Australian Agriculture: Broadacre Crops methodology

Latest release

Reference period

2024-25 financial year

Released

2/03/2026

Next release Unknown

Release date and time

30/06/2026 11:30am AEST

Overview

Scope

Includes crop production, value, cropping area and counts of businesses for key summer and winter broadacre crops and sugarcane.

Excludes hay and silage.

Geography

Data is available for

Australia
States and territories
SA2

Source

Source data includes:

Agricultural levy payer register transaction records
Satellite crop map imagery
Industry harvest information

Collection method

Agricultural levy payer register records from 12 months after the crop harvest are combined with satellite derived crop mapping that relates to the growing period.

Concepts, sources and methods

Production and value refers to the amount and local value of levied (sold) production. Crop area refers to total growing area. Business counts relate to number of businesses paying levies.

History of changes

Not applicable for this release.

Introduction

The Australian Bureau of Statistics (ABS) is modernising the way official agricultural statistics are produced to better support Australian agriculture. These changes were outlined in early 2023 in Modernising ABS Agriculture Statistics which explained why the ABS is modernising its Agriculture Statistics Program and the guiding principles being followed. The first iteration of official statistics under the new methodology were released in June 2024 with the release of 3 sets of agricultural estimates:

A further update was provided with the release of Modernising agricultural statistics: Update on achievements and remaining data gaps in October 2024.

A key part of the modernisation has been the development of partnerships with industry and government to identify new data sources and develop new statistical methods. This has reduced respondent burden on farmers, and created greater consistency between existing data sources which helps to build trust in the statistics.

The broadacre crop statistics have been developed in partnership with the Grains Statistics Working Group which includes a mix of industry and government experts.

The methods presented below have been refined with input from this group to produce broadacre crop statistics on the production and local value of broadacre crops sold through the levy system, the area of crops grown, and the number of businesses paying levies on broadacre crops. This marks the third release of agricultural broadacre statistics under the modernised approach described below.

ABS agricultural statistics are being released in a staggered manner to ensure statistics are published as close to the reference period as possible. This release adds summer broadacre and sugarcane crop estimates at the Statistical Area 2 (SA2) level and marks the final release of broadacre statistics for 2024-25.

Data sources

A summary of the key data sources used to produce the broadacre crop statistics contained in this publication is presented below.

Levy Payer Registers

Satellite derived crop mapping

Industry data

Concepts

Estimates of broadacre crop production, value and business counts are calculated using information reported in DAFF levy returns. Sugarcane estimates also utilise information from ASM and rice estimates utilitse information from SunRice.

Production and local value estimates relate to the tonnage and value of crops sold which are subject to a levy.

Local value is also known as farm-gate price and is the value of the commodity at the place of production.

Business count estimates relate to the number of unique ABNs associated with levy returns for each crop.

Crop areas are calculated using satellite imagery derived crop mapping to estimate the area of broadacre crops grown at the paddock level. This data is aggregated to the SA2 level. The estimated area of crop includes all land identified as growing a particular crop regardless of it is final use: harvested and sold, harvested for on farm use or grazed off.

Scope and coverage

Estimates presented in this publication are based on information extracted from the Levy Payer Register for crops produced (grown for sale) in the year end 30 June. Sale of the crop may have occurred in the following financial year.

Statistics relate to crop produced for commercial purposes and exclude crops produced for hay and silage or domestic purposes (e.g. on-farm animal feed and grain held for future crops). The Levy Payer Register also excludes reporting of very small production amounts which are not leviable (where the total levy payable is less than $25 a year).

Value information contained in the DAFF Levy Payer Registers is based on local value, also known as farm-gate value.

The DAFF Levy Payer Register for broadacre crops contains records at the business (ABN) level.

The satellite imagery derived crop tables provide an estimate of actively growing crop areas within its coverage, including those not harvested for commercial purposes:

Crop map data for sugarcane supplied by the Queensland Department of Environment and Sciences relates to the actively growing sugarcane crop in Queensland and northern New South Wales
Crop map data supplied by DAS covers all of Australia’s major broadacre cropping regions but excludes some cropping activity undertaken beyond those regions. Crop area estimates outside of the DAS coverage are made using the Levy Payer Register production amounts.

How the data is produced

The levy payer register, satellite derived crop mapping, and industry data that support the broadacre estimates are produced for a range of purposes and a number of data editing, adjustment and data transformation steps take place to produce statistics from these sources. These steps include:

Levy record data repair, editing and geo-coding
Levy record allocation to crop regions
Reallocation and benchmark processes to ensure data coherency and confidentiality.

Levy record data repair, editing and geocoding

DAFF Levy Payer Register data was extracted from the DAFF Levy Payer Portal on 31 October 2025 for winter broadacre crops and sugarcane, and on 31st January 2026 data was extracted for summer broadacre crops. These dates have been determined to best represent crops sold from the 2024-25 harvest.

DAFF levy records were aggregated by ABN and SA2.

Records are geocoded to SA2s based on reported business address. Records with incomplete or missing address details have addresses repaired programmatically prior to geocoding.

Automated editing is applied to sales tonnage, based on sales price per tonne, with crop-specific outlier thresholds set in consultation with industry representatives and data analysis. This corrects for reporting issues such as production amounts being incorrectly entered as kilograms instead of tonnes. Sales amount divided by median price is used to calculate an adjusted tonnage for records that fall outside outlier thresholds. The impact of the price-based editing on crop tonnage varies by crop (Table 1).

Example of price-based editing for wheat:

outlier limits for price per tonne were established for wheat in 2024-25
a number of records reported a sales value and tonnage that was outside of the limits, and of these the majority reported unrealistic prices of less than $10/t
records falling outside of these limits were changed in line with the median price for the non-outliered records
following price-based editing the revised wheat tonnage decreased from 52.5 million tonnes to 34.8 million tonnes (see Table 1)

Table 1 – Impact of price-based editing on interim tonnage estimates, 2024-25
Crop	Levy data tonnage	Tonnes edited	% Tonnes adjusted
Barley	25,546,112	-11,812,706	-46%
Canola	6,846,924	-33,634	<1%
Chickpeas	2,053,845	-5,921	<1%
Faba beans	761,553	-28,671	-4%
Field peas	872,492	-755,499	-87%
Lentils	1,050,143	-20,884	-2%
Lupins	944,792	-268,751	-28%
Maize	451,607	232	<1%
Oats	1,378,928	-227,417	-16%
Rice*	523,286	n/a	n/a
Sorghum	2,655,443	-51,942	-2%
Sugarcane*	28,283,808	n/a	n/a
Wheat	52,455,983	-17,676,804	-34%

*Method requires both tonnage and local value levies data. Method not currently applicable for rice and sugarcane

Levy record allocation to crop regions

Levy records are assigned to an SA2 region based on the geocoding process.

Levy records outside of crop growing areas are identified by a spatial overlay with crop map area data. Production, value and business counts from these levy records are allocated proportionally based on crop area in SA2s within the same region, usually the same Statistical Area 4 (SA4).

While satellite derived crop map data was available for most cropping areas, levy data also appears in valid locations beyond the satellite map coverage. For levy data reported outside of crop map coverage areas, the following criteria were used to determine if levy data reported in these locations were valid:

the levy data were reported outside of ‘significant urban areas’
multiple records existed and the tonnage reported met a crop-specific minimum tonnage limit

Where these criteria were met the data were considered valid for producing estimates and the levy records were left in the reported SA2. Historical data was employed to validate the parameters used.

Example of location-based reallocation:

Image

Description

An infographic with an example of location-based reallocation:

The Infographic show three panels with a SA2 region in each.
The middle panel shows a SA2 which covers a regional town and the SA2 has reported 4,000 tonnes of crop production.
No cropping area was detected by satellite imagery in the SA2 covering the regional town.
Satellite imagery identified 2,000 hectares of crop production in the two neighbouring SA2s shown in the left and right panel. The left panel shows a SA2 with 400 hectares of crop production (20% of 2,000 hectares) and the right panel shows a SA2 with 1,600 hectares of crop production (80% of 2,000 hectares).
The 4,000 tonnes of crop production for the regional town SA2, was reallocated to the two neighbouring SA2s shown on the left and right panels, based on the proportion of crop area in those SA2s.
The SA2 shown in the left panel that had 400 hectares (20%), received 800 tonnes, 20% of the 4,000 tonnes originally reported in the regional town SA2 and the SA2 shown in the right panel that had 1,600 hectares (80%), received 3,200 tonnes, 80% of the 4,000 tonnes originally reported in the regional town SA2.

Levy business locations were sometimes reported as addresses in a regional centre or capital city, placing the data in non-growing areas. Location-based reallocation was used to move the crop production data from these records into known growing area SA2s in the surrounding region (usually SA4). The reallocation was based on the area of crop in each surrounding SA2 as shown in the diagram above. Table 2 shows the amount of incorrectly located data that was reallocated to nearby areas where crop mapping data shows the crop was grown in 2024-25.

Table 2 – Impact of location-based reallocation, 2024-25
Crop	Tonnes reallocated	% Tonnes reallocated
Barley	1,081,042	8%
Canola	548,903	8%
Chickpeas	225,760	11%
Faba beans	106,281	15%
Field peas	23,569	20%
Lentils	78,849	8%
Lupins	69,307	10%
Maize	61,588	14%
Oats	76,513	7%
Rice	6,295	1%
Sorghum	295,766	11%
Sugarcane	2,011,189	7%
Wheat	2,337,963	7%

Reallocation and benchmark processes to ensure data coherency and confidentiality

Following the initial allocation of levy records to crop regions, reallocation, benchmark and confidentiality processes are undertaken to improve the quality and utility of the estimates whilst also protecting privacy.

Yield-based reallocation involves the use of a crop-specific yield limit to iteratively reallocate records from SA2s with unrealistic yields to the surrounding SA2s in the region (usually SA4). This is based upon their respective crop map areas, to achieve an acceptable yield. This is necessary because large broadacre cropping farms often span multiple SA2s but the levy record is reported with a single address that falls in one SA2. The recipient SA2 regions gain tonnage, sales value and business counts, resulting in yields more in line with those elsewhere in the region. Table 3 describes the impact of yield-based reallocation on production tonnage in 2024-25.

Hypothetical example of yield-based reallocation for canola:

following initial allocation of crops to regions, the Victorian regional centre SA2 of Horsham was reporting 31,000 tonnes of canola sold. Satellite imagery indicated only 481 hectares of canola was grown, giving rise to an unrealistic ratio of 64 tonnes per hectare
yield-based reallocation redistributed all but 1,732 tonnes to SA2 regions within the corresponding SA4 of Victoria-North West, including Horsham Surrounds, Buloke, Yarriambiack and Nhill Region. This saw only minor increases in the tonnes:hectares ratio for these larger cropping regions and the ratio for Horsham dropped by 94% to 3.61 tonnes per hectare

Table 3 – Impact of yield-based reallocation, 2024-25
Crop	Tonnes reallocated	% Tonnes reallocated
Barley	977,726	7%
Canola	679,412	10%
Chickpeas	137,450	7%
Faba beans	16,691	2%
Field peas	0	0%
Lentils	63,340	6%
Lupins	14,090	2%
Maize	23,140	5%
Oats	49,398	4%
Rice	137,529	26%
Sorghum	23,140	5%
Sugarcane	5,927,767	21%
Wheat	2,317,406	7%

Benchmarking is an additional step undertaken for sugarcane outputs. Regional industry data supplied by ASM was used to benchmark and, where needed adjust SA2 data to align at a regional level with these industry amounts.

Confidentiality tests were applied for each crop across national, state and all SA2 regions to ensure that production outcomes for individual businesses cannot be identified in the data. Regions that fail these checks had data reallocated to surrounding SA2 regions, using a proportional re-allocation method, that reiterates until the confidentiality criteria are met. This has an extremely minor impact on the data as can be seen in table 4.

Table 4 – Impact of confidentiality, 2024-25
Crop	Tonnes reallocated	% Tonnes reallocated
Barley	2,783	0.20%
Canola	10,584	0.16%
Chickpeas	2,157	0.11%
Faba beans	533	0.07%
Field peas	272	0.23%
Lentils	610	0.06%
Lupins	814	0.12%
Maize	4,839	1.07%
Oats	12,289	1.07%
Rice	0	0.00%
Sorghum	699	0.03%
Sugarcane	0	0.00%
Wheat	1,707	0.00%

Local value for sugarcane and rice

Reliability of estimates

The satellite derived crop map data is used to improve the location reliability of levy record data. The crop map enables identification of records that lie outside of crop map areas. Its use reduces the impact of data appearing in metropolitan and other urban areas. As a consequence, it improves reliability and coherence between production and growing location supporting annual production of statistics at fine geographic levels.

Where levies are based upon sales value, reported tonnage data in the levy records were in some cases inconsistent with the corresponding sale value, such that a price of $0.02 per tonne sold could be found. This typically results from tonnage data being reported in kilograms. Using such unrealistic data would undermine the quality of statistics produced from it. To address these issues, break-even price data provided by the Grains Research and Development Corporation (GRDC) and wider analysis were used to outlier unrealistic prices and adjust the tonnage in line with the median price for non-outlier records for the crop.

Yield testing identifies where levy record tonnages have created unusually high ratios of tonnage to satellite crop map data in an SA2. Data is reallocated to nearby cropping areas to bring the ratio into more realistic magnitudes, improving quality and utility.

Confidentiality and rounding

Some detailed estimates in this publication may have been confidentialised to avoid potential identification of agricultural holdings in accordance with the Census and Statistics Act 1905 and the Census and Statistics Determination 2018.

Where detailed estimates have been suppressed for reasons of confidentiality, they have been included in relevant aggregated totals.

Where figures have been rounded, discrepancies may occur between sums of the component items and totals.

Data limitations

These statistics are produced through the integration of multiple data sources. This integration of multiple data sources can help to manage the strengths and weaknesses of different data sources some of which are developed for a range of purposes that are not purely statistical. A number of assumptions have been made in the use of these data sources and these are highlighted below:

Crop mapping data is assumed to be correct in identifying the accuracy of crop area and crop type. There are potential errors associated with each of these that are not measured.
Yield limits are applied consistently for each crop within each region when reallocating levy data, these yield limits do not consider localised factors like soil condition or irrigation.
A small percentage of crops are grown outside of the satellite derived crop mapping coverage. Yields from similar climatic areas are used to calculate area from the production amounts.
Production amounts relate to tonnes sold through the levy system. For some crops this will closely reflect total production but for others like oats it will be significantly less than the total production. For these crops it is not sensible to calculate yields by comparing with the total crop area.
Address information on levy returns may not accurately reflect the location of actual crop production. Where this can be identified, the production and value amounts are reapportioned according to the crop map distribution because no other data was available to inform this. There is error associated with this that cannot be measured.
Where errors are identified in levy payer register records through analysis of the price per tonne, corrections are made to the estimated tonnes using a median price per tonne on the assumption that the dollar amount is correctly reported.
Levy payer register records from the 12 months after the harvest are assumed to represent the harvest total but some crops may be stored for more than 12 months before sale, meaning they will be represented in the following years data. Industry input suggests such long-term storage is uncommon.

Revisions

Revisions are a change to a published value and may arise due to a variety of reasons.

Revisions may be applied to broadacre crop estimates due to:

Revisions to source data
Refinements to decisions made around the treatment of data anomalies in the series
Implementation of methodological and process improvements

Methodological enhancements

The methods and data sources used to produce these estimates will be subject to ongoing review to improve the accuracy and timeliness of outputs.

Comparability

The are conceptual differences between the data produced by ABS' Agricultural Census and agricultural surveys and the data produced using the new data sources appearing in this publication. These include:

the scope of the survey based estimates was businesses with an estimated value of agricultural output (EVAO) of $40,000 or more. Non-survey data sources do not have the EVAO restriction and measure the full extent of Australian agriculture sold and leviable through the DAFF Agricultural levies registers.
survey based estimates were subject to sampling variability and may have differed from the estimates that would have been produced if information had been obtained from all businesses. In comparison, it is compulsory to report any leviable amounts of crops sold to DAFF under government legislation.
survey based estimates for broadacre crops included production amounts not sold and those used on farm (for example for stock feed or silage). DAFF Levy Payer registers capture leviable amounts of crops sold only. For some crops such as Oats and Sorghum there is a significant difference between total production and what is sold and captured by the levy system.

For more information on the historical survey-based estimates see Agricultural Commodities, Australia.

How the data is released

Geographic classifications

National, state and territory statistics for the levied production, local value of levied crops, area and the count of businesses paying levies for broadacre crops are available in this publication.

Sub-state SA2 broadacre statistics are available via the ABS' Data Explorer.

National, state and territory, and SA2 estimates have been produced using the Australian Statistical Geography Standard (ASGS) (Edition 3).

Related publications

Other ABS publications containing agricultural data are listed on the ABS’ Agricultural Statistics page. The ABS also issues a daily Release Advice on the website which details products to be released in the week ahead.

Abbreviations

Standards and classifications

Australian Statistical Geography Standard (ASGS), Edition 3, July 2021 - June 2026

Abbreviation	Definition
'000 ha	thousand hectares
'000 t	thousand tonnes
ABN	Australian Business Number
ABS	Australian Bureau of Statistics
ACT	Australian Capital Territory
ASGS	Australian Statistical Geography Standard Edition 3
ASM	Australian Sugar Manufacturers
ASMC	Australian Sugar Milling Council
CCS	Commercial Cane Sugar
DAFF	Department of Agriculture, Fisheries and Forestry
DAS	Digital Agriculture Services
EVAO	Estimated Value of Agricultural Operations
GRDC	Grains Research and Development Corporation
ha	hectare
na	not available
np	not published
n.e.c.	not elsewhere classified
no.	number
NSW	New South Wales
NT	Northern Territory
Qld	Queensland
SA	South Australia
SA2	Statistical Area level 2
SA4	Statistical Area level 4
t	tonne
Tas.	Tasmania
Vic.	Victoria
WA	Western Australia
xlsx	Microsoft Excel spreadsheet file

APA

Citation