RECENT case studies have suggested a low level of precision was sufficient to maximise net return for nitrogen (N), phosphorus (P) and potassium (K) fertiliser.
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That was the key message from a presentation by Department of Primary Industries and Regional Development (DPIRD) senior research scientist Craig Scanlan at the virtual Grains Research and Development Corporation (GRDC) Grains Research Updates last month.
Optimising the application of N, P and K fertiliser is an ongoing challenge as grain producers are attempting to address multiple objectives.
They are trying to strike a balance between maximising their gross margins at a paddock or enterprise level, maximising the chance of capitalising on good years by removing nutritional constraints to yield and minimising the overall financial risk to their business in poor years.
Fertiliser recommendation systems - most commonly the sufficiency approach where fertiliser rates are adjusted to achieve a yield or profit target - are widely used in WA to assess the optimal fertiliser strategy based on assumptions about yield response to fertiliser, potential yield and fertiliser price.
Dr Scanlan said the sufficiency approach had its origins in soil test calibration curves for nutrient response where little or no yield response to a nutrient is expected above a certain soil test level.
"This is typically expressed as the critical range for 90 per cent of maximum yield, that is 10pc or less yield response to a nutrient is expected above its critical range," Dr Scanlan said.
"Soil test calibration curves are combined with predicted yield response to fertiliser in analytical models to predict the yield and profit response from applied nutrients.
"Presented as a dose response, this type of modelling allows the user to identify an optimal rate based on the highest point on the rate-net return response curve."
However, given the statistical uncertainty of economically optimum rates, and the flatness of rate-net return response curves, optimality may be more meaningful in terms of ranges rather than rates.
In a farming system, the goal of identifying an optimal fertiliser rate is further complicated by the interactions between different nutrients applied as fertiliser, soil properties, crop sequence, crop type and season.
It is likely that the optimal rate of a nutrient applied as fertiliser is influenced by those factors, as well as the level of soil supply of that nutrient.
With that in mind, Dr Scanlan and his team examined one component only of optimising fertiliser rate - the precision in rate required to maximise profit from N, P and K fertiliser - by drawing upon field research being completed or compiled in a current GRDC project.
"Our analysis suggested that a low level of precision of N, P or K fertiliser is sufficient to maximise net return," he said.
"Based on the case studies, fertiliser rates that are 20, 5 and 15 kilograms per hectare of the predicted optimum for N, P and K are likely to fall within the range of rates where maximum net return occurs.
"The range of rates that fall within the 90pc confidence interval may be greater than the values above as we have been conservative with our interpretation because in some cases the quadratic model did not provide a good fit to the rate-net return data."
The economic analysis also suggested the level of yield response to fertiliser had a greater impact on the optimal rate than grain or fertiliser price.
"We showed that the optimal rate increases as the level of yield response increases, and the sensitivity of optimal rate to grain or fertiliser price decreases," Dr Scanlan said.
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"Fortunately, the influence of yield response on optimal rates can be assessed using current decision support tools used by fertiliser advisors by assessing different scenarios of target yield and soil and residue nutrient supply."
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