This project will provide information on within-paddock variation in soil pH and related soil properties, in different regions of the High Rainfall Zone (HRZ). To do this, we will map the horizontal and vertical variations in soil pH across 10 cropping paddocks in the Victorian HRZ. This will demonstrate to farmers how soil pH varies spatially and the economic benefits of targeting management of soil acidity to different zones within each paddock.
Key messages
Soil acidity affects up to 5.5 million hectares (50%) of Victoria’s agricultural land and soil acidification looms as a major soil
degradation issue (NHT 2001). Soil acidification can be seen is a cost of productive agricultural systems - whether from
product removal, increased potential for nitrate leaching, the build-up of soil organic acids, or from the increased use of
nitrogen fertilizers.
Soil acidity and acidification are mostly ameliorated by applying agricultural lime. Australian Bureau of Statistics (2018)
survey data show the average rate of application of lime is only about 1.5 t/ha, which is considerably less than the general
minimum recommendations of 2.5-7.5 t/ha (Agriculture Victoria 2019). Moreover, few Victorian farmers, about 1,000 (5%),
use variable rate application. Variable rate application is used to apply a wide range of agricultural chemicals, lime being
only one of many, so that the application rate is adjusted to match changing local requirements within the paddock. No
statistics are available on the application of variable rate technology for managing soil acidity, however service providers
supporting variable rate liming are increasingly active.
Agriculture Victoria Research (AVR) studied 10 case-study paddocks in the HRZ of Victoria to demonstrate the net
economic benefits of using intensive point sampling of surface soil pH and the precision application of lime in cropping
systems.
The initial pHCa distribution within each paddock was obtained by sampling at the rate of 100 soil cores per paddock
followed by spatial interpolation to a resolution of 10 square metres.
Discounted cash flow (DCF) analysis was used to generate profit-maximising lime 'prescriptions’ for each homogenous pH
zone (HZ) within the 10 case-study cropping paddocks, and to quantify the net benefits of the precision liming strategy.
These benefits were compared to alternative liming strategies, including traditional approaches and uniform application.
The analysis followed the best-practice method described by Mullen (2001). It involved optimization and simulation; and it
accommodated the dynamic nature of the acidity nature of the soil, in that production in the current year is affected by
current pH and in turn has an impact on pH in the next year.
It was shown that reaping the benefits of the precision liming strategy is difficult, because benefits depend on the
decisions made by farmers and their advisors requiring a high level of data collection and management, interpretation, and
judgement.
When acid tolerant crops are grown, the net benefits of liming can generally be maximised using low-cost traditional
practices. However, if the decision-maker wants the option of planting high-value, acid-sensitive crops then it would pay to
pursue a profit-maximising strategy involving intensive point sampling, pH mapping and variable rate application.
The DCF model described in this report demonstrates the nature of the data, analysis and interpretation involved in the
decision-making process. The model has been prototyped in MS Excel® and uses Evolver, an optimization add-in that is
part of Palisade’s DecisionTools Suite. The DCF model is available from the primary author on request and can be used
with attribution.
Lead research organisation
Agriculture Victoria Research
Host research organisation
N/A
Trial funding source
GRDC DAV00152
Trial funding source
AgVic
Related program
N/A
Acknowledgments
This research was funded through the Grains Research and Development Corporation (DAV00152) and the Victorian State Government. The generous assistance of Nathan Robinson (Federation University), Lisa Miller (SFS) and Kirsten Barlow (PA) and is gratefully acknowledged. The generosity of the farmers who allowed us to use their paddocks is also acknowledged.
Trial source data and summary not available Check the trial
report PDF for trial results.
Climate
Derived climate information
No observed climate data available for this trial. Derived climate data is
determined from trial site location and national weather sources.
Devenish VIC
Gatum VIC
Lilliput VIC
Maroona VIC
Miepoll VIC
Mininera VIC
Newlyn VIC
Seaspray VIC
Werneth VIC
Winnindoo VIC
Devenish VIC
NOTE: Exact trial site locality unknown - Climate data may not be accurate
Gatum VIC
NOTE: Exact trial site locality unknown - Climate data may not be accurate
Lilliput VIC
NOTE: Exact trial site locality unknown - Climate data may not be accurate
Maroona VIC
NOTE: Exact trial site locality unknown - Climate data may not be accurate
Miepoll VIC
NOTE: Exact trial site locality unknown - Climate data may not be accurate
Mininera VIC
NOTE: Exact trial site locality unknown - Climate data may not be accurate
Newlyn VIC
NOTE: Exact trial site locality unknown - Climate data may not be accurate
Seaspray VIC
NOTE: Exact trial site locality unknown - Climate data may not be accurate
Werneth VIC
NOTE: Exact trial site locality unknown - Climate data may not be accurate
Winnindoo VIC
NOTE: Exact trial site locality unknown - Climate data may not be accurate
SILO weather estimates sourced from https://www.longpaddock.qld.gov.au/silo/
Jeffrey, S.J., Carter, J.O., Moodie, K.B. and Beswick, A.R. (2001). Using spatial interpolation to
construct a comprehensive archive of Australian climate data , Environmental Modelling and Software, Vol
16/4, pp 309-330. DOI: 10.1016/S1364-8152(01)00008-1.