Question: What is the recycled content percentage in the SSAB cold-rolled steel sheets? Please provide numerical percentages.

ECO PLATFORM

'EPDⓇ

EPD

VERIFIED

Environmental Product Declaration

Cold rolled steel
sheets and slit coils

EPD of multiple products, based on the average results of the product group

SSAB

In accordance with ISO 14025:2006 and EN 15804:2012+A2:2019/AC:2021

Programme: The International EPD® System, www.environdec.com
Programme operator: EPD International AB

EPD owner: SSAB Europe Oy

EPD registration number: EPD-IES-0023966
Publication date: 2025-06-16

Valid until: 2030-06-04

Contents

1. General information

3

1.1 SSAB's vision - A stronger, lighter and more sustainable world
1.2 Company information

4

2. Product information

4

2.1 Product technical information and applications

4

2.2 Product description

4

2.3 Labeling and packaging

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3. Production and transportation

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5

3.1 Production sites

5

3.2 Transportation

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5

10

4. LCA

160

4.1 LCA information

4.2 Product content declaration

8

4.3 Environmental performance indicators results

8

5. References

11

2

1. General information

PROGRAM INFORMATION

The International EPDⓇ System

Program:

EPD International AB

Address:

Box 210 60

SE-100 31 Stockholm

Sweden

Website:

www.environdec.com

info@environdec.com

Email:

Accountabilities for PCR, LCA and independent, third-party verification

Product Category Rules (PCR)

Core product category rules: CEN standard EN 15804 serves as the core PCR.

Product category rules: PCR 2019:14 Construction products. Version 1.3.4. Date 2024-04-30.

Product group classification: UN CPC 412.

PCR review was conducted by: The Technical Committee of the International EPD System. See www.environdec.com for a list of members.
Review chair: Claudia A. Peña, University of Concepción, Chile. The review panel may be contacted via the Secretariat www.environdec.com/contact.
Life Cycle Assessment (LCA)

LCA accountability: Lisa Hallberg, IVL Swedish Environmental Research Institute.

Third-party verification

Independent third-party verification of the declaration and data, according to ISO 14025:2006, via:

> EPD verification by individual verifier

Third-party verifier: David Althoff Palm, Dalemarken AB.

Approved by: The International EPD® System

Procedure for follow-up of data during EPD validity involves third party verifier:

> Yes ☐ No

[Procedure for follow-up the validity of the EPD is at minimum required once a year with the aim of confirming whether the information in the EPD
remains valid or if the EPD needs to be updated during its validity period. The follow-up can be organized entirely by the EPD owner or together with
the original verifier via an agreement between the two parties. In both approaches, the EPD owner is responsible for the procedure being carried
out. If a change that requires an update is identified, the EPD shall be re-verified by a verifier]

The EPD owner has the sole ownership, liability, and responsibility for the EPD.

EPDS within the same product category but registered in
different EPD programmes, or not compliant with
EN 15804, may not be comparable. For two EPDs to
be comparable, they must be based on the same PCR
(including the same version number) or be based on
fully-aligned PCRs or versions of PCRs; cover products
with identical functions, technical performances and use
(e.g. identical declared/functional units); have equivalent

system boundaries and descriptions of data; apply
equivalent data quality requirements, methods of data
collection, and allocation methods; apply identical cut-
off rules and impact assessment methods (including
the same version of characterization factors); have
equivalent content declarations; and be valid at the
time of comparison. For further information about
comparability, see EN 15804 and ISO 14025.

3

1.1 SSAB'S VISION - A STRONGER,
LIGHTER AND MORE SUSTAINABLE
WORLD

Description of the organizations:

SSAB Europe is responsible for strip, heavy plate, and
tubular products in Europe as well as for the global
business in the Automotive customer segment. SSAB
Europe is also responsible for color coated products.

•

SSAB is a global steel company with a leading position in
high-strength steels and related services. The company
is a frontrunner in the green transformation of the steel
industry and aims to largely eliminate carbon dioxide
emissions from its operations and together with suppliers
and customers create a fossil-free value chain.
SSAB's production sites are in Sweden, Finland and
the USA and have an annual crude steel production
capacity of 8.8 million tonnes. SSAB Europe is responsible
for sales of strip, heavy plate, and tubular products
in Europe as well as for the global business in the
Automotive customer segment. SSAB Special Steels
has global responsibility for sales of SSAB's quenched
and tempered (Q&T) steels and advanced high-strength
steels (AHSS). SSAB Americas is the largest heavy plate
producer in North America and has a strong position
based on cost efficiency and quality.

Name and location of production sites:
⚫ SSAB EMEA AB (Luleå, Sweden):
Svartövägen 20, 974 37 Luleå (Sweden).

SSAB EMEA AB (Oxelösund, Sweden):
Aspleden 1, 613 80 Oxelösund (Sweden).

•

SSAB EMEA AB (Borlänge, Sweden):

•

Kontorsviksvägen 1, 781 84 Borlänge (Sweden).

• SSAB Europe Oy (Raahe, Finland):

•

Rautaruukintie 155, 92100 Raahe (Finland).

SSAB Europe Oy (Hämeenlinna, Finland):
Harvialantie 420, 13300 Hämeenlinna (Finland).

Certifications:

Certificates applicable to SSAB sites are ISO 14001 and
ISO 9001.

1.2 COMPANY INFORMATION

Contact:

EPD owner:

EPDssab@ssab.com.

SSAB Europe Oy, Kaisa Ahvonen, Harvialantie 420,
13300 Hämeenlinna, Finland.

2. Product information

For more detailed information about technical product
properties and the product portfolio, please visit
www.ssab.com.

2.1 PRODUCT TECHNICAL INFORMATION
AND APPLICATIONS

SSAB specializes in materials for demanding applications
where high strength and formability are needed for weight
savings and increased durability. Cold rolled steel sheets
and slit coils are used in many industries and applications,
including automotive industry, construction, light
engineering, domestic and electrical appliances, heating
and air conditioning equipments, storage systems, and
tubular products.

2.2 PRODUCT DESCRIPTION

The scope of this EPD is SSAB cold rolled blast furnace-
based steel sheets and slit coils.

The steel is an alloy of mainly iron and carbon and may
contain other alloying metals and trace elements. These
alloying elements improve the chemical and physical
properties of steel, such as strength, ductility, durability,
and corrosion resistance.

SSAB offers a comprehensive selection of steel
products that includes cold-forming steels, advanced
high-strength steels, complex phase steels, martensitic
steels, ultrahigh-strength steels, weather-resistant steels
and hardenable boron steels.
Cold rolled steel sheets and slit coils are produced in
a thickness range of 0.40-3.0 mm.

The exact composition of the steel manufactured by
SSAB depends on product requirements, either based
on national and/or international standards, such as
EN 10130, EN 10268, EN 10338, VDA 239-100, on
customer-specific and/or other OEM standards.
SSAB's unique products also have their own specific
requirements.

The products are often customized to meet national
and/or international standards as well as customer-
specific or other Original Equipment Manufacturer (OEM)
standards. Besides standardized steel grades, SSAB's
cold rolled product portfolio also includes products unique
to SSAB and which in some cases may be patented.

Content declaration and average chemical composition
are presented in section 4.2. More detailed information on
the different steel compositions is available from national
and international standards, and on www.ssab.com.

4

2.3 LABELING AND PACKAGING

SSAB products are labeled to be easily identifiable and
traceable. The packaging and protection type of SSAB
steel products is specified when ordering.

for cut-to-lengths packaging. The bundles are fastened
with strapping bands.
Depending on orders, coils can be delivered fastened
with or without a pallet, protected with cardboard or
laminated plastic, and plastic or metallic end rings,
metallic corner protection and strapping bands.

Steel bands or strappings, wood props, paper or plastic
film, corner protection and other accessories supporting
packaging are used as appropriate, depending on the
protection needed. Paper and plastic film are usually used

3. Production and transportation

3.1 PRODUCTION SITES

annealed and tempered, and cut-to-length or slitted at
SSAB Borlänge (Sweden).

Blast furnace-based steel slabs used for cold rolled steels
are typically manufactured at SSAB Luleå and at SSAB
Oxelösund in Sweden. Slabs are produced using iron ore
pellets and, as an energy source and reducing agent, coke
from coal, and injection carbon. These raw materials are
charged into a blast furnace to produce molten hot metal,
pig iron.
Steel scrap and alloying elements are then added to the
hot metal along with slag forming burnt lime, and oxygen
is blown through the mixture to convert it into liquid steel
in the basic oxygen furnace (BOF). The liquid crude steel
is then cast into slabs on a continuous casting line.

Pickling, cold rolling, batch annealing and tempering,
and cut-to-length or slitting can also be done at SSAB
Hämeenlinna (Finland) using SSAB hot-rolled coils
produced in Raahe (Finland).
Co-products, such as slag, mill scale and iron oxide,
generated in SSAB's steel production processes are
recycled as industrial raw materials or materials to
replace virgin resources. A high percentage of the
baghouse dust originating in various processes is
recycled to reduce waste and improve efficiency.

Blast furnace-based steel slabs are hot rolled, pickled,
cold rolled, continuous annealed and tempered or batch

FIGURE 1. SSAB main production sites and process steps for blast furnace-based cold rolled steel sheets and slit coils.
SSAB Cold Rolled Steel sheets and slit coils - main production processes

| Slabs

BOF Steel Making

Continuous Casting

Raw materials

Blast Furnace

SSAB LULEA-

品

SSAB OXELÖSUND

Scrap Lime Alloys

Iron ore

Lime

Coke

|Train

園

Hot rolling

Cold rolling

Cut-to-length or slitting

Pickling

Annealing and tempering

SSAB BORLÄNGE

SSAB

Cold rolled steel
sheets and slit

coils

Note: pickling, cold rolling, batch annealing and tempering, and cut-to-length or slitting can also be done at SSAB Hämeenlinna (Finland)
using SSAB hot-rolled coils produced in Raahe (Finland).

3.2 TRANSPORTATION

Borlänge. Hot rolled coils from SSAB Raahe are
transported by rail to SSAB Hämeenlinna.

Blast furnace-based steel slabs from SSAB Luleå and
from SSAB Oxelösund are transported by rail to SSAB

5

4. LCA

Time representativeness:

4.1 LCA INFORMATION

2023 for the steel slabs production at SSAB Oxelösund,
2023 for the steel slabs production at SSAB Luleå,
2021 for the steel slabs production at SSAB Raahe,
2022 for the steel processing at SSAB Borlänge,
2021 for the steel processing at SSAB Hämeenlinna.

Declared unit:
1 kg of product

Reference service life:

Not applicable

Database(s) and LCA software used:

Description of system boundaries:

The LCA was modelled using the LCA software LCA for
Experts and corresponding database (version 2024.1)
provided by Sphera.

The system boundaries are cradle-to-gate with modules
C1-C4 and module D.

System diagram:

Pre-consumer:
with burden (A1)

EoL of Core waste (A3)

SSAB Luleå,
Oxelösund,
Raahe:
Blast furnace
based steel
production
(A3)

Post-consumer:
burden-free (A1)

Internal scrap:
burden-free (A1)

Production of
iron ore, energy and
ancilliary materials
or chemicals (A1)

EoL of Core waste (A3)

Downstreams
at SSAB's sites
in Europe
(Sweden and
Finland) (A3)

Material

to module C

Waste processing,
steel (C3)

Credit,

steel (D)

The product
is assumed to
end up in steel
recycling

Deconstruction

Transport
(C2)

(C1)

Disposal,
steel (C4)

Module A1: Production of raw materials and production
of fuels

Module C1: Deconstruction of the product

•

•

• Module C2: Transport to waste processing and disposal
Module C3: Waste processing of the product, to be sent
to steel recycling

Module A2: Transportation of raw materials to SSAB's
manufacturing site (including transportation of steel
between SSAB sites)

•

Module C4: Disposal of the remaining part of the prod-
uct in a landfill

•

Module A3: Manufacturing of steel products and
management of production waste

•

Module D: Benefits from recycling the steel

•

Sweden and for Finland has been applied (corresponding
to a GWP-GHG impact of 0.07 kg CO2eq per kWh, and
0.5 kg CO₂eq per kWh, respectively), however 30% from
Hämeenlinna electricity is fossil free with GWP-GHG
impact of 0.0046 kg CO₂eq per kWh.

Allocation:

Pre-consumer scrap is used in the production of steel.
The environmental burden from the use of this scrap is
allocated based on economic value by making a
conservative assumption equal to 5% of virgin (blast
furnace-based) steel. This corresponds to a value of
0.1 kg CO,eq per kg of pre-consumer scrap.
Co-products from blast furnace and coke making
operations have been allocated based on economic
value as per PCR 2019:14. Similarly, impact associated
with internal energy generation have been allocated
based on economic value.

Scenario for module C1:

The product is being deconstructed by a machine pow-
ered by diesel.

Scenario for module C2:

The waste is transported 150 km by truck to waste pro-
cessing (C3) and disposal (C4).

Cut-off criteria:

Scenario for module C3:

98% of the product is assumed to be processed in order
to be sent for recycling.

The maximum cut-off criteria established by the PCR and
EN 15804:2012+A2:2019 standard is 1% of all material
and energy flows to a single unit process and 5% of total
inflows (mass and energy) to the upstream and core
module. No cut-offs exceeding this limit have been made.

Scenario for module C4:

2% of the product is assumed to be disposed of as waste
at a landfill.

Inclusion of infrastructure and capital goods:
Infrastructure and capital goods are not included in any
of the modules covered in this EPD. For the electricity
sources of renewable origin (within the residual mix),
the infrastructure of the power plant is included.

Scenario for module D:

The environmental benefit of the recycled steel is gained
through the avoided production of primary steel. This
benefit corresponds to -1.7 kg CO2eq per kg of scrap in
module D. The net flow of the recycled steel being credit-
ed in module D corresponds to 0.86 kg and is based on an
assumed recycling rate of 98% and an assumption of yield
losses in the steel recycling process.

Electricity information:

At SSAB Oxelösund, SSAB Luleå, and SSAB Raahe
some of the electricity used is produced internally
(corresponding to a GWP-GHG impact of 0.62, 0.36 and
2.03 kg CO₂eq per kWh, respectively). At SSAB Borlänge
and SSAB Hämeenlinna, only external electricity is used.
For external electricity, the residual electricity mix for

Weighted average for the EPD:

The results represent a weighted average based on the
production volumes for the product group.

Modules declared, geographical scope, share of specific data (in GWP-GHG indicator) and data variation

Life cycle stage

Specific
data used

Variation -
products

Variation -
sites

Module

Modules
declared

Geography

EU, SE & FI

Raw material supply
Transport

A1

X

+ 8%
- 1%

Product stage

EU, SE & FI

<10%

A2

76%

X

SE & FI

Manufacturing

A3

X

Transport

A4

ND

Construction
process stage

Construction installation

A5

ND

Use

B1

ND

B2

Maintenance

ND

Repair

B3

ND

Use stage

Replacement

B4

ND

Refurbishment

B5

ND

Operational energy use

B6

ND

Operational water use

B7

ND

De-construction demolition

C1

X

EU

Transport

C2

X

EU

End of life stage

Waste processing

C3

X

EU

Disposal

ཙུ。
C4

X

EU

Resource recovery stage Reuse-Recovery-Recycling-potential D

X

EU

X: Module Declared

ND: Module not declared

7

4.2 PRODUCT CONTENT DECLARATION

Pre- and postconsumer scrap content is 4.1%.
Recycled material content with internal scrap is 18.9%.

Content declaration and average chemical composition of
cold rolled steel sheets and slit coils per kg produced is:

Product Composition

Weight (%)

Biogenic carbon,
weight (%)

Weight (kg)

Biogenic carbon,
weight (kg)

Pre-consumer scrap

0.021

0%

0

2.1%

Post-consumer scrap

0.020

2.0%

0%

0

Internal scrap

0.148

0%

0

14.8%

Primary steel

81.2%

0.812

0%

0

Average chemical composition*

Iron (Fe)

> 97%

Manganese (Mn)

0.6%

Silicon (Si)

0.3%

Carbon (C)

0.1%

< 1.5%

Other

* The figures provided represent the best estimate at the time of publication.

Content Declaration of renewable
packaging material

Weight (kg)

Weight %
(of product)

Biogenic carbon, weight
(kg/declared unit)

0.0030

Wood

0.30%

0.0013

The production of the packaging materials has been
omitted since it falls under the cut-off limit. The content
of biogenic material in the packaging is 0.0013 kg per kg
of steel.

4.3 ENVIRONMENTAL PERFORMANCE

INDICATOR RESULTS

The estimated impact results are only relative statements,
which do not indicate the endpoints of the impact
categories, exceeding threshold values, safety margins
and/or risks. Usage of results from A1-A3 without

Cold rolled steel sheets and slit coils do not contain
any of the substances of very high concern (SVHC)
regulated by Regulation (EC) No 1907/2006 (REACH)
or Regulation (EC) No 1272/2008 of the European
Parliament and of the Council.

considering the results of module C is not encouraged.

80

Potential environmental impact - mandatory indicators according to EN 15804+A2 (version EF 3.1)

Results per declared unit: 1 kg of product

Indicator

A1-A3

Unit

C2

D

C1

C3

C4

Climate Change - fossil

kg CO₂ eq

2.17

4.39E-04

1.01E-02 2.71E-03 2.99E-04

-1.49

8.16E-04 1.34E-06 2.68E-05 1.01E-05 9.52E-07 3.16E-04

Climate Change - biogenic

kg CO₂ eq

Global warming
potential (GWP)

Climate Change - land use and land

7.31E-06 8.61E-05 3.66E-05 1.80E-06 -1.98E-04

kg CO₂ eq

4.81E-04

use change (LULUC)

Climate Change - total

2.17

kg CO₂ eq

4.47E-04

1.03E-02 2.76E-03 3.02E-04

-1.49

Depletion potential of the stratospheric ozone layer (ODP) kg CFC-11 eq

1.34E-18 4.89E-15 8.08E-16 2.00E-12

6.00E-12

4.39E-17

Acidification potential (AP)

mole H+ eq

1.18E-05 1.36E-05 2.13E-06 -3.64E-03
-3.47E-07
1.35E-03 1.49E-06 3.93E-06 6.24E-06 5.47E-07 -5.85E-04

4.76E-03

3.01E-06

kg P eq

Freshwater

7.71E-07

1.86E-09

3.12E-08 1.05E-08 6.80E-10

Eutrophication
potential (EP)

Marine

kg N eq

Terestrial

mole N eq

-5.24E-03
1.67E-06 -2.38E-03

1.43E-02 1.65E-05

4.74E-05

6.90E-05 6.03E-06

Formation potential of tropospheric ozone (POCP)

kg NMVOC eq

2.89E-06 1.01E-05

3.78E-03

1.73E-05
2.84E-09
5.07E-02 3.95E-03

kg Sb eq

3.71E-11 8.05E-10

Abiotic

Minerals and metals*

7.64E-06

1.94E-11 -8.43E-06

depletion

Fossil resources*

28.7

0.140

MJ

5.68E-03

-14.8

potential (ADP)

Water scarcity potential (WDP)*

m³

5.18E-04

-0.100

6.48E-06 9.13E-05

0.179

3.43E-05

*Disclaimer: The results of this environmental impact indicator shall be used with care as the uncertainties of these results are high or as there is limited
experience with the indicator.

Note: Biogenic carbon in packaging is balanced in A1-A3.

Additional mandatory and voluntary impact category indicators

Results per declared unit: 1 kg of product

72
C2

Indicator

Unit

A1 - A3

C4

D

C1

C3

Global warming potential (GWP) GWP-GHG (1)

kg CO₂ eq

2.17

4.47E-04

1.03E-02

2.76E-03

-1.49

3.02E-04

(1) This indicator accounts for all greenhouse gases except biogenic carbon dioxide uptake and emissions and biogenic carbon stored in the product.
As such, the indicator is identical to GWP-total except that the characterization factor for biogenic CO2 is set to zero.

Resource use indicators

Results per declared unit: 1 kg of product

Indicator

A1-A3

Unit

C2

D

C1

C3

C4

4.80E-04 7.81E-03 5.41E-03 6.89E-04
0.00E+00 0.00E+00
4.80E-04 7.81E-03
0.140

Used as energy carrier (PERE)

1.28

0.584

MJ

Primary energy

Used as raw materials (PERM)

0.00E+00

0.00E+00 0.00E+00 0.00E+00

MJ

resources -
Renewable

Total (PERT)

5.41E-03 6.89E-04

0.584

MJ

1.28

Used as energy carrier (PENRE)

5.07E-02 3.95E-03
0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00
5.07E-02 3.95E-03

-14.8

28.7

5.68E-03

MJ

Primary energy

Used as raw materials (PENRM)

0.00E+00

MJ

resources -

Non-renewable

Total (PENRT)

28.7

5.68E-03

MJ

0.140

-14.8

Use of secondary material (SM)

4.40E-02 0.00E+00 0.00E+00

0.00E+00 0.00E+00 0.00E+00
0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00
4.18E-25 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00
8.18E-03 5.39E-07 8.94E-06 1.51E-05 1.05E-06 -0.151

kg

Use of renewable secondary fuels (RSF)

3.56E-26

MJ

Use of non renewable secondary fuels (NRSF)

MJ

m³

Net use of fresh water (FW)

Note: Primary energy calculated using PCR option B.

9

Waste indicators

Results per declared unit: 1 kg of product

Unit

A1-A3

Indicator

D

C1

C2

C3

C4

Hazardous waste disposed (HWD)

1.19E-06 1.84E-13 7.06E-12
8.84E-07 2.08E-05 1.39E-05 2.00E-02
7.34E-09 1.70E-07 6.38E-07 4.15E-08 1.62E-06

7.33E-12 9.84E-13 -1.11E-07

kg

Non-hazardous waste disposed (NHWD)

kg

0.179

3.73E-02

Radioactive waste disposed (RWD)

kg

9.85E-04

Output indicators

Results per declared unit: 1 kg of product

Indicator

Unit

A1 - A3

D

C1

C2

C3

C4

0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00
0.00E+00 0.00E+00 0.00E+00 0.980 0.00E+00 0.00E+00
0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00
0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00
0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

Components for re-use (CRU)

kg

Materials for recycling (MFR)

kg

Material for energy recovery (MER)

kg

Exported electrical energy (EEE)

MJ

Exported thermal energy (EET)

MJ

Disclaimer

ILCD classification

Disclaimer

Indicator

Global warming potential (GWP)

None

Depletion potential of the stratospheric ozone layer (ODP)

ILCD Type 1

None

Potential incidence of disease due to PM emissions (PM)

None

Acidification potential, Accumulated Exceedance (AP)

None

Eutrophication potential, Fraction of nutrients reaching freshwater
end compartment (EP-freshwater)

None

Eutrophication potential, Fraction of nutrients reaching marine
end compartment (EP-marine)

None

ILCD Type 2

Eutrophication potential, Accumulated Exceedance (EP-terrestrial)

None

Formation potential of tropospheric ozone (POCP)

None

Potential Human exposure efficiency relative to U235 (IRP)

1

Abiotic depletion potential for non-fossil resources (ADP-minerals&metals)

2

Abiotic depletion potential for fossil resources (ADP-fossil)
Water (user) deprivation potential, deprivation-weighted
water consumption (WDP)

2

2

ILCD Type 3

Potential Comparative Toxic Unit for ecosystems (ETP-fw)
Potential Comparative Toxic Unit for humans (HTP-C)
Potential Comparative Toxic Unit for humans (HTP-nc)
Potential Soil quality index (SQP)

2

2

2

2

Disclaimer 1 - This impact category deals mainly with the eventual impact of low dose ionizing radiation on human health of the nuclear fuel
cycle. It does not consider effects due to possible nuclear accidents, occupational exposure nor due to radioactive waste disposal in underground
facilities. Potential ionizing radiation from the soil, from radon and from some construction materials is also not measured by this indicator.
Disclaimer 2 - The results of this environmental impact indicator shall be used with care as the uncertainties on these results are high or as there
is limited experienced with the indicator.

10

Variation in environmental indicators

The table below shows the variation for modules A-C where the difference between products is greater than 10%.

Cold rolled steel sheets and slit coils

Difference (%)

Environmental impact indicator

GWP-biogenic

21%

43%

ODP

AP

16%

EP-fresh

36%

EP-marine

14%

EP-terrest

14%

POCP

14%

ADP-elements

41%

ADP-fossil

16%

5. References

General Programme Instructions of the International EPD® System. Version 4.0

•

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Question: What nitrogen fertilizer application rates in kg N per hectare were used for zero-tillage barley production in Queensland dryland conditions?

CSIRO PUBLISHING

www.publish.csiro.au/journals/ajea

Australian Journal of Experimental Agriculture, 2007, 47, 965–975

Zero tillage and nitrogen fertiliser application in wheat
and barley on a Vertosol in a marginal cropping area
of south-west Queensland

G. A. Thomas,F, R. C. Dalal³, E. J. Weston C, D, C. J. Holmes^,E, A. J. King^,
D. N. Orange and K. J. Lehane

AQueensland Department of Natural Resources and Water, Natural Resource Sciences,
South West Region, PO Box 318, Toowoomba, Qld 4350, Australia.
BQueensland Department of Natural Resources and Water, Natural Resource Sciences,

80 Meiers Road, Indooroopilly, Brisbane, Qld 4068, Australia.

CQueensland Department of Primary Industries and Fisheries, PO Box 102, Toowoomba,

Qld 4350, Australia.

DPresent address: 50 Broadwater Terrace, Redland Bay, Qld 4165, Australia.

EPresent address: MS 172, Allora, Qld 4362, Australia.

FCorresponding author. Email: gregory.thomas@nrw.qld.gov.au

Abstract. Winter cereal cropping is marginal in south-west Queensland because of low and variable rainfall and
declining soil fertility. Increasing the soil water storage and the efficiency of water and nitrogen (N) use is essential for
sustainable cereal production. The effect of zero tillage and N fertiliser application on these factors was evaluated in wheat
and barley from 1996 to 2001 on a grey Vertosol. Annual rainfall was above average in 1996, 1997, 1998 and 1999 and
below average in 2000 and 2001. Due to drought, no crop was grown in the 2000 winter cropping season.
Zero tillage improved fallow soil water storage by a mean value of 20 mm over 4 years, compared with conventional
tillage. However, mean grain yield and gross margin of wheat were similar under conventional and zero tillage. Wheat
grain yield and/or grain protein increased with N fertiliser application in all years, resulting in an increase in mean gross
margin over 5 years from $86/ha, with no N fertiliser applied, to $250/ha, with N applied to target ≥13% grain protein.
A similar increase in gross margin occurred in barley where N fertiliser was applied to target malting grade. The highest
N fertiliser application rate in wheat resulted in a residual benefit to soil N supply for the following crop.
This study has shown that profitable responses to N fertiliser addition in wheat and barley can be obtained on long-term
cultivated Vertosols in south-west Queensland when soil water reserves at sowing are at least 60% of plant available water
capacity, or rainfall during the growing season is above average. An integrative benchmark for improved N fertiliser
management appears to be the gross margin/water use of ~$1/ha.mm. Greater fallow soil water storage or crop water use
efficiency under zero tillage has the potential to improve winter cereal production in drier growing seasons than
experienced during the period of this study.

Introduction

Winter cereal cropping, with wheat as the main rainfed crop,
is carried out over 200000 ha in south-west Queensland
(Australian Bureau of Statistics 2001). Winter cereals are
usually sown between mid April and late June, depending on
sowing opportunity, following a 6-8 month fallow period after
harvest of the preceding crop in October-November. Reduced
tillage practices during the fallow period, including zero tillage,
have been shown to result in better soil water storage and grain
yield of wheat and barley than conventional tillage in other parts
of southern Queensland (Thomas et al. 1997). These practices
therefore offer potential to improve the reliability of cropping in
the south-west area. Nitrogen fertiliser application is an option
for compensating for N fertility decline under winter cereal
cropping. However, when the experiments discussed in this
paper commenced in 1996, N fertiliser use in the south-west

The south-west Queensland cropping region, which includes the
Roma, St George and Dirranbandi districts, is marginal for
rainfed crop production. The region receives an average annual
rainfall of 500-600 mm with 20-30% year-to-year variability
and has annual potential evapotranspiration of ~2000 mm,
resulting in a rainfall: potential evapotranspiration ratio of <0.3
(Weston et al. 1975). Moreover, as the period of cereal cropping
has increased, grain yield and grain protein have decreased as
soil fertility, particularly soil nitrogen (N) supply, has declined
(Dalal and Mayer 1986a). On a Vertosol, which is the main
cropping soil in the region, the mean rate of net N loss from the
soil profile was 35.8 kg N/ha.year (Dalal and Mayer 1986b).
Therefore, it is essential to address these issues of water and N
supply to crops in developing sustainable farming systems for
this area if it is to continue to support grain cropping.

© CSIRO 2007

10.1071/EA05253

0816-1089/07/080965

Australian Journal of Experimental Agriculture

966

G. A. Thomas et al.

Table 1.

Soil chemical and physical characteristics, Nindigully trial

Soil depth
(cm)

Electrical
conductivity
(1:5 H2O) (dS/m)

Cation exchange Exchangeable

Clay (%)

Chloride
(mg/kg)

pH
(1:5 H₂O)

Plant available

sodium (%)

capacity
[cmol(+)/kg]

water capacity
(mm)

22222
25
26
24
20

0.10

0-10

3.8

24

8.6

10

52

11

10-30

0.11

53

9.0

6.2

40

0.18

11.7

30-60

36

55

60

9.2

60-90

8.8

64

0.59

144

15.5

54

90-120

1.58

305

57

8.1

17.0

54

area was none or low and little was known about the economics
of N fertiliser application in the area.
The aim of this study was to determine whether zero tillage
fallow management and N fertiliser application improve grain
yield and quality and gross margin in wheat and barley on a
Vertosol in the marginal cropping region of south-west
Queensland.

and physical characteristics of the soil profile are given in
Table 1. Details of the analytical methods used for these
analyses are given by Bruce and Rayment (1982).
At St George, long-term (1943–96) mean daily maximum
and minimum temperatures range from 19°C and 5.4°C,
respectively, in July, to 34.5°C and 21.5°C, respectively, in
January (Bureau of Meteorology). Frosts (mean screen
temperature ≤2.2°C) may occur between early May and mid
September. Mean daily evaporation ranges from 3.1 mm in June
to 11.0 mm in December. Long-term mean monthly rainfall at
St George and actual monthly rainfall at the Nindigully trial site
from 1996 to 2001 are shown in Table 2.

Materials and methods

Field trial site

We established a farming systems trial at Nindigully, on the
property 'Dunkerry South' (28°30'S, 148°45′E), ~50 km south
of St George in south-west Queensland, in May 1996. The site
I was on a grey Vertosol soil (Isbell 1996) that had been under
cultivation since 1956. Native vegetation at the site was
primarily coolibah (Eucalyptus microtheca) open woodland and
Mitchell grass (Astrebla lappacea). The site was chosen as
being representative of a land system in the region with a large
area of cropping (~100000 ha, Robinson 2005) and in which
soil fertility decline had been identified (Dalal and Mayer
1986a, 1986b). At the start of the trial, soil organic carbon, total
nitrogen and bicarbonate-extractable phosphorus at 0-10 cm
were 0.65%, 0.07% and 9 mg/kg, respectively. Other chemical

Field trial establishment and crop management

The field trial commenced in May 1996 following a wheat crop
in 1995 and three tillage operations with a chisel plough during
the fallow period. Several experiments were conducted within
the trial area. In this paper, we report on studies on tillage
method (conventional and zero) (experiment 1) and N fertiliser
application (experiment 2). The experiments were sown and
harvested in 1996, 1997, 1998, 1999 and 2001. Due to drought,
no crop was grown in the 2000 winter cropping season.
In experiment 1, following harvest of wheat in 1996, main
plots, 40 m long and 36 m wide and replicated three times, were

Table 2. Long-term mean monthly, in-crop and fallow rainfall for St George (1881–1996), and monthly,
in-crop and fallow rainfall recorded at the Nindigully trial site from 1995 to 2001
n.m., not measured

Mean rainfall

Rainfall (mm) at Nindigully trial site
1998

Month

for St George,
1881-1996 (mm)

1996

1995

1997

1999 2000 2001

194
573-376-346×22
95
44
1
1
18

2020*232265
24
64
27
51

35

Jan.

74

238

118

45

Feb.

62

50

61

22

13

0

Mar.

54

13

189

61

33

63

22

Apr.
May
June

24

4

39

87

72

11

18

33

33

9

66

60

33

July
Aug.
Sept.

43

124

31

2

25

9

54

108

41

27

23

78

32

0

48

94

73

Oct.

39

48

55

57

32

93

Nov.

46

68

52

32

3

Dec.

62

203

58

8

Total

730

786

372

516

700

616

n.m.

269 111A
286

May Oct. (usual in-crop)
Nov.-Apr. (usual fallow)

196

288

181

496

n.m.

320

339

274

410

384

426

ANo crop sown due to lack of sowing rainfall.

Australian Journal of Experimental Agriculture 967

Tillage and N supply in cereals on a Vertosol in south-west Queensland

each split into two treatments, conventional tillage (CT) and
zero tillage (ZT). The main plots comprised 16 runs of a 2.25-m
wide seeder. The tillage subplot width was 18 m (eight seeder-
runs). Tillage treatments were imposed after the harvest of 1996
cereal crops and maintained until the harvest of 2001. The CT
treatment had 3-4 cultivations with a chisel plough or scarifier
for weed control during the fallow period. A similar number of
herbicide applications were used for weed control during the
fallow period under the ZT tillage system. At sowing of wheat
in 1997, 1998, 1999 and 2001, the CT and ZT treatments were
split further into two sub-subplots, each 9 m wide (four seeder-
runs), one without and one with N fertiliser application.
In experiment 2, four N fertiliser treatments (one without and
three with N fertiliser application) were applied at sowing in
wheat under the ZT system in all years. The main plots were 40 m
long and 36 m wide (16 runs of a 2.25-m wide seeder) with three
replications and were split into four N fertiliser subplots that were
each 9 m wide (four seeder-runs). From 1996 to 1999, N fertiliser
treatments in wheat were applied to the same subplots each year.
Two N fertiliser treatments (one without and one with N
fertiliser application) were applied at sowing in barley under ZT
in all years. The main plots of barley were 40 m long and 18 m
wide (eight seeder-runs) with three replications and were split
into two N fertiliser subplots that were each 9 m wide (four
seeder-runs). The location of the main plots of barley varied
from year to year within the trial area.
In experiments 1 and 2, a basal application of 40 kg/ha of
mixed fertiliser (9.4% N, 20.5% P, 2.2% S, 2.5% Zn) was
banded with the seed at sowing in all years except 1998.
In both experiments, N fertiliser application rates were
determined from consideration of soil water and soil nitrate-N
content obtained from soil sampling before sowing. Using the
equation of Dalal et al. (1997), relating grain protein
concentration to the ratio between available soil water (mm) and
N supply (soil nitrate-N + N fertiliser) (kg/ha) at 0-120 cm
depth at sowing, the amount of N fertiliser required to target a
given grain protein concentration was calculated. The required
ratios were 2.5 for malting barley (10.2 ± 1% protein on oven-
dry basis) and for wheat grain at 12% moisture, 2 for 10.5 ± 1%
protein, 1.5 for 11.5 ± 1% protein and ≤1 for ≥13% protein.
Wheat protein concentrations of 10.5%, 11.5% and 13% are the
minimum requirements for the Australian Premium White
(APW), Australian Hard (AH) and Australian Prime Hard
(APH) grades, respectively. A retrospective assessment of N
fertiliser requirements to achieve grain protein concentration of
10.2% in barley and 13% in wheat was also carried out using the
computer program HOWWET? (Freebairn et al. 1997). In the N
requirement section of the program, measured available soil
water and soil nitrate-N at sowing from experiment 2 were
entered with both a commonly used estimate for water use
efficiency (WUE) (10 kg/ha.mm, 100-mm threshold soil water)
and a mean measured value for WUE (9.5 kg/ha.mm) from the
experiment from 1996 to 2001. The N fertiliser requirements
estimated from HOWWET? were then compared with those
using the available soil water/N supply method.
In experiment 1, the N fertiliser application rate varied from
year to year, depending on soil water and nitrate-N content, and
was chosen to target wheat grain protein of 11.5 ± 1% at 12%
moisture content in 1997 and 13 ± 1% at 12% moisture content

in 1998, 1999 and 2001. In experiment 2, application rates of N
fertiliser also varied from year to year, depending on soil water
and nitrate-N content (Tables 5 and 6). In each year, increasing
N fertiliser rates were chosen to target grain protein of 10.5%,
11.5% and 13% (±1%) at 12% moisture in wheat, and a single
rate was chosen to target malting barley of 10.2 ± 1% grain
protein on an oven-dried basis.
In 1996, 1999 and 2001, wheat under CT and ZT and barley
under ZT were sown with a small-plot seeder which had nine
rigid, spear point tines followed by solid, centre-ribbed press
wheels, at a row spacing of 25 cm. Sowing depth was 5-8 cm. In
N fertiliser treatments, urea was applied at sowing at 5-8 cm
depth in the centre of alternate seed rows. In 1997 and 1998,
wheat and barley were sown with a small-plot air seeder of similar
configuration, but with sowing tines modified to distribute N
fertiliser in bands 3-4 cm on either side of the seed row.

Wheat (cv. Hartog) and barley (cv. Tallon) were both sown
on 24 May 1996 and on 29 May 1997. In 1998, wheat
(cv. Sunco) was sown on 23 May and barley (cv. Tallon) was
sown on 14 May. Wheat (cv. Kennedy) and barley (cv. Tallon)
were both sown on 22 June 1999 and 21 June 2001. Both crops
were sown at 40 kg/ha in 1996, 1999 and 2001 and at 30 kg/ha
in 1997 and 1998.

Soil and plant sampling and analysis

Soil profile nitrate-N concentration and water content were
measured from soil samples collected in April, 4-8 weeks
before sowing and in October-November, shortly after harvest,
each year. At each sampling time, four soil cores were taken in
a line across two adjacent crop rows and inter-rows at a
randomly selected location in each plot. Two samples were taken
in the crop rows to a depth of 120 cm in 1996 and 150 cm in
subsequent years, and two samples were taken in the centre of
the inter-row space to a depth of 30 cm. Cores were 50 mm in
diameter in 1996 and 1997 and 38 mm in following years. Cores
were divided into 0-10, 10-30, 30-60, 60-90, 90-120 and
120–150 cm layers, according to depth of sampling. For each
plot, the samples from corresponding layers were bulked, sealed
in plastic bags and stored at 4°C until analysed for nitrate-N
concentration and moisture content.
Soil was dried at 35 ± 5°C in a forced draught oven and
ground <2 mm for colorimetric determination of nitrate-N (Best
1976) after extraction of 10 g of soil in 100 mL of 2 mol/L KCl.
Nitrate-N in kg/ha was calculated from the nitrate-N
concentration for each layer, depth of the layer and its bulk
density, and then summed for the whole profile.
Gravimetric soil water content (g/g) was determined by
drying soil samples at 105°C for 48 h. Volumetric soil water
content (mm) for each layer was then calculated using bulk
density values determined from soil cores taken when the soil
profile was fully wet. Plant available soil water content was
determined for each layer by subtracting the lowest soil water
content recorded during the trial for that layer in a mature,
stressed crop (lower limit of water extraction) (Gardner 1985)
from the measured soil water content, and was then expressed as
equivalent depth of water (mm) for the whole profile.
The number of ears/m² was determined from one or two
0.25-m² samples taken from each subplot at crop maturity. Crop
grain yield at maturity was determined from machine harvesting

968 Australian Journal of Experimental Agriculture

G. A. Thomas et al.

method of Reynolds and Elrick (1991) to measure hydraulic
conductivity and pore size distribution. Rainwater (electrical
conductivity <3 µS/m) was also used for these measurements.
Fine bedding sand (mean diameter <0.001 m) was used to
ensure good contact between the disc permeameter and the soil.
The disc permeameters did not measure flow in pores >3 mm,
so large cracks and micropores were not characterised.
Measurements were made from four disc permeameters per
treatment in each replicate.
Using a linear relationship between infiltration and surface
cover (Freebairn et al.1993), infiltration measurements for 0%
and 100% cover were used to estimate values for existing cover
levels under CT and ZT.

1.75 m x 36 m of each of the inner two seeder-runs of each
subplot. Grain samples were taken from each subplot for grain
N and grain weight determination. Grain N concentration was
determined from Kjeldahl digests using automated ammonium
analysis (Crooke and Simpson 1971). Grain yield, grain protein
concentration and grain weight were calculated at 12% moisture
content, except for barley grain protein concentration, which
was expressed at 0% moisture content.

Water use efficiency and nitrogen use efficiency

Water use efficiency for grain yield (kg/ha.mm) was determined
by dividing grain yield by crop water use (mm). Crop water use
was calculated as profile soil water content in April before
sowing, minus soil water content in October-November after
harvest, plus in-crop rainfall received between these sampling
times, mostly during crop growth.
Nitrogen use efficiency (NUE) for grain N yield was
calculated as follows: NUE (%)
NUE (%)
= 100 × grain N yield
(kg/ha)/plant utilisable N (kg/ha). Plant utilisable N was equal to
soil nitrate-N before sowing, plus N fertiliser (if applied), minus
soil nitrate-N after harvest, plus soil nitrate-N mineralised during
the cropping period. Soil nitrate-N mineralised during the
cropping period was estimated from the change in soil nitrate-N
during this period in an unplanted area adjacent to the trial.

Statistical analysis

Significant differences (P = 0.05) between treatments for the
various measurements in each experiment were determined
using standard analyses of variance (Snedecor and Cochran
1967). Experiment 1 was analysed as a factorial design (two
tillage treatments, each split for two N fertiliser treatments ×
three replications). In experiment 2, N fertiliser treatments in
wheat and barley were analysed as a randomised block design
with three replications.

Results

Gross margin

Seasonal conditions

To compare the profitability of treatments, gross margins were
calculated as the on-farm income from the grain produced, less
the variable or operating costs involved in fallow and crop
management. Gross margins do not take into account fixed or
overhead expenses such as rates, taxes, insurance, interest and
depreciation on machinery and buildings. The on-farm income
from the grain was calculated from the Australian Wheat Board
prices for grain at the nearest grain depot (Thallon), at the grain
protein concentration recorded for each treatment. Variable costs
were estimated from a record of operations and materials and their
costs (Department of Primary Industries 2000). Gross margins
were calculated using grain prices and costs pertaining to each
year and also using mean grain prices between 1996 and 2004.
Profitability of water use ($/ha.mm) was determined by
dividing the gross margin by the crop water use.

Annual rainfall was above average in 1996, 1997, 1998 and
1999 and below average in 2000 and 2001 (Table 2). Rainfall
was insufficient to enable sowing of the crop in 2000. In-crop
rainfall was below average in 1997. In 1998, when in-crop
rainfall was well above average, there were severe infestations
of yellow spot (Pyrenophora tritici-repentis) in wheat and net
blotch (Pyrenophora teres) in barley.

Effects of tillage practice on wheat grain yield, grain protein
concentration, gross margin and water use efficiency
Because there were no significant interactions between tillage
practice and N fertiliser application, mean effects of CT and ZT
across N fertiliser treatments are presented. Grain yield of wheat
was greater under ZT than under CT in 1997, but was similar
under CT and ZT in all other years and for the mean values over
4 years (Table 3). There were no differences in grain protein
concentration between CT and ZT.
Gross margins calculated using grain prices and costs
pertaining to each year were greater under ZT than under CT in
1997, but greater under CT than under ZT in 1998 and 1999
(Table 3). Gross margins in 2001 and mean gross margins over
years were similar under CT and ZT.
There were no differences in crop water use between CT
and ZT (data not shown), but efficiency of water use for
grain production was greater under ZT than under CT in 1997
(Table 3).

Infiltration measurements

In April 1999, infiltration of water into the soil was measured in
the field in CT and ZT treatments using a portable rainfall
simulator based on the design of Bubenzer and Meyer (1965).
One hundred mm of simulated rainfall was applied
simultaneously over 1 h to two 100-cm wide and 160-cm long
plots in each of the three replicates of CT and ZT treatments.
Crop stubble was cut and removed from one of these plots to
approximate 0% cover and was added to the other plot to give
100% cover. Runoff water was collected at the downslope edge
and routed by vacuum through calibrated tipping buckets. Tip
rate was logged at 1-min intervals. Water used for simulations
was rainwater with electrical conductivity <3 µS/m.
After rainfall simulation, soil hydraulic conductivity was
measured with disc permeameters (Perroux and White 1988) in
the same area of each CT and ZT treatment that received
simulated rainfall. Disc permeameters were applied using the

4

Effects of tillage practice on infiltration and soil water and
nitrate-N at sowing
At the end of the fallow period in 1999, cumulative infiltration
after 100 mm of simulated rainfall over 1 h was greater under
ZT than under CT at existing stubble cover levels (60% and

Australian Journal of Experimental Agriculture

Tillage and N supply in cereals on a Vertosol in south-west Queensland

969

Table 3. Effects of conventional tillage (CT) and zero tillage (ZT) on plant available soil water
at sowing (0-120 cm), wheat grain yield, grain protein, gross margin and water use efficiency
n.s., not significant

Grain yield
(t/ha)

Tillage
method

Available soil
water at

Grain protein Gross margin
(%)

Water use

($/ha)

efficiency
(kg/ha.mm)

sowing (mm)

1997 crop

CT

106

8.3

140

2.11

9.6

ZT

150

2.59

9.8

154

9.8

1.s.d. (P = 0.05)

0.13

1.0

32

n.s.

n.s.

1998 crop

1.62

-2
225
བསླབ་སྤམ
27
21
163
29

CT

82

13.0

2.9

105

ZT

1.54

13.0

2.8

1.s.d. (P = 0.05)

n.s.

n.s.

n.s.

n.s.

1999 crop

CT

165

3.11

10.7

8.0

199

ZT

3.08

10.6

7.4

1.s.d. (P=0.05)

27

n.s.

n.s.

n.s.

2001 crop

2.27

145

145

12.7

CT

6.4

160

2.40

55

6.5

ZT

12.4

1.s.d. (P = 0.05)

n.s.

n.s.

n.s.

n.s.

n.s.

Mean of 1997-2001 crops

133

2.23

CT

11.4

125

6.4

ᏃᎢ

2.36

11.4

153

92

6.7

1.s.d. (P = 0.05)

18

n.s.

n.s.

n.s.

n.s.

10%, respectively) and with 0% cover, but was greater under CT
than under ZT with 100% cover (Table 4). Mean final
infiltration rate after 1 h was greater with 100% cover
(17 mm/h) than with existing cover (5 mm/h) and 0% cover
(2 mm/h) [1.s.d. (P 0.05) 11]. Saturated hydraulic
conductivity of surface soil after simulated rainfall was greater
under ZT than under CT at existing stubble cover levels
(Table 4). Mean pore density in the 1.5–3.0 mm diameter pore
range in surface soil was greater under CT (mean of
9.3 pores/m²) than under ZT (mean of 6.8 pores/m²) [1.s.d.
(P=0.05)=1.7]. There were no significant differences between
CT and ZT in saturated hydraulic conductivity and pore density
in the 1.5–3.0 mm diameter pore range in subsurface soil (13 cm
depth) (data not shown).
Mean plant available water in the soil profile at sowing over
4 years was 20 mm greater under ZT than CT (Table 3).
However, in individual years, plant available soil water at
sowing was greater under ZT than under CT only in 1999, when
this effect was not reflected in improved grain yield (Table 3).

Mean fallow water storage efficiency (percentage of rainfall
stored in the soil during the fallow period between crops) for the
1996-97, 1997-98, 1998-99 and 1999-2001 fallow periods was
16% under ZT and 13% under CT.
There were no differences between CT and ZT in soil
nitrate-N at sowing (data not shown).

=

=

Effects of N fertiliser application on wheat grain yield,
grain protein, yield components, gross margin and
water use efficiency

Since grain yield responses to N fertiliser were similar under CT
and ZT practices in wheat, only data for ZT practice are
presented. Wheat grain yield increased with increasing rates of
N fertiliser addition and N supply in all years except 2001
(Table 5). However, grain protein concentration increased with
increasing rates of N fertiliser addition and N supply in all years.
The first increment of N application generally resulted in
significantly greater grain yield and protein than when no N was
applied. Although increases in grain yield with subsequent

Table 4.

Cumulative infiltration and saturated hydraulic conductivity of surface soil after simulated
rainfall (100 mm rain over 1 h), for conventional tillage (CT) and zero tillage (ZT) with stubble removed (0%
cover), at existing stubble cover levels (10% and 60%, respectively) and with stubble added to give 100% cover

Cumulative infiltration (mm)
Existing cover

Tillage method

Saturated hydraulic conductivity (mm/h)
Existing cover

100% cover

100% cover

0% cover

0% cover

1740
1720

CT

19

23

65

195

340

1260

35

ZT

42

47

440

1.s.d. (P = 0.05)
(tillage x cover)

10

435

Australian Journal of Experimental Agriculture

970

G. A. Thomas et al.

increments of N addition were not generally significant, grain
protein concentration often continued to increase significantly
as N fertiliser addition and N supply increased. As a result, gross
margins calculated using costs and returns pertaining to each
year increased with increasing N supply in 1996, 1997 and 1999
and for the mean values over 5 years. In a wet growing season
and disease-affected crop in 1998, there was no effect of N
fertiliser application on gross margins. When gross margins
were calculated using mean grain prices between 1996 and
2004, mean gross margin increased from $30/ha, with no N
fertiliser applied, to $150/ha, with the highest rate of N addition
(data not shown).
Except for 1998, grain weight decreased with increasing N
supply. The decrease in grain weight was compensated by

increasing tiller numbers, as shown by the increasing number of
ears (Table 5).
Plant available soil water at sowing and crop water use were
not significantly affected by N fertiliser application in
individual years (data not shown). However, mean crop water
use over 5 years was greater with mean annual N fertiliser
application rate of 64 kg N/ha (399 mm) than with no N
fertiliser application (374 mm) [1.s.d. (P = 0.05) = 23]. Water
use efficiency for grain yield of wheat increased with N
fertiliser application in all years except 2001 and for mean
values over 5 years (Table 5). As for grain yield, the greatest
increase in WUE was generally with the first increment of N
addition. In the wet growing season of 1998, WUE was below
4 kg/ha.mm, indicating the adverse effects of periodic

Table 5. Effects of N supply (N fertiliser applied at sowing + soil nitrate-N before sowing, 0-120 cm) on
grain yield, grain protein, grain weight, number of ears, gross margin and water use efficiency for continuous
zero tillage (ZT) wheat
n.s., not significant

Grain
yield
(t/ha)

Number
of ears/m²

Water use
efficiency
(kg/ha.mm)

N fertiliser
(kg N/ha)

Soil
nitrate-N

Grain

Grain

Gross

protein
(%)

weight
(mg)

margin
($/ha)

(kg N/ha)

1996 crop

3.01

8.5

8.1

75

0

40.3

313

189

30

75

3.50

38.5

306

239

9.2

8.9

75

355

9.8

60

3.66

10.7

35.6

289

12.3

90

75

3.82

33.2

372

353

10.0

1.s.d. (P=0.05)

93

0.29

0.9

2.5

46

0.9

n.s.

1997 crop

39

0

2.20

7.7

38.5

178

79

7.5

40

9.3

2.70

9.9

35.8

281

161

2.81

11.8

32.9

344

190

9.3

70

54

2.93

333

10.3

100

13.1

32.0

224

1.s.d. (P=0.05)

15

0.7

0.17

1.9

76

48

1.4

1998 crop

33
90
35508
55
55
18

230

1.12

2.6

11.8

0

-26
n.s.
201712
57
47

20.7

30

20.3

1.51

12.6

282

3.4

40

1.83
1.79

13.4

20.9

309

3.8

3.7

13.8

50

20.6

296

1.s.d. (P=0.05)

0.27

0.7

0.4

n.s.

n.s.

1999 crop

སམྨརྞཧི
198
220
344
52

0

155

2

36

2.58

8.0

40.9

6.2

60

32

11.3

3.84

38.2

234

9.4
9.1
9.2

38.6

12.2

90

37

4.01

297

150

37.3

49

4.02

13.4

240

1.s.d. (P= 0.05)

0.28

0.9

1.8

115

1.3

n.s.

2001 crop

10.0

36.5

186

8.6

0

90

2.92

255
255

40

90

3.13

33.5

238

11.7

8.8

90

32.2

333

60

3.00

13.4

256

8.0

100

31.7

269

280

90

2.99

14.9

7.9

1.s.d. (P= 0.05)

3.6

77

1.8

n.s.

n.s.

n.s.

n.s.

Mean of 1996-2001 crops

72237
6.7
8.0
7.9
8.3
0.7

0

54

2.36

9.2

35.4

226

86

40

59

33.3

274

168

2.94

10.9

328

32.0

60

12.3

64

3.06

202

3.11

98

71

13.5

30.9

302

250

1.s.d. (P=0.05)

9

0.13

0.4

0.9

47

20

Australian Journal of Experimental Agriculture

Tillage and N supply in cereals on a Vertosol in south-west Queensland

971

waterlogging and plant disease on crop growth and yield in
this year.
Gross margin/water use increased with N fertiliser addition
and greater N supply in 3 out of 5 years (1996, 1997 and 1999)
(data not shown) and for mean values over 5 years (Fig. 1). The
highest value recorded for gross margin/water use in individual
years was $0.93/ha.mm, for wheat with the highest N fertiliser
application and the greatest N supply in 1996.

0.8

Mean gross margin/water use

Wheat

☐ Barley

اس

0.6

($/ha.mm)

0.4

Effects of N fertiliser application on barley grain yield,
grain protein concentration, yield components, gross
margin and water use efficiency

0.2

0

Significant increases in barley grain yield resulted from the
addition of N fertiliser in 1996 and 1999 (Table 6). In 1996,
1997, 1998 and 1999 seasons, grain protein concentration with
N fertiliser application was in the range to qualify for malting
grade barley (9-12% at 0% moisture content) and, except for the
1998 crop, resulted in similar gross margins to those for wheat
at 12.3% grain protein in 1996 and APH grade wheat (≥13%
grain protein) in 1997 and 1999. Barley was of feed grain
quality and of lower value because of weather damage in 1998
and high grain protein in 2001, due to high residual nitrate-N in
soil from the unavoidable long fallow (no crop in 2000 due to
lack of sowing rain). Where gross margins were calculated
using costs and returns pertaining to each year, mean gross

0

40

98

0

29

64

Mean N fertiliser application rate (kg N/ha.year)

Fig. 1. Mean effects of N fertiliser application on gross margin/water use
for wheat and barley, 1996–2001. Vertical line indicates the 1.s.d. value
(P = 0.05).

margin over 5 years, where malting grade barley was targeted,
was almost double that where it was not. Using mean grain
prices between 1996 and 2004, mean gross margin where
malting barley was targeted was $180/ha (data not shown).
Grain weight of barley was greater with N fertiliser
application than without in 1999, and lower with N fertiliser

Table 6. Effects of N supply (N fertiliser applied at sowing + soil nitrate-N before sowing, 0-120 cm) on grain
yield, grain protein (0% moisture content), grain weight, number of ears, gross margin and water use efficiency
for zero tillage (ZT) barley
n.s., not significant

N fertiliser

Water use
efficiency
(kg/ha.mm)

Grain
yield
(t/ha)

Grain

Number
of ears/m²

Soil
nitrate-N
(kg N/ha)

Grain
weight
(mg)

Gross
margin
($/ha)

(kg N/ha)

protein
(%)

1996 crop

3.15

174

75

47.5

0

9.1

40

75

3.68

11.6

38.9

1036

448

10.2

1.s.d. (P=0.05)

2.5

0.29

46

1.0

n.s.

1997 crop

2.48

11.1

39.1

0

67

245

461

10.9

226

9.5

20

68

2.48

12.4

39.2

511

1.s.d. (P =

= 0.05)

0.8

1.4

n.s.

n.s.

n.s.

n.s.

n.s.

1998 crop

27.4

0

1.92

49

10.5

394

20

4.5

379

2.25

11.4

5.2

20

49

28.4

33

1.s.d. (P=0.05)

0.5

0.7

n.s.

n.s.

n.s.

n.s.

n.s.

1999 crop

0

36

2.96

7.2

37.0
39.2

476

62

7.1

9.8

533

45

36
1
n.s.

4.06

360

9.2

1.s.d. (P=0.05)

1.3

0.28

1.0

1.8

n.s.

n.s.

2001 crop

0

95

3.17

13.2

33.8

464

155

8.6

3.15

376

20

95

14.4

31.1

133

8.9

1.s.d. (P=0.05)

n.s.

n.s.

n.s.

n.s.

n.s.

n.s.

n.s.

Mean of 1996-2001 crops

2.74

65

9.3

131

0

37.0

431

7.9

35.3

65

29

3.12

10.8

567

240

8.5

1.s.d. (P = 0.05)

0.4

0.9

0.13

47

20

n.s.

n.s.

Australian Journal of Experimental Agriculture

972

G. A. Thomas et al.

than without in 1996 and for mean values over 5 years (Table 6).
Tiller numbers were not affected by N application in any
individual year, but mean tiller numbers over 5 years were
greater with N fertiliser application than without.
There were no significant differences in crop water use
between N fertiliser treatments in barley in any year or across
years (data not shown). Water use efficiency was significantly
lower in N fertilised treatment than without N application in
1997, but increased with N fertiliser application in 1998 and
1999 seasons (Table 6). Mean gross margin/water use over
5 years for barley increased significantly with N fertiliser
application (Fig. 1). Mean gross margin/water use values were
greater in barley than in wheat where no N fertiliser was applied,
while maximum values were similar in wheat and barley. The
highest gross margin/water use in barley in individual years
($1.24/ha.mm) was obtained for malting grade barley in 1996
(data not shown).

70

y = 0.41x
R2 = 0.90

60

Increased grain N (kg/ha)

50

40

30

20

10

50

100

150

200

Fertiliser N applied (kg N/ha)

Fig. 3. Relationship between increased grain N (grain N yield in the N
treatment - grain N yield in the control) in wheat and barley and N fertiliser
applications. The slope of the regression line × 100 is the apparent N
recovery in grain.

Residual benefit of applied N fertiliser

In all years, the N fertiliser application to wheat resulted in a
residual benefit to soil N supply for the following crop, as
measured by soil nitrate-N (0-120 cm depth) before sowing
(Fig. 2). Thus, in this semiarid, marginal crop growing
environment, a substantial amount of N fertiliser that is unused
by a crop is carried over to the next season.

Prediction of grain protein concentration from the ratio of
available soil water/N supply before sowing
Measured grain protein concentrations of wheat and barley were
compared with the predicted values using the equation derived
by Dalal et al. (1997):

Nitrogen use efficiency for grain N yield

Apparent N fertiliser use efficiency for wheat and barley grain
[(grain N yield of N treatment - grain N yield of control)/N
fertiliser applied] was 41% (Fig. 3), with no significant tillage
or N fertiliser application rate effects. There were no
significant differences between N fertiliser treatments in NUE
for grain N yield. Accounting for residual N fertiliser and in-
crop N mineralisation increased NUE for grain N yield, which
ranged from a mean of 43% in 1996 to 59% in 1999 (data not
shown).

Grain protein (%) = 6.52 + 10.0 × exp(−0.44 available
water/available N)

where plant available water (mm) and available N (soil nitrate-N
+ N fertiliser) (kg/ha) in 0-120 cm depth of soil were measured
at or near sowing.

16

Predicted grain protein concentration (%)

y= 1.00 (± 0.02 s.e.)x
R² = 0.75

14

140

120

Residual fertiliser N (kg/ha)

12

y=0.74x-22.36
R² =

100

-= 0.68

0

80

60
60

40
40

20

6

8

10

12

14

16

Measured grain protein concentration (%)

-20

0

50

100

150

200

Previous year fertiliser N application (kg N/ha)

Fig. 4. Relationship between the predicted (Dalal et al. 1997) (y) and
measured (x) grain protein concentrations for wheat and barley. The
equation of regression line (full) through the origin is: y = 1.00 (±0.02 s.e.)x
(R2 = 0.75). The dotted lines show ±1% range in grain protein about the
regression line. The dashed line is the 1:1 line.

Fig. 2.
Soil nitrate-N (0-120 cm) at sowing following N fertiliser
application in the previous year, in excess of that with no N fertiliser
application.

Australian Journal of Experimental Agriculture 973

Tillage and N supply in cereals on a Vertosol in south-west Queensland

water at sowing in 1999. The lower gross margin under ZT than
under CT in 1998 and 1999 was due to higher fallow weed
control costs with herbicide under ZT than tillage costs under
CT in these years.
Other experiments in southern Queensland have shown that
there is a greater advantage in yield with ZT over CT in drier
growing seasons, as a result of greater soil water storage or
water use efficiency (Freebairn et al. 1986; Marley and Littler
1989; Radford et al. 1992; Thomas et al. 1995; Strong et al.
1996a). Retention of crop residues on the soil surface, as occurs
under ZT, has also been shown to extend crop sowing time and
facilitate timeliness of sowing during dry weather (Radford and
Nielsen 1983), thus providing more sowing opportunities and
enhancing potential yield benefits associated with optimum
sowing time (Woodruff and Tonks 1983). Therefore, ZT may
provide yield and economic benefits to longer-term crop
production under the drier conditions more likely to be
experienced in this environment than those that occurred from
1996 to 2001.
We observed significant grain yield responses to N fertiliser
application in all cropping years except the 2001 season, when
the crop followed a long fallow of 18 months (due to lack of
sowing rains in 2000) and 80 kg N/ha was accumulated in the
soil profile. Except for a wet growing season in 1998, gross
margins significantly increased from fertiliser application. We
suggest that profitable responses to N fertiliser addition can be
obtained in the marginal cropping area of south-west
Queensland on deep grey clay soil that has been cropped for
several years and is of relatively low fertility. However, all trials
that produced grain yields commenced with soil water storage
>60% of the plant available water capacity, or received above
average rainfall over the growing season. In drier growing
seasons, crops were either not sown (2000, 2002) or failed to
produce harvestable grain yield (2003, data not shown).
Robinson et al. (1999) concluded from simulation modelling
that positive responses to applying 60 kg N/ha at sowing
occurred in 97% of years under conditions similar to those
experienced in 1996, but in less than 40% of years when soil
water at sowing was less than 50% plant available water
capacity. However, on a Vertosol at Warra, ~300 km north-east
of Nindigully, N application increased gross returns from five of
the seven wheat crops grown, because of increasing grain yield
and/or grain protein responses (Strong et al. 1996a). These
results occurred over the 1987-94 period, which included a
4-year period of exceptionally dry seasonal conditions. At
Warra, although grain yield responses were inconsistent in the
first year of fertiliser application where no N fertiliser had been
applied to preceding crops, grain protein usually increased with
increasing N application. Holford and Doyle (1992) also
showed profitable grain yield responses with wheat to varying
rates of N application during a dry growing season in northern
New South Wales. Similar effects to those at Warra and in
northern New South Wales may also occur under drier seasonal
conditions in the south-west Queensland region.
This study has also shown that unused available soil and
fertiliser N generally remains in the soil profile to benefit the
following crop. This benefit results in a lower N fertiliser
requirement in the following crop. Similar effects were also
recorded at Warra (Strong et al. 1996b). However, unused

N fertiliser requirement using available
soil water/N supply (kg N/ha)

160

120

80

HOWWET? with
estimated WUE
HOWWET? with
measured WUE
1:1 line

=

0

120

40

80

160

N fertiliser requirement using HOWWET?
(kg N/ha)

Fig. 5. Relationship between the N fertiliser requirement to target grain
protein concentration of 10.2% in barley (0% moisture content) and 13% in
wheat (12% moisture content) using the available soil water/N supply
method (Dalal et al. 1997) to calculate y, and HOWWET? (Freebairn et al.
1997) to calculate x with (i) a commonly used estimate of water use
efficiency (WUE) (y = 1.41x + 13.31, R2 = 0.91) and (ii) a measured mean
value for WUE from this experiment (y = 1.07x - 7.08, R² = 0.92).

There was a significant and a 1:1 relationship between the
predicted (y) and measured (x) grain protein values (Fig. 4).
Including a commonly used estimate of WUE, HOWWET?
(Freebairn et al. 1997) under-predicted grain yield and therefore
the N fertiliser requirements to achieve grain protein
concentration of 10.2% in barley and 13% in wheat, compared
with the available soil water/N supply method (Fig. 5). Using a
measured mean value for water use efficiency from the
experiment in HOWWET? resulted in better agreement between
these two methods.

Discussion

At the existing levels of soil cover during the 1998-99 fallow
period, the soil under ZT had four times greater hydraulic
conductivity and two times greater water infiltration than the
soil under CT, resulting in 27 mm extra water in the soil profile
under ZT practice at the end of the fallow period. In Vertosols,
Dalal (1989) showed a much higher rate of Cl leaching under ZT
than CT, indicating greater water infiltration under ZT, and
Turpin et al. (1999) measured much faster water infiltration and
bromide movement under ZT than CT, especially when stubble
was retained.
Although mean plant available water in the soil profile at
sowing over 4 years was 20 mm greater under ZT than under CT,
the mean grain yields and gross margins were similar under CT
and ZT over this period. ZT resulted in higher grain yield, gross
margin and water use efficiency than CT in 1997, when plant
available soil water levels at sowing were similar for the two
tillage practices, indicating that ZT made more efficient use of
stored soil water and in-crop rainfall in this near-average
growing season. CT and ZT resulted in similar grain yields in
1998, 1999 and 2001, even though available soil water before
sowing was higher under ZT than under CT in 1999. Above
average in-crop rainfall may have negated differences in soil

Australian Journal of Experimental Agriculture

974

G. A. Thomas et al.

nitrate-N in the soil profile may be lost occasionally by leaching
below the root zone and by denitrification, depending on
seasonal conditions. Its benefit (and that of fresh N fertiliser
application) may also be lost to the following crop if factors
such as plant disease limit the response to the additional
N supply.
Apparent N fertiliser use efficiency of 41% (Fig. 3) is
comparable to that obtained by Strong et al. (1996b) in the
Warra experiment (45%) over a 6-year period that had a range
of seasonal conditions. Values for NUE for grain N yield
(43-59%) were similar to those recorded by Huggins and Pan
(1993) (51-72%) and Dalal et al. (1996) (43–65%).
We found that the relationship between the ratio of plant
available water and available N supply at sowing and grain
protein concentration developed by Dalal et al. (1997) for wheat
and barley is applicable in this environment. As concluded by
Dalal et al. (1997), the amount of plant available water (mm) to
a depth of 120 cm at sowing should be equally matched by
available N (kg N/ha), to produce approximately the 13% protein
concentration required for the APH grade of wheat. Malting
grade barley (10.2% protein concentration at 0% moisture
content) would require ~40% of the available N needed for APH
wheat. This knowledge enables the protein concentration for
APH grade wheat or malting grade barley to be targeted by
meeting any deficit in N supply from nitrate-N present in the
soil with that from fertiliser application at sowing. In 1996,
grain protein concentration did not reach the level for APH
classification, even with the highest rate of N addition
(90 kg N/ha), indicating that the top N fertiliser application rate
should have been higher for this relatively high-yielding crop.
At sowing in 1996, soil water characteristics of the site (crop
lower limit) had not been clearly defined, and available soil
water at sowing was apparently underestimated. Subsequent
determinations showed that plant available water/nitrogen ratio
was greater than 1 (1.3) and, therefore, APH grade wheat would
not have been expected (estimated grain protein, 12.2% v.
observed value of 12.3%). However, grain protein concentration
was >13% with the highest rate of N addition in all other
cropping years.
In this example, the ability of HOWWET? (Freebairn et al.
1997) to predict N fertiliser requirements was greatly improved
when used with measured, rather than estimated, water use
parameters. This indicates the importance of on-farm records in
validating such decision support programs.
The highest WUE for grain yield recorded in wheat was ~10.0
kg grain/ha.mm of water used, which was lower than the
maximum value recorded for wheat by Radford et al. (1992)
(18 kg grain/ha.mm) and Thomas et al. (1995) (15 kg
grain/ha.mm) in south-west Queensland. The considerably lower
values recorded in 1998 (2.6-3.7 kg grain/ha.mm) were
associated with above average rainfall during the growing period,
which resulted in periodic waterlogging, and the severe
occurrence of the leaf diseases, such as yellow spot in wheat and
net blotch in barley. The lower values for WUE for grain yield
obtained at Nindigully may have been associated with the timing
and effectiveness of rainfall in relation to stage of growth of the
crop and higher potential evaporative demand. Other factors,
such as soil-borne disease, may also have limited the efficiency
of water use under the continuous winter cereal system.

Wildermuth (2001) found that the incidence and severity of
crown rot (Fusarium pseudograminearum) in continuous wheat
increased at a faster rate and to a higher level with the application
of N fertiliser in this experiment. However, higher wheat yield
with N fertiliser application was associated more consistently
with greater water use efficiency than with greater water use.
Gross margin/water use could be a useful concept for
comparing the relative value and economic efficiency of crops
and management practices, as it integrates grain yield, grain
quality and water use. Although it is influenced by the relative
prices of crops within and between years, a value of ~$1/ha.mm,
which was the highest value recorded in these experiments,
appears to be a potential benchmark in this region.

Conclusions

Zero tillage has potential to improve winter cereal production in
south-west Queensland, particularly in drier growing seasons
than experienced in this study, by resulting in greater fallow soil
water storage or crop water use efficiency than conventional
tillage.
Profitable responses to N fertiliser addition in wheat and
barley can be obtained on long-term cultivated Vertosols in
south-west Queensland when soil water reserves at sowing are
at least 60% of plant available water capacity or rainfall during
the growing season is above average. Presowing soil profile
water and nitrate-N levels can be used to determine the N
fertiliser rate required to target grain protein concentration in
this environment. An integrative benchmark for improved N
fertiliser management appears to be gross margin/water use of
~$1/ha.mm.

Acknowledgements

The authors thank the Grains Research and Development Corporation
(GRDC) for financial assistance and Mr and Mrs D. Hill, 'Dunkerry South'
Nindigully, who provided land and other assistance for the trial. We
gratefully acknowledge the involvement and advice of members of the trial
management committee. We also thank Dr J. Standley, Mr J. Hagedoorn,
Mr K. Spann, Mrs J. Glasby and Mrs A. Pumfrey for soil and plant chemical
analyses, Mr G. McNamara, Ms J. Riddell and Ms M. Fraser for technical
assistance, Messrs, J. Henderson, G. Pauli, G. Kedzlie, D. Cooper, R. Norris,
D. Baills, M. Weston and P. Marsh for field operations, and Mrs A. Kelly and
Ms K. Bell for advice on trial design and statistical analysis.

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Dalal RC, Mayer RJ (1986b) Long-term trends in fertility of soils under
continuous cultivation and cereal cropping in southern Queensland. V.
Rate of loss of total nitrogen from the soil profile and changes in
carbon:nitrogen ratios. Australian Journal of Soil Research 24,
493-504. doi: 10.1071/SR9860493

Dalal RC, Strong WM, Weston EJ, Cooper JE, Lehane KJ, King AJ (1996)
Comparison of legumes and fertilizer nitrogen for wheat production in
subtropical Australia. In ‘Nitrogen economy in tropical soils'. (Ed.
N Ahmed) pp. 363–369. (Kluwer Academic Publishers: Dordrecht,
Netherlands)
Dalal RC, Strong WM, Weston EJ, Cooper JE, Thomas GA (1997)
Prediction of grain protein in wheat and barley in a subtropical
environment from available water and nitrogen in Vertisols at sowing.
Australian Journal of Experimental Agriculture 37, 351-357.
doi: 10.1071/EA96126
Department of Primary Industries (2000) 'Winter crop management notes.'
(Kingswood Press: Underwood, Qld)
Freebairn DM, Ward LD, Clarke AL, Smith GD (1986) Research and
development of reduced tillage systems for Vertisols in Queensland,
Australia. Soil and Tillage Research 8, 211–219. doi:10.1016/0167-
1987(86)90335-1
Freebairn DM, Loch RJ, Cogle AL (1993) Tillage methods and soil and
water conservation in Australia. Soil and Tillage Research 27, 303-325.
doi: 10.1016/0167-1987(93)90074-Y
Freebairn DM, Hamilton NA, Cox PG, Glanville SF, Dimes JP,
Holzworth D (1997) 'HOWWET? - estimates how much rain is stored
in the soil during a fallow and how much soil nitrate has accumulated.
A computer program, Version Number: 2.10.' (Agricultural Production
Systems Research Unit, QDPI/DNR/CSIRO: Toowoomba, Qld)
Gardner EA (1985) Soil water. In ‘Identification of soils and interpretation
of soil data'. (Ed. GE Rayment) pp. 197–234. (Australian Society of Soil
Science Incorporated, Queensland Branch: Brisbane)
Holford ICR, Doyle AD (1992) Yield responses and nitrogen fertiliser

Thomas GA, Gibson G, Nielsen RGH, Martin WD, Radford BJ (1995)
Effects of tillage, stubble, gypsum, and nitrogen fertiliser on cereal
cropping on a red-brown earth in south-west Queensland. Australian
Journal of Experimental Agriculture 35, 997-1008. doi:10.1071/
EA9950997

Thomas GA, Felton WL, Radford BJ (1997) Tillage and crop residue
management. In ‘Sustainable crop production in the sub-tropics: an
Australian perspective'. Queensland Department of Primary Industries
Information Series QI97035. (Eds AL Clarke, PB Wylie) pp. 195–213.
(Queensland Department of Primary Industries: Brisbane)
Turpin JE, Bridge BJ, Orange D, Thompson JP (1999) Water and bromide
movement in a Vertosol under four fallow management systems.
Australian Journal of Soil Research 37, 75-89. doi:10.1071/S97108
Weston EJ, Nason CN, Armstrong RDH (1975) Resources study and
problem analysis for primary industries in the Condamine-Maranoa
Basin of southern Queensland. Queensland Department of Primary
Industries, Division of Plant Industry Bulletin No. 731.
Wildermuth GB (2001) Crown rot - an important disease in the Western
Downs. In 'Western Farming Systems Project Results Booklet 2001'.
(Ed. KJ Lehane) pp. 30-31. Queensland Government (Department of
Primary Industries, Natural Resources and Mines) and Grains Research
and Development Corporation, QI 01093. (Greenridge Press:
Toowoomba, Qld)
Woodruff DR, Tonks J (1983) Grain yield variation in relation to time of
flowering of wheat genotypes. Australian Journal of Agricultural
Research 34, 1-11. doi: 10.1071/AR9830001

requirements of wheat in relation to soil nitrate levels at various depths.
Australian Journal of Soil Research 30, 683-694. doi:10.1071/
SR9920683

Huggins DR, Pan WL (1993) Nitrogen efficiency component analysis: an
evaluation of cropping system differences in productivity. Agronomy
Journal 85, 898-905.
Isbell RF (1996) ‘The Australian soil classification.' (CSIRO Publishing:
Melbourne)
Marley JM, Littler JW (1989) Winter cereal production on the Darling
Downs an 11 year study of fallowing practices. Australian Journal of
Experimental Agriculture 29, 807–827. doi: 10.1071/EA9890807
Perroux KM, White I (1988) Designs for disc permeameters. Soil Science
Society of America Journal 52, 1205-1215.
Radford BJ, Nielsen RGH (1983) Extension of crop sowing time during dry
weather by means of stubble mulching and water injection. Australian
Journal of Experimental Agriculture and Animal Husbandry 23,
302-308. doi: 10.1071/EA9830302
Radford BJ, Gibson G, Nielsen RGH, Butler DG, Smith GD, Orange DN
(1992) Fallowing practices, soil water storage, plant-available soil

Manuscript received 1 June 2005, accepted 6 February 2007

http://www.publish.csiro.au/journals/ajea

Table 6. Effects of N supply (N fertiliser applied at sowing + soil nitrate-N before sowing, 0-120 cm) on grain yield, grain protein (0% moisture content), grain weight, number of ears, gross margin and water use efficiency for zero tillage (ZT) barley


Question: What is the annual maintenance lime application rate in kg per hectare or tonnes per hectare for Australian grain farming systems?

The dollars and sense of liming: The Stantons' story

Second and third generation Island farmers, the Stantons,

run a mixed farming enterprise of cropping, sheep and
cattle.

Most of the farm land is inherently acidic and soil testing
over the last 10 years has shown a steady decline in pH. The
Stantons place a high priority on maintaining soil fertility
levels, especially in cropping paddocks. In the past, paddocks
with low pH were limed prior to being cropped. This means
that only some paddocks on each property have been limed,
while test results show that nearly all paddocks will need to
be limed at some stage.

"The current strategy is to set up a rotation of liming
approximately one fifth of the total land base or about 300
ha per year to assist in budgeting. It's envisaged that possibly
two full rotations will be needed to get all paddocks up to
ideal levels of close to 5.5 pHCaCl. The only deviation to this
plan is that paddocks being sown to lupins will not be limed
the year the lupins are sown. A budget of $20,000 has been
allocated per year to enable this to occur" explained Jenny
Stanton.

The Stock Jo

FARM FACTS

Primary Industries and Regions SA (PIRSA) staff with
assistance from the GRDC and Department of Environment,
Water and Natural Resources (DEWNR), have developed
three computerised decision support tools to assist
landholders and advisers to make better decisions in treating
soil acidity. They are:

Operators:

Richard and Kate Stanton with sons and daughters-in-law
Will and Jenny and Michael and Sarah.

Location:

Stokes Bay and on the central plateau
(SE of Parndana).

» Acid $Cost

used to estimate the impact of

acidification on production (i.e. the cost of not liming)

Size:

LimeCheque (Lime Sources Cost Comparison) — a tool
for calculating lime application rates for acidic soils and
comparing the costs of lime from different suppliers

»

1,500 arable ha (spread over four farms).
Cropping rotation:

Legume (lupins on sandy soils and beans on ironstone
soils), canola, cereal (wheat, barley or oats).

Maintenance Liming Rate Calculator — a tool for

>>>

calculating the replacement lime requirement to offset

Livestock:

annual acidification and maintain the current pH of the
soil.

Merinos, 120 cattle, Poll Dorset stud.

Pastures:

All the tools can be found at

Subclovers and annual grasses plus 250 ha kikuyu.

http://agex.org.au/project/soil-acidity/

Soil Type:

Jenny took one cropping paddock "Middle of the Road" as
an example to test the calculators.

Ironstone to deep sands. Main soil issues are acidity,

non-wetting sandy soils and waterlogging.

Average rainfall:

582 mm.

SOUTH

Natural Resources

AUSTRA

Kangaroo Island

Government

of South Australia

The Cost of Not Treating Soil Acidity tool (Figure 1) shows
that without liming there will be a $1,545 loss in production
over the next four years of crop; run that over 10 years and
the cost will be almost $3,900!

"We put 100 kg/ha of Calciprill down the tube to give a
quick pH lift and boost calcium levels as legumes, especially
beans, love calcium just like grasses love nitrogen. The beans
yielded well, averaging 2.5 t/ha, compared to an average
of 1.8 t/ha pre-liming" Jenny said. "Since then I've noticed
a distinct difference to the paddock: feed stays greener for
longer once the soil profile starts to dry out, compared to
adjacent paddocks that haven't been limed and the actual
soil structure has changed, becoming more friable".

The Lime Sources Cost Comparison tool (Figure 2) was used
to calculate the cost of moving the pH from 4.5 to 5.5 in
one lime application. This requires a lime application rate of
4.3 t/ha at a total paddock cost of $2,260. In a nutshell a
lime expenditure of approximately $2,300 will save $3,900
in lost production or a 70% return on their money. Due to
the potential for inducing manganese deficiencies at this
high lime application rate, the Stantons would probably
apply two applications of about 2.5 t/ha spread over the
10 years.

The paddock results that really convinced the Stantons of
the benefits of liming was when they purchased a piece of
L and N Deer's property — Caledonia.

"In the year before we purchased the property, Lloyd had
limed a paddock before sowing it to barley as barley is quite
intolerant of low pH. As we cropped the whole property, we
removed all the internal fences and the old barley paddock
plus surrounding paddocks were sown to wheat. The old
barley paddock stood out with an increase in yield of about
20-30% more than the surrounding paddocks. In 2007
the paddock was tested and the old barley paddock was
pHCaC 5.8 and surrounding areas only 4.6. For many years,
until the surrounding areas were limed, the yield difference
was extremely noticeable. This very visible response to lime
made us aware of the real economic benefits of maintaining
our soil pH" Will said.

Once paddocks have been limed the soil will still acidify. The
Maintenance Liming Rate Calculator (Figure 3) calculates
how much lime is needed to maintain soil pH levels. It also
helps identify he key drivers of acidity. In this example, a key
cause of low pH is the acidifying effects of nitrogen inputs,
either via the legume component of the hay/cropping
program or the application of nitrogenous fertilisers. On
average almost 0.5 t of lime is required per year just to
balance the acidification.

The Middle of the Road paddock was actually limed at 3t/ha
in 2013 and the paddock was sown to beans. In hindsight,
the paddock should have been limed the year before to
enable the limesand to fully react with the soil.

Once the Stantons had seen the results from the tools, they
felt a lot more comfortable about their budgeted annual
lime expenditure.

"Basically we will recoup that expenditure within a year or
two of liming", Jenny said.

CENTRAL WEST

ENTRAL WEST

Spreading

1828

TAKE HOME MESSAGES

Use the tools - they are easy to use and real eye opener on what acidity can be
costing you.

Significant yield improvements have been seen when cropped paddocks are limed.
Make liming a part of your annual program.

Figure 1: The cost of not treating soil acidity

This year

Current pH value (CaCl2)

Next year

Three years time

Four years time

Select crop type

Select crop type

Select crop type
wheat (tol)

Select pH value

Select crop type
canola

beans

4.5

beans

Enter expected crop yield t/ha
2

Enter expected crop yield t/ha

Enter expected crop yield t/ha

Enter expected crop yield t/ha
3.5

2

2

Enter crop pasture value $/ha
$625

Enter crop pasture value $/ha
$200

Enter crop pasture value $/ha
$400

Enter crop pasture value $/ha
$625

Estimated loss of production

Estimated loss of production
0.7 t

Estimated loss of production

Estimated loss of production
0.8 t

0.8 t

1 t

Estimated value of lost production Estimated value of lost production Estimated value of lost production Estimated value of lost production
$500
$407

$138

$500

Cumulative loss/ha $1,545

Cumulative loss

$ Value

Yield

4

ི༔ ༔ ༔ ༔ ༔ ་

expected
actual

expected

actual

3

2

t/ha

0

0

wheat (tol)

wheat (tol)

canola

beans

beans

canola

beans

beans

Figure 2: Lime sources cost comparison

Lime rate calculator

How

Paddock middle froud

니 다

Target Jme ratƆng C & Adjusted

Zone Area

ha H (C&Cl, Texture +[CaCl,]

Lime rate

Application

Enter

Select

Enter

Enter

Select
sandy loam

DG

high

1

5.0

5.5

5.0

information

2

00

Ε

DO

0.0

Lime Sources Comparison

Source 1

Source

Select

Neutralizing
Value (NV) or

SANJAN

Neutraliving

Tonnequined

42 km

om

Either

5/km/t

$6.30 St

St

517.50 5

Enter

Spreading cot

Or

Contract Scot

Sit

Sit

5

即

Total Sje

Product & cart

575

Zone1
Jone

50

Jone

575

Padlock

190

Quantity of lim

Figure 3: Maintenance liming rate calculator

Top Soil

Paddock name:

Enter
Middle of Road

Select

Loamy Sand

Texture:

Your

+

H

+

H

Year (20.....

2016

2019

2014

2010

2015

2012

Enter

2011

Annual Rainfall

555

854

518

Enter

771

625

Saturated Soil

Tes

Yes

Select

Yes

Yes

Yes

Leaching S

35%

85%

85%

85%

85%

Product Removal

Clover hay

Oilseed

Glower hay

Select

Grain legume

Crop Type

Cereal grain
3.3

Cerea

Yield (tonnanha||

54

2.5

19

Enter

2.1

Lime replacement/tonne grain yield (ba/ha)

40

40

20

9

2

9

2

Lime required due to product removal [kg/ha)

Total (kg/ha)

144

258

29.7

46

526.2

4.2

8.8

40.5

Legume Fixed Nitrogen

kg N fixed per tonne legume production

30

60

0

0

C

0

188

Legume fixed nitrogen (kuha]

109

1935

0

0

0

G

Leaching adjusted lime requirement (kg/ha/kg N
Lime required due to legume fixed N (kg/h)

5.1

G.O

3.1

0.0

51

G.D

Total (kg/h)

4227.20

550.4

502.11

0

+424.7

Fertilisers inputs

Fertiliser 1. (Seeding)

Fertiliser Type

Single Super

ОДР

Select

MAP

DIAP

MAP

MAP

|Rate fertiliser (kg/ha)

Enter

GC

40

50

BO

a

Product N (

10.0

10.0

100

18.0

C.O

18.0

Rate of nitrogen

9

0

B

8.6

9

Leaching adjusted lime requirement (ke/ha/kN

0.0

4.9

6.7

6.7

6.7

4.9

Lime required due to seeding fertiliser applications (kg/h)

43.7

Total (kg/ha)

166

57.3

0.0

58.3

43.7

282.0

Fertiliser 2.

Fertiliser Type

Select

Urea

Ureda

Unea

Urea

Pate fertilizer (kg/ha)

Enter

200

150

Product N (

0.0

460

46.0

460

0.0

460

Rate of nitrogen

345

92

0

10

69

92

Leaching adjusted lime requirement (kg/ha/kg N
Lime required dun to in-crop fortificer applications [kg/ha

00

5.1

5.1

5.1

3.1

Total (kp/ha)

105.6

1815

211.1

0.0

0.0

1090.0

281.5

Annual replacement lime required (kg/ha)

355.0

474.5

982.3

5216
2598.3

272.Z

Cumulative lime required over"n" years (kg/ha)

474.5

1456

INTL

26035

Summary of lime requirement to address annual acidification

Influence of management practise on total lime required

Number of years of management data (n)

7

Cumulative replacement required by management practise (kg/ha)

Lime required due to product
removal (kg/ha)

Lime required due to product removal (kg/ha)

526.2

34%

9%

Lime required due to legume fixed N (kg/ha)

1344.9

Lime required due to legume
fixed N (kg/ha)

Lime required due to seeding fertiliser applications (kg/ha)

282

Lime required due to in-crop fertiliser applications (kg/ha)

1090.9

Lime required due to seeding
fertiliser applications (kg/ha)

Total cumulative lime required over "n" years (kg/ha)
Average annual replacement lime required (kg/ha)

3243.9

16%

41%

463.4

Lime required due to in-crop
fertiliser applications (kg/ha)

Recommended lime application rate for 10 year period (t/ha)

4.6

Lime maintenance rate

FOR MORE INFORMATION

Annual replacement lime required (kg/ha)

Natural Resources Kangaroo Island

Lime required due to legume fixed N (kg/ha)

Lime required (kg/ha)

37 Dauncey Street Kingscote SA 5223

P 08 8553 4444 E kinrc@sa.gov.au

www.naturalresources.sa.gov.au/kangarooisland

The project is supported by Natural Resources Kangaroo
Island through funding from the Australian Governments
National Landcare Program.

Natural Resources

National
Landcare
Programme

Kangaroo Island

4

2

3

5

7

6

Australian Government

Year

Once paddocks have been limed the soil will still acidify. The
Maintenance Liming Rate Calculator (Figure 3) calculates
how much lime is needed to maintain soil pH levels. It also
helps identify he key drivers of acidity. In this example, a key
cause of low pH is the acidifying effects of nitrogen inputs,
either via the legume component of the hay/cropping
program or the application of nitrogenous fertilisers. On
average almost 0.5 t of lime is required per year just to
balance the acidification.

Total cumulative lime required over "n" years (kg/ha)
Average annual replacement lime required (kg/ha)