Optimising Soil Acidity Management with iLime: A Validated Bioeconomic Decision Support Tool
Tracks
| Thursday, July 24, 2025 |
| 10:00 AM - 10:12 AM |
Overview
Speaker
Ms Jenni Clausen
Senior Research Scientist
Department of Primary Industries and Regional Development
Optimising Soil Acidity Management with iLime: A Validated Bioeconomic Decision Support Tool
Abstract
Soil acidity is a major constraint to grain production in Western Australian sandy soils. While most grain farmers test soil pH and apply lime, state-wide application rates remain below the estimated requirement to remediate the soil.
Analysis of soil samples collected from farm paddocks between 2005–2012 found that 70% of surface soil and 50% of subsurface soil was below minimum recommended targets for pH (Gazey, Andrew, and Griffin, 2013). Samples collected between 2020-2023 from paddocks in a more limited area found that 44% of surface soil and 37% of subsurface soil was below minimum recommended targets (Butler et al., 2023).
Constraints to managing soil acidity include the cost of applying lime, ameliorating subsurface acidity, prioritising lime applications across the farm, and confidence in the economic return from liming.
An app to assist lime management decisions was released in 2019. iLime models acidification processes and balances them against lime dissolution and movement through the soil profile. The dynamic model integrates economic analysis to evaluate investment decisions by comparing two lime sources and application strategies.
Outputs include return on investment calculations and 20-year projections for yield, cashflow, and pH changes across three depths.
iLime's pH outputs have been compared with data from field trials and farm paddocks. The predicted soil pH matched closely to data from five long-term trials (r2 = 0.8) and observed changes from paddocks with 5-30 year liming histories (Butler et al., 2023). In both cases, there was limited information available to parameterise the model.
This presentation describes iLime’s development and validation against field experiments and farm data, including recent research with deep lime incorporation.
iLime provides farmers and advisors with an accessible decision-support tool that demonstrates both historical liming value and optimal future strategies. The model’s realistic pH forecasting supports sustainable soil management through economically optimised liming strategies.
Analysis of soil samples collected from farm paddocks between 2005–2012 found that 70% of surface soil and 50% of subsurface soil was below minimum recommended targets for pH (Gazey, Andrew, and Griffin, 2013). Samples collected between 2020-2023 from paddocks in a more limited area found that 44% of surface soil and 37% of subsurface soil was below minimum recommended targets (Butler et al., 2023).
Constraints to managing soil acidity include the cost of applying lime, ameliorating subsurface acidity, prioritising lime applications across the farm, and confidence in the economic return from liming.
An app to assist lime management decisions was released in 2019. iLime models acidification processes and balances them against lime dissolution and movement through the soil profile. The dynamic model integrates economic analysis to evaluate investment decisions by comparing two lime sources and application strategies.
Outputs include return on investment calculations and 20-year projections for yield, cashflow, and pH changes across three depths.
iLime's pH outputs have been compared with data from field trials and farm paddocks. The predicted soil pH matched closely to data from five long-term trials (r2 = 0.8) and observed changes from paddocks with 5-30 year liming histories (Butler et al., 2023). In both cases, there was limited information available to parameterise the model.
This presentation describes iLime’s development and validation against field experiments and farm data, including recent research with deep lime incorporation.
iLime provides farmers and advisors with an accessible decision-support tool that demonstrates both historical liming value and optimal future strategies. The model’s realistic pH forecasting supports sustainable soil management through economically optimised liming strategies.
Biography
Jenni is a Research Scientist based at the Department of Primary Industries and Regional Development, Western Australia, and has eleven years’ experience in applied agricultural research and development, seven of those specialising in soil research and extension. She holds a BSc in Agricultural Science and GradDip in GIS and Remote Sensing.
Based in Northam and working across the WA Central Wheatbelt, Jenni contributes to the DPIRD-GRDC Soil Water and Nutrition (SWAN) Strategic Collaboration. Her work within the initiative includes developing soil management decision support tools, evaluating the long-term profitability of soil amelioration strategies, and supporting on-farm implementation of soil research.
