Can I test management strategies for weedy oats

Weedy oats species have lifecycles and growth patterns similar to those of winter cereals, making them highly competitive with crops in the absence of effective control measures.

Now, if you have a theory about how to manage Avena spp. (aka wild or black oats), you can put it to the test on your computer before spending any money.

Dr Michael Walsh, weeds researcher formerly with the University of Sydney, says the newly released Avena Integrated Management (AIM) model allows growers and agronomists to test the effects of various wild oat management scenarios applied during a crop rotation on weed population dynamics and crop gross margins.

“AIM predicts the effect on crop yield, emerged weed numbers, weed seedbank and gross margins for each management scenario tested,” he says. “Users can then test multiple scenarios with different crop rotations and management strategies to compare the impact of these different options. Then they can implement the strategy that best suits their farm and business.”

“It is a great way of comparing the longer-term impact of different single and multiple control techniques.”

AIM is the newest in a suite of similar tools, all based on the widely tried and tested RIM model for annual ryegrass management. Similar models are available for brome grass, barnyard grass and barley grass.

“The AIM model was rigorously tested against real-world data collected in a wheat and sorghum cropping rotation trial,” says Michael. “The model reliably predicted the effectiveness of both individual and integrated weed management tactics on a wild oat population.”

The purpose of the WeedSmart Big 6 is to develop robust weed management strategies that help growers maximise crop competitiveness and reduce the weed seed bank. Predictive tools like AIM take much of the guesswork out of the complex analysis of management options. The AIM model can be downloaded from the Australian Herbicide Resistance Initiative (AHRI) website.

Can I test options for managing herbicide-resistant populations?

Members of the Avena family are widespread and problematic weeds in Australian grain cropping systems. For example, sterile oat (Avena ludoviciana) is the northern region’s most competitive grass weed in cereal crops, costing growers more than 20 thousand tonnes in yield loss and a revenue loss of $4.5 million annually.

Resistance to herbicides from Group 1 [A], 2 [B], 9 [M], and 0 [Z] is known, increasing the importance of protecting the efficacy of the few remaining herbicide options.

AIM does not predict herbicide resistance evolution, but existing (or expected) resistance can be simulated by changing the efficacy rating of a particular herbicide during the scenario rotation.

What parameters can I define for my farm and weed management options?

AIM models scenarios over a 10-year period, with options for various crop species and fallow or pasture phases in a rotation. The available crops are wheat, chickpeas, canola, faba beans, another legume, sorghum, winter fallow, and pasture (sheep grazing).

The user can include one application of the following tactics in their simulation per season: pre-planting knockdown (2 choices), pre-planting double knock (1 choice), pre-emergence herbicide (5 choices), post-emergence (5 choices and up to 3 applications), pre-harvest seed set control (e.g. crop-topping (2 choices), green/brown manuring, hay, silage) and harvest weed seed control (2 choices). The model will ‘apply’ each of these tactics at the optimal timing within the wild oat lifecycle and apply the correct efficacies and costs accordingly.

Multiple scenarios can be built and compared within the model. There is no recipe for eradication of wild oats – the key is to use as many weed control tactics as possible over time to target the weed at different times during a crop rotation.

Can I see the costs of implementing different strategies?

There is usually a trade-off between weed pressure (i.e. yield penalty) and the cost of control. AIM provides the gross margins for each crop in the simulated rotation based on expected yield and control costs. An informative scenario to include is an ‘inadequate weed control’, such as no-till and no herbicide, to demonstrate the value of weed control tactics for wild oat.

Testing scenarios that include seemingly costly tactics such as green or brown manuring or more expensive herbicides can identify the potential weed control returns from that investment. In these scenario tests, many background assumptions are included in the model, such as the expected efficacy of treatments, production potential, rotation effects and so on. These assumptions can also be changed to investigate the consequences of scenarios such as a failed control treatment or poor growing season.

AIM doesn’t provide prescriptive answers for specific paddock management but can indicate likely outcomes answers to questions such as:

• Which combination of control options and rotations provides the best overall management system in the long term?
• How fast can a wild oat problem develop?
• How can I maintain my income if I cannot rely on herbicides?
• If a pasture phase is included, how long should it be for?
• Is a particular treatment (e.g. green manuring) a profitable practice? If so, under what circumstances?

AIM allows users to test how wild oat populations and gross margins evolve in response to different management choices.

GRDC investment code: US00084

More resources

Winter planted sorghum and weedy oat 

Sample results page from AIM analysis of two weed control scenarios over 10 years, showing the effect on weed population and weed control expenses.