Grower group probes nitrogen decision-making

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Photo of Agrarian Management consultant Craig Topham addressing a field day

Agrarian Management consultant Craig Topham addresses a field day with a focus on crop nitrogen use efficiency as part of an RCSN Geraldton Port Zone-supported project. 

PHOTO: Mingenew Irwin Group

Matching crop inputs, especially nitrogen fertiliser, to soil type, soil moisture availability, yield potential, crop nutritional status and seasonal forecasts are important considerations for optimising crop returns and managing risk.

In Western Australia’s northern agricultural region, the Mingenew Irwin Group (MIG) has assessed modelling, measuring and observational tools to help growers achieve this objective. The research aimed to inform better decision-making for nutrient inputs, mainly for in-crop nitrogen applications, and local grain marketing.

The MIG-led project looked to improve grower understanding of nitrogen use efficiency (NUE) and soil-water interactions on major soil types, such as pale deep sand at Mingenew and Binnu, yellow deep sand at Mullewa, and red sand at Morawa.

Tools for the job

Nitrogen models and tools used by MIG to help with fertilliser decision-making.

  • iPaddock Yield app – yield forecasting, rainfall recorder;
  • French and Schultz ‘Broken stick’ – modified French and Schultz model, calculates water use efficiency;
  • Yield Prophet® – predicts yield based on Agricultural Production Systems Simulator (APSIM) model; and
  • Crop Manager – software interpretation system for yield forecast, soil andweather data.

Several local grower groups, plus Agrarian Management consultants and CSIRO researcher Yvette Oliver, contributed to the research, which was supported by the GRDC Regional Cropping Solutions Network (RCSN) Geraldton Port Zone group.

At each site, soil moisture probes were installed, the soil was characterised and soil nitrogen was measured to a depth of 80 centimetres in the soil at sowing in 2015. This helped provide an accurate picture of soil nitrogen and plant-available nitrogen in the soil profile.

Using this data, the Equii soil test model was applied to develop nitrogen response curves. Other models, including iPaddock Yield, French and Schultz’s ‘Broken stick’ and Yield Prophet®, were also used to estimate values for potential yield. 

The resulting nitrogen response curves helped tailor decisions for in-crop nitrogen application to meet a range of target yields, soil types and limitations, and grain marketing scenarios.&

MIG researcher Debbie Gillam says the profitability of nitrogen fertiliser applications is dependent on maximising NUE.

“We found the point where maximum nitrogen fertiliser recovery is achieved was, typically, not the most economical rate for applying nitrogen,” she says.

Agrarian Management consultant Craig Topham says the critical factor is how crops respond to additional units or kilograms of applied nitrogen. 

“What growers need to look for is the most economic point on the curve,” he says. “This is where it flattens out and additional profit from one extra unit of applied nitrogen is equal to – say – two times the value of that unit of applied nitrogen.”

Mr Topham says growers need to decide on the rate of return they aim to take from additional nitrogen inputs, such as a $2 return from $1 additional input. 

The investments at the lower end of the response curve will provide a far greater return than this two-for-one,” he says (see Figure 1).

Figure showing MIG Nitrogen response triasl – nitrogen rate

Figure 1: MIG Nitrogen response trials – nitrogen rate

SOURCE: Mingenew Irwin Group

“Then the return drops off as the response curve flattens out and – eventually – hits zero. As you move up the response curve, the risk on that additional investment also increases.” 

Ms Gillam says getting the most out of the modelling to help pinpoint optimum in-crop nitrogen levels requires information about paddock performance during the season (management regime, soil moisture and rainfall) as well as historical yield and rainfall data.

She says the MIG RCSN project found iPaddock Yield was the most reliable for predicting grain yield (using 31 July estimates for each soil type) with 77 per cent accuracy. The French and Schultz ‘Broken stick’ model predicted yield with 74 per cent accuracy. 

Modelling of soil test results at the start of the 2015 season indicated there would be yield benefits from a range of in-crop nitrogen application rates at each trial site. However, well-below-average rainfall (Decile 1) at all sites meant soil moisture, rather than nitrogen supply, was the main yield limitation.

Yield prediction modelling and data analysis showed a zero rate of nitrogen would be most cost-effective at three sites, and 20 units of nitrogen was the most cost-effective rate at the Morawa site. 

Further results from each site are available at the GRDC Online Farm Trials website.

More information:

Debbie Gillam, MIG,
0427 281 006,


Business focus


Data builds on WAs deep rippping experience

GRDC Project Code MIG00015

Region West