farming Systems
|Host research organisation||N/A|
|Trial funding source||GRDC CWF00018|
Maintaining profitable farming systems with retained stubble
CWFS would like to acknowledge the support provided by the co-operating farmers, without their in-kind support the trials would not have been possible. The author also thanks Neil Fettell for his support in compiling this report. Lastly CWFS would like to acknowledge the GRDC for their generous support for research in the grains industry.
|Other trial partners||Not specified|
|Trial design||Blocked, randomised and replicated|
|Sow rate or Target density||35 kg/ha Livingston wheat|
|Sow date||23 May 2016|
|Harvest date||21 November 2016 21-11-2016|
|Plot size||110m x 40m|
|Plot replication||Not specified|
||Protein (%)||Grain yield (t/ha)||Screenings (%)||Biomass (kg/ha)|
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.