Paddock Practices: New tool to help HRZ growers tackle yield gap
Author: Quinton McCallum | Date: 16 Aug 2018
Three new fertiliser decision-making tools have been produced to help growers in the high-rainfall zone of south-eastern Australia tackle the problem of yield gaps caused by nutrient limitations.
Inadequate nutrition has been found to be a major cause of yield gaps in cropping enterprises of the HRZ.
Agriculture Victoria soil research scientist Dr Malcolm McCaskill says wheat and canola yields in the southern region HRZ are well below their water-limited potential.
To help growers in the HRZ achieve the most profitable yields, the three Excel-based decision support tools have been produced thanks to a GRDC investment, Optimising the yield and economic potential of high input cropping systems in the HRZ.
Part of the project is helping grain growers determine the economic optimum application rate of nitrogen, phosphorous, potassium and sulfur under a range of conditions.
Through a series of nutrient response experiments led by Agriculture Victoria across the HRZ, researchers established that providing sufficient nutrients to soils with a low or marginal nutrient status can lead to wheat and canola yield equalling or exceeding their water-limited yield potential, except in cases of severe drought or waterlogging.
Dr McCaskill says the most common yield responses in these nutrient deficient trials were to nitrogen, followed by phosphorous, sulfur and potassium (Table 1).
Among the 12 experiments, there were no responses to copper or zinc. All trial sites were on land that was regularly cropped, apart from the long-term phosphate experiment at Hamilton, where soils of low phosphorus fertility were sought to develop response curves for applied fertiliser.
|Location||Year||Crop||Rainfall decile||Yield of 'all'||Yield gap if a nutrient is omitted|
|Hamilton (long-term phosphate)||2017||Canola||7||6.3||N (29%), P (94%)|
|Bool Lagoon||2017||Wheat||10||4.7||P (17%)|
|Hamilton||2016||Canola||10||6.2||N (83%), K (17%)|
|Rutherglen||2016||Canola||10||0.7*||N (67%), P (22%), S (32%)|
|Bool Lagoon||2016||Wheat||10||4.6||N (59%), P (24%), S (22%)|
|Bool Lagoon||2016||Canola||10||1.4||N (41%), P (38%), S (30%)|
|Bool Lagoon||2015||Wheat||1||3.6*||N (3%)|
|Inverleigh||2015||Canola||1||1.8||N (20%), P (17%)|
*yields constrained by drought (2015) or waterlogging (2016, 2017)
Dr McCaskill says several of these experiments were affected by prolonged waterlogging including Bool Lagoon in 2016 and 2017 and Rutherglen in 2016.
“Wheat at Bool Lagoon in 2017 was inundated continuously from mid-July until mid-November, but still yielded 2.6 tonnes per hectare,” he says.
Many of the experiments had statistically significant responses to nitrogen, phosphorous, potassium and sulfur, but not the micronutrients copper or zinc.
Dr McCaskill says the critical soil test value used to estimate economic optimums varies depending on yield potential.
“Economic analysis has showed that the critical soil test values used in the medium and low rainfall areas underestimate the economic optimum in the HRZ because of the higher yield potential,” Dr McCaskill says.
“The critical soil value is typically the nutrient level that produces 90 per cent of maximum yield, and estimates the economic optimum, above which the cost of extra fertiliser applications is not paid by the extra yield produced.”
“However, crop yield potential is much greater in the HRZ than drier areas, and a critical figure of 95 per cent maximum yield may be more appropriate.”
Decision support tools
To help growers in the HRZ fulfil their crops’ yield potential, three different Excel-based decision support tools have been developed.
These tools use conventional marginal investment and return economics to calculate the optimum application rates of nitrogen, phosphorous, potassium and sulfur for a given set of input conditions, grain and fertiliser prices, and the user’s preferred benefit/cost ratio or rate of return on the marginal dollar invested in fertiliser.
The spreadsheets address three different questions important for nutrient management:
- Awareness: what is the likely response to in-crop nitrogen application based on the initial phosphorous, potassium and sulfur availability?
- In-season planning: what in-crop applications of nitrogen are required to fulfil yield potential based on seasonal forecasts?
- Post-season evaluation: Was the crop under-fertilised or over-fertilised given the seasonal conditions experienced?
According to Dr McCaskill, the three decision support tools have been prepared to help calculate the optimum nutrient supply under a wide range of conditions, since the economic optimum fertiliser application rate is also dependent on input prices, product price and seasonal outlook.
“While yield potential in the HRZ is generally high, it can vary enormously (Table 1), and this makes estimating nutrient demand and fertiliser decisions particularly difficult,” he says.
“The spreadsheets are populated with yield and nutrient response data from a bio-physical model but allows modification to suit individual circumstances.
The awareness tool is used pre-sowing and determines the profitability of nitrogen application based on background levels of phosphorous, potassium and sulfur, as well as seasonal outcomes and market prices.
The tool incorporates inputs such as crop type, location, initial soil fertility, yield potential, crop price at farm gate, the required return on marginal fertiliser investment, fertiliser delivery and spreading costs, and fertiliser nitrogen costs.
Based on those inputs, the spreadsheet provides optimum nitrogen applications, one with sufficient phosphorous, potassium and sulfur and one modelled on the initial phosphorous, potassium and sulfur scenario.
The tool then provides estimates of yield, total fertiliser costs, expected gross returns and an expected gain in profit from increased yield.
Dr McCaskill says they are seeking industry feedback so the fertiliser decision making tools can be developed and used with a higher level of confidence.
“One of the limitations at present is the tools are only populated with five sites in southern Victoria and the South East of SA, but we will be progressively adding further sites from other representative stations within the high-rainfall cropping zone,” he said.
“This is a prototype version for which we are seeking feedback as part of longer term development of decision support for nutrients.”
According to Dr McCaskill, the additional sites include ones being added at Skipton and Seaspray, Vic, and Campbell Town, Tas. He says any other site suggestions in high-rainfall zones are welcome.
As part of a follow-up project, Dr McCaskill is working with producers on large-scale strip trials, which will compare yields with those predicted by the model.
He says this will resolve the common problem of yields from small plots being greater than from entire paddocks, which arises because small-plot trials are usually located in the best part of the paddock.
In the long-term, Dr McCaskill says these tools could ensure much more effective and efficient use of fertiliser and give agronomists and growers a firm basis for their fertiliser decision making.
GRDC research code: DAV00141
Malcolm McCaskill, Malcolm.firstname.lastname@example.org, 03 5573 0957
The decision support tools can be downloaded at the eXtensionAUS website
GRDC Project code: DAV00141
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