Getting the nitrogen (N) supply to a crop ‘right’ in any one year is incredibly difficult, so that in any one year it is often ‘wrong’. The crop’s N demand is largely driven by the seasonal outcomes after you have had to make this decision, and hence you need a very good and trustworthy prediction of the potential seasonal outlook and/or yield to be able to tailor your N supply to that seasons outcome. Tools like YieldProphet are designed to help with getting a better idea of the likely yield outcomes as the season unfolds, but often there is still a large amount of uncertainty.
The below figure highlights that for different seasonal conditions how much the optimal N supply can vary, showing that getting this value ‘right’ from year to year is very difficult.
So, given this uncertainty the question is, can we find an N supply target (i.e. soil mineral N and fertiliser to be applied) that we could aim for year-in, year-out, that means we get the N rate we apply ‘less wrong’ more often.
That is, can we find an N supply rate that means that we reduce the opportunity cost when the season is positive and a higher N supply would have been better, while at the same time avoiding situations where we spend money on fertiliser that would not have given us a positive outcome.
Difference in optimal N supply required across different seasonal conditions. This ranges from low (e.g. 50 kg N/ha) in dry years (Decile 1) to 250 kg N/ha in wet years (Decile 9). Each of the orange lines depicted here has equal chance of being right in any one year.
To try to quantify this value, the RiskWi$e team have simulated using APSIM a range of N supply targets (i.e. combination of soil mineral N at sowing and fertiliser N inputs) over the long-term in order to estimate what target might be optimal in a range of situations.
How can I predict the optimal N supply target for me?
Simulations have been run across 50 sites spanning the cropping regions of Australia using soil types commonly found in each region. Drawing on this large amount of output we have developed a platform where users to select their location, and then explore the impact of different N supply targets on predicted yields, crop economics, N cycling and balances, GHG emissions over the long-term (60 years) across different soil types, soil carbon status and crop sequences.
ACCESS OUR RISKWI$E NITROGEN DECISION DASHBOARD HERE
The Dashboard enables users to specify and explore a wide range of outputs for a specific situation. These include:
- Distribution of crop yield, biomass, gross margin, fertiliser inputs across years
- Average responses of crop yield, relative yield and gross margin to N supply
- Response of yield and crop gross margin to N supply in different seasonal conditions (Decile 1, 3, 5, 7, and 9)
- Trade-offs between risk (i.e returns in worst 20% of years) compared to reward (long-term average)
- Shadow costs calculated as the difference in crop gross margin in a given year compared to the N rate producing the best result
- Predicted green-house gas emission implications due to nitrous oxide and changes in soil C
The dashboard also allows users to explore the sensitivity of responses to commodity prices, fertiliser costs, and soil organic carbon status.
Front page of the Dashboard allowing users to select their location, rotation, focus crop and soil type.
Choosing the best long-term N supply target
One of the key metrics that can help inform decision making from these long-term simulations is the annual shadow cost. This calculates for any one year what the best outcome would have been across the N supply values simulated and then compares how much below this ‘optimal’ option that N supply rate would have been (either due to a lower yield or costs of unneeded fertiliser).
The long-term simulations can provide an output of the size and probability of this shadow costs across a 60-year period. Here this is shown as a box and whisker plot the depicts the range of outcomes. The goal is to have as much of the box and shortest whiskers close to the zero – i.e. the lowest shadow costs across the full range of potential seasonal outcomes.
In the graph below the red box demonstrates the N supply target that minimises the shadow cost for this particular scenario. However, this value varies with production environment, crop sequence, and soil type.
This is how the RiskWi$e Nitrogen Decision dashboard can help define this target for your situation, so you can get your N supply ‘less wrong’, more often.
Example of the predicted shadow costs (i.e. difference between the best choice each year and what was achieved in that scenario) across increasing N supply targets. Box and whiskers present the range of potential outcomes and their probabilities as defined at percentile 5, 25, 50 (median), 75, and 95 (shown on right). The red box denotes the N supply target that minimises the size and frequency of sub-optimal outcomes compared to the impossible task of picking the best choice each year.