Investment

Investment

GRDC Code: UOQ2204-010RTX
Predicting nitrogen cycling and losses in Australian cropping systems - augmenting measurements to enhance modelling
Fertiliser inputs represent about a third of the costs production for most grain producers, dominated by nitrogen (N) costing about $1.1 billion p.a. The proportion of fertiliser N recovered by the crop within the season it is applied is typically small and variable (often in the range of 25-70%), and in some cases we have a poor understanding of fertiliser N not accounted for in the soil, grain and crop residues at the end of the season, which is assumed to be lost from the system. This has implications for nutrient management and crop production with many rules of thumb used to estimate crop fertiliser N requirements assuming 50% of the N applied is lost. Moreover, intensively cropped soils have declining organic matter contents and many farms have negative N balances. An increasing reliance on fertilisers to supply N to cereals and canola often results in considerable amounts of mineral N in the soil that are prone to several loss pathways with potential to impact the environment, especially in high rainfall conditions. Regulations that restrict fertiliser N management have been introduced in Europe, New Zealand and other countries driven by concerns about the impacts of N losses on the environment e.g. ammonia losses, nitrates in water ways and greenhouse gas emissions. There are significant gaps in our knowledge of N cycling processes, losses and their impact on the environment in modern Australian cropping systems. More data is needed for key N pathways on a number of key soil types to: a) inform regulatory authorities and marketers of environmental impacts; and b) develop more informed fertiliser application strategies to optimise return on nutrient investments. Where N losses are significant, increasing N recovery by the crop will reduce the potential for losses and unwanted environmental impacts, boost production efficiency, and enhance the enduring profitability of grain production.
This five year investment will collect a comprehensive data set of N balance and cycling with explicit measurement of loss pathways to address key gaps in data for the most important soil types and farming systems across Australia's grain growing areas. A consortium of researchers, led by the University of Queensland will monitor N cycling and losses at key experimental sites and other trials for three seasons across WA, SA, Victoria, NSW and Qld. Detailed measurements at these key locations will serve as case studies that bring credibility to N cycling and losses for the grains industry. Extending detailed N measurements from a limited number of sites to represent the national grains industry as a whole will require the use of models. Consequently, these data will be also used to enhance and augment the relevant N routines in the APSIM NextGen crop and soil model which will then be used to make predictions of N loss and environmental impacts for grain production across Australia. A summary of the case studies, improved APSIM simulations and consequent implications for environmental impacts will be communicated to the grains industry, marketers, policy makers and researchers.
Project start date:
18/04/2022
Project end date:
01/06/2026
Crop type:
  • Wheat, (Cereal)
  • Barley, (Cereal)
  • Canola/Rapeseed, (Oilseed)
Organisation
The University of Queensland
Region:
North, South, West
Project status
status icon Active

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Predicting Nitrogen Loss – better data better decisions
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Darryl Anderson interviews Professor Mike Bell and Dr David Lester to find out about GRDC’s $11.9 million investment into predicting...

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Predicting Nitrogen cycling and losses in Australian cropping systems
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With water logging across paddocks, growers are at heightened risk of losing nitrogen from denitrification, and it’s an issue GRDC...

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Predicting Nitrogen Loss: Better data, better decisions

Predicting Nitrogen Loss: Better data, better decisions

1682431200000

GRDC is funding a collaborative, national research program that aims to provide the data needed to accurately predict nitrogen loss; as well as establish how...

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