Carbon farming participation: five insights from 402 producers

Carbon farming participation: five insights from 402 producers

by | Oct 22, 2026 | Agricultural Policy & Programs

For government agencies, reaching producers is only part of the challenge. Producers also need to understand a program and see a reason to take part.

A 2024 KG2 telephone survey of 402 producers examined awareness, familiarity and attitudes towards carbon farming. The findings offer five considerations for agencies
designing and evaluating producer programs. As the research focused on carbon farming, its lessons should be tested before applying them to other program areas.

1. Interest can run ahead of understanding

Producers rated the importance of managing carbon in their business at 6.7 out of 10. Their interest in generating carbon credits averaged 6.1, while familiarity with carbon farming was lower, at 4.6.

Interest does not necessarily mean producers understand what participation involves. Clear information about requirements, financial implications and ongoing commitments can help them make an informed decision.

2. Awareness does not guarantee participation

Just over half of producers (51%) were aware of the national carbon credit scheme. However, 93% had not participated in any of the five schemes and programs examined.
Awareness of two other programs was 18% and 13%, with participation in each at 1% or less. These results show why awareness and participation should be measured separately. The survey figures do not establish why participation was low.

3. Financial return was the factor named most often

When asked what would most influence their decision to join a carbon project, 35% of producers named the financial return. A better understanding of the project was mentioned by 13%, benefits to soil and land by 10%, and red tape and paperwork by 5%.

This suggests agencies should explain potential returns, costs and obligations clearly. Producers need enough information to assess how a project might fit their business.

4. Producers use different information sources and formats

The internet was the first place 41% of producers said they would look for information about carbon farming. The agriculture department was named by 14%, friends and family by 10%, and 12% did not know where they would look.

Fourteen per cent had previously dealt with a government organisation about carbon farming. Their average familiarity was 5.7 out of 10, compared with 4.5 among those who had not. This is an association; it does not show that contact with government caused greater familiarity.

In-person workshops within 100 kilometres were considered the most helpful format by 36% of producers, followed by case studies (21%) and online resources and webinars (15%). A mix of channels may better reflect how producers look for and prefer to receive information.

5. Averages can hide regional and enterprise differences

Familiarity with carbon farming ranged from 4.2 out of 10 in one region to 5.1 in another. Interest in generating credits ranged from 5.5 to 6.6.
Sheep and beef producers recorded the highest average familiarity (5.3), while grain-only producers recorded the lowest (4.0). Where sample sizes allow reliable comparisons, results by region and farm type can help agencies identify different information needs.

What agencies can take from the findings

The survey suggests agencies should look beyond awareness when assessing producer engagement. It may be useful to understand what producers know, what they value, where they seek information and how results differ between producer groups.

These findings relate to carbon farming. Further research would be needed to establish whether the same patterns apply to other programs, such as drought support, biosecurity or natural resource management.

About the research

The findings are from a 2024 KG2 telephone survey of 402 producers about carbon farming, conducted for a government agency.

The research examined producer awareness, familiarity, attitudes and participation relating to carbon farming and carbon-related programs.

AI on Australian grain farms: grower interest and the challenges of adoption

AI on Australian grain farms: grower interest and the challenges of adoption

by | Oct 22, 2026 | Agricultural Technology & Data, Farmer Insights & Behaviour

Seven in ten grain growers surveyed by KG2 said they would definitely or probably use an AI farm assistant.

That interest provides a starting point for agricultural technology developers, but it leaves an important question: what would make growers use one in practice?

KG2’s 2026 telephone survey of 350 grain growers explored where an AI assistant might fit into farm decision-making. The findings suggest that practical usefulness, local information and confidence in the advice would matter. They also highlight a challenge that product design cannot overlook: unreliable connectivity.

The research tells a connected story about the distance between interest in a new tool and a decision to adopt it.

Growers see potential, but reservations remain

Among surveyed growers, 30% said they would definitely use an AI farm assistant, while 40% said they probably would. Its perceived value averaged 6.8 out of 10, with 44% rating it eight or higher.

However, responses varied. One in ten rated its value at just one out of 10, and most of that group felt a tool could not replace practical farming experience.

The results show openness to the concept alongside reservations about its role. They measure stated willingness, rather than actual use. Whether that interest translates into adoption would need to be tested with a working product in farming conditions.

Time-sensitive decisions stand out

The strongest priority was the timing of input purchases, spraying and weather-dependent operations. This decision area received an average importance rating of 8.7 out of 10, the highest of any tested.

Spray and chemical timing was also the decision most frequently identified as taking the greatest time or effort, named by 30% of respondents.
Crop and variety selection remained important, averaging 7.7 out of 10. Yet no respondent identified it as the decision requiring the most effort.

This distinction helps explain where decision support might be useful. An important decision is not necessarily the one growers find most demanding. In this survey, timing stood out both for its importance and for the effort involved.

Information needs to reflect the farm

Weather and rainfall forecasting was the information growers most often found hardest to obtain, identified by 37%. Several respondents questioned the usefulness of a forecast for a location 40 kilometres from their property.

Pricing, market timing and forward contract decisions followed at 23%.

These responses point to a need for information relevant to a grower’s location and circumstances. Access to information alone may not resolve the problem if it does not help with the decision at hand.

For an AI farm assistant, this raises questions about the sources it uses and how clearly it communicates their limitations. The findings do not demonstrate that AI can improve weather forecasts or market predictions. Any such capability would need evidence from testing.

Digital tools are familiar, but access is uneven

Many respondents already used digital systems. Seventy per cent used a machine or GPS display, and 63% used farm management software. Only 10% reported having no formal system.

Connectivity ratings were less encouraging. Mobile reception averaged 5.1 out of 10, while internet connectivity averaged 5.5. Some 43% rated their mobile reception at four or below.

Existing use of digital tools therefore does not mean growers can reliably access an online assistant wherever they work. A product that depends on a continuous connection could be difficult to use during field operations.

These results make connectivity a practical consideration for agricultural AI development, alongside the quality of the information a tool provides.

Confidence comes from seeing the tool work

Reliability and accuracy were cited as reasons for hesitation by 33% of growers. Before committing, 34% said they would need to see other growers in their region using the tool and getting results. The same proportion wanted a free trial or demonstration.

These preferences suggest that growers want an opportunity to judge performance and relevance for themselves. Local examples and practical trials could provide that opportunity, although their effect on adoption would still need to be tested.

The research also found that willingness to share farm records with an AI assistant averaged 6.3 out of 10. This indicates some openness, without suggesting universal comfort with sharing data. Clear information about how records are accessed, stored and used would help growers make an informed choice.

Meanwhile, 43% of respondents had never used a chatbot or smart assistant. For these growers, assessing an agricultural AI assistant could also involve becoming familiar with a new type of tool.

What developers can take from the findings

The survey suggests a focused approach to product development: begin with a decision growers find demanding, then test whether an assistant provides useful support under real farm conditions.

Time-sensitive operations offer a potential starting point. Trials could examine whether the information is sufficiently local, whether advice is reliable, and whether growers can understand the uncertainty behind it.

Connectivity should also be part of testing. Developers could investigate which functions remain useful without reception, what information can be retained, and how the tool behaves when a connection returns.

Practical demonstrations would give growers a way to assess those capabilities before committing. Testing should also explore how an assistant can complement existing farming knowledge and what growers need to know before sharing records.

These are development priorities suggested by the findings, rather than proven drivers of adoption.

From interest to practical adoption

KG2’s research shows that many surveyed grain growers are willing to consider an AI farm assistant. It also gives a clearer picture of what deserves attention before that interest can become regular use.

The next step is to demonstrate useful, reliable support for the decisions growers already face. Local relevance, workable connectivity and visible results will be important areas to evaluate as agricultural AI products are developed and tested.

About the research

KG2 conducted a telephone survey of 350 Australian grain growers in 2026, drawing participants from its agricultural database. Respondents were predominantly located in the southern grain belt, and 87% operated mixed grain and livestock enterprises.

The findings describe the surveyed growers’ views and should not be read as nationally representative estimates. Stated willingness to use an assistant also differs from observed adoption.

Beyond certification: what KG2’s research reveals about Australia’s organic industry

Beyond certification: what KG2’s research reveals about Australia’s organic industry

by | Oct 22, 2026 | Agricultural Markets & Industries

Australia’s organic industry extends beyond the businesses captured in certification records.

Understanding those other operators matters when assessing the industry’s size, developing policy or identifying where support is needed.

A national study conducted by KG2 for the Australian Government examined 358 organic operators, including certified and uncertified businesses. It explored their production practices, commercial circumstances and expectations for growth.

One finding stood out: 45% of uncertified operators believed compulsory certification would be useful. Yet uncertified producers also identified cost, limited commercial benefits and administrative requirements as barriers to becoming certified.

The findings reveal how support for stronger organic assurance can coexist with practical concerns about participating in certification.

Research note: This article revisits research conducted in December 2021 and published in February 2022. Findings reflect respondents’ circumstances and attitudes at that time.

The Department of Agriculture, Water and the Environment commissioned the research to better understand organic operators, including smaller and uncertified businesses.

Among the 358 operators surveyed, 62% were certified organic and 38% were uncertified. These percentages describe the survey sample, rather than the national distribution of organic businesses.

The report also examined the potential size of the uncertified sector. Its analysis compared 4,178 certified operations reported in the Australian Organic Market Report 2021 with approximately 6,300 organic records held in KG2’s database at the time.

From this comparison, the report estimated 2,122 uncertified operators. This was an indicative estimate based on the two sources, rather than a verified national population count.

Small businesses were prominent among respondents: 68% described their operation as small, using their own definition of size, while just 8% described it as large.

The research highlighted why certification counts alone provide an incomplete picture of organic activity in Australia.

Certification needed a clearer commercial return

For uncertified producers, the most frequently reported reason for remaining uncertified was cost, mentioned by 30%. Other reasons included:

  • No benefit in sales or profit: 27%.
  • Certification being too restrictive: 26%.
  • Too much paperwork: 22%.

The administrative commitment was also evident among certified producers. Preparing for audits was a main business cost for 47%, followed by certification fees for 40%.

These findings suggest that participation involves a business calculation as well as a willingness to meet standards. Operators need to weigh the expense and work involved against the value certification could bring to their operation.

Only 13% of uncertified producers had previously been certified. Most were therefore describing barriers to entering certification, rather than reasons for leaving it.

Uncertified did not necessarily mean opposed

Overall, 60% of respondents believed a compulsory certification scheme would be useful. Agreement reached 69% among certified operators and 45% among uncertified operators.

Respondents identified reducing false organic claims and requiring businesses making organic claims to be certified as reasons for seeing value in a compulsory scheme.

However, uncertified operators also expressed concerns about individual choice and higher fees.

This distinction matters when interpreting attitudes towards certification. An operator could recognise benefits for the industry while remaining concerned about the consequences for their own business.

The findings point to a need to consider confidence in organic claims alongside the affordability and practical demands of certification.

Uncertified operators were more likely to sell directly to consumers: 71% did so, compared with 50% of certified operators.

Certified businesses were more likely to supply retailers, at 63% compared with 55% of uncertified operators. More than half of certified operators (57%) also supplied organic processors.

These differences provide context for how operators might assess certification’s commercial value. A business selling directly to customers may face different expectations from one supplying retailers or processors. The survey does not establish that certification caused these differences in sales channels.

Operational practices also varied. Among respondents running parallel organic and conventional production, 93% of certified operators reported separating the two, compared with 50% of uncertified operators.

Self-assessed knowledge followed a similar pattern. Some 74% of certified operators rated their knowledge of certification requirements at eight out of ten or higher, compared with 30% of uncertified operators.

For certification bodies, this suggests practical guidance should account for differences in operators’ knowledge, production arrangements and customer relationships.

Growth expectations came with production constraints

At the time of the survey, 60% of operators expected their organic production to increase over the following five years. This measured their expectations in December 2021, rather than growth subsequently achieved.

Weed control and the lack of herbicide options were the most frequently reported production problem, mentioned by 21%. Labour and access to organic raw materials or certified inputs followed, each at 14%.

Meanwhile, 65% of respondents believed organic farming was more expensive.

The combination of optimism and operational pressure identifies useful areas for further investigation. Tracking production intentions alongside weed management, labour requirements and input availability would help explain what enables expansion and what holds it back.

What the findings mean for government and industry

What the findings mean for government and industry

The study offers several practical considerations for organisations working with the Australian organic industry.

For government agencies, research and consultation need to include businesses outside certification records. Their experiences can help inform a fuller assessment of industry needs and potential policy impacts.

For certification bodies, the findings suggest value in addressing administrative demands and explaining the commercial relevance of certification to different business types.

For industry organisations, support may need to reflect differences in scale, production systems and sales channels. Small operators selling directly to consumers may have different priorities from businesses supplying processors or retailers.

Future research could revisit these groups to establish how their circumstances have changed and whether earlier growth expectations were realised.

Understanding the industry through its operators

KG2’s research showed that certification status alone could not explain the decisions organic businesses were making.

Costs, customer relationships, production practices and confidence in organic claims all formed part of the picture. Including certified and uncertified operators made those differences visible.

That remains a useful principle for industry research: understanding a sector requires hearing from businesses across its different operating models, including those less visible in established reporting systems.

About the research

KG2 conducted computer-assisted telephone interviews with 358 organic operators across every state and the Northern Territory in December 2021, drawing the sample from its agriculture database.

Respondents included 325 producers and 127 operators in processing or other non-farming activities. Categories overlapped because some businesses undertook both. The report’s broader processing category included retailing, wholesaling, exporting, storage and transport.

KG2 completed the data collection, analysis and reporting. The department published the final report in February 2022.

Geospatial Data for Agribusiness: How to Identify and Target the Right Regions

Geospatial Data for Agribusiness: How to Identify and Target the Right Regions

by | Sep 25, 2026 | Agtech, Research

For Australian agribusinesses, choosing the right region requires more than broad market estimates. Geospatial data for agribusiness brings farm activity, location, land use, climate, and market information together to show where opportunities are concentrated.

At KG2 Australia, we combine agricultural intelligence, farmer-validated data, and location-based insights to help businesses make more informed regional decisions. If you need to understand a specific market or farming region, connect with us to discuss your data requirements.

What is Geospatial Data for Agribusiness?

Geospatial data connects information to a specific geographic location. In agriculture, this includes farm locations, land use, commodities, production activity, regional characteristics, and other location-based datasets.

When these datasets are analysed using GIS or location intelligence tools, agribusinesses get a clearer view of where customers, production activity, and market opportunities are concentrated.

ABARES provides regional agricultural data covering farm performance, production and industry activity. Its regional datasets show how agricultural intelligence becomes more useful when it is linked to defined geographic areas.

How Does Geospatial Data Help Identify High-Potential Agricultural Regions?

Geospatial data helps agribusinesses compare regions using consistent criteria instead of relying on assumptions or broad state-level averages.

You can assess factors such as:

  • Concentration of farms and agricultural enterprises
  • Commodity and land-use patterns
  • Farm size and enterprise type
  • Regional production activity
  • Customer or market concentration
  • Environmental and seasonal conditions

For example, ABARES publishes regional agricultural statistics and land-use datasets, while KG2’s data capabilities provide additional insight into Australian farming activity and farmer behaviour.

This regional view helps businesses prioritise territories for sales, market research, distribution, customer engagement and expansion.

How Does Location Intelligence Support Agribusiness Market Planning?

Location intelligence turns agricultural data into a practical tool for territory planning. A business might identify regions with high concentrations of a particular crop, compare customer segments across areas, or find where market demand matches existing agricultural activity.

KG2’s AgScan® studies track farmer behaviour across more than 80 farm types and report insights by geographic levels including SA3, state, industry region and agro-ecological zone. This creates opportunities to combine regional location information with farmer behaviour, purchasing decisions and market trends.

For agribusiness marketers, this supports more precise audience segmentation and regional targeting.

How Can Geospatial Data Improve Regional and Site Selection?

Geospatial analysis provides a structured way to compare locations before committing resources.

A business assessing a new territory might look at agricultural activity, farm types, commodity concentration, infrastructure considerations, and market characteristics together. This provides a more detailed regional profile than a single demographic or agricultural dataset can provide.

KG2’s Rural Property Platform also brings together agricultural intelligence, satellite and aerial imagery, climate data, farmer-validated information and predictive analytics. Its filtering tools support analysis by factors such as LGA, farm size, land use and commodity.

The value is practical: decision-makers get a clearer basis for deciding where to focus resources.

Final Thoughts

Geospatial data for agribusiness gives decision-makers a stronger basis for identifying where agricultural activity, customers and market opportunities are concentrated. When combined with farmer behaviour, agricultural data and regional analysis, it supports better territory planning, market segmentation and location decisions.

At KG2 Australia, we bring together agricultural expertise, validated farmer insights and digital data capabilities to help businesses understand Australian agriculture at a more useful geographic level. If you are assessing regions, planning market activity or need more precise agricultural data, get in touch with our team to discuss your requirements.

FAQs

1. What is geospatial data in agriculture?

Geospatial data is agricultural information linked to a geographic location. It includes data such as farm activity, land use, commodities, production, environmental conditions, and regional characteristics.

2. How does geospatial data help agribusinesses target markets?

It shows where relevant farms, commodities, customer groups, or agricultural activities are concentrated. Businesses use these insights to prioritise territories and improve regional market segmentation.

3. How is GIS used in agribusiness?

GIS combines geographic information with business or agricultural datasets. Agribusinesses use it to map activity, compare regions, analyse territories and identify geographic patterns.

4. What agricultural data is useful for regional analysis?

Useful datasets include farm location, commodity, land use, farm size, production activity, demographics, farmer behaviour and environmental information. Combining multiple datasets provides stronger regional context.

5. How can Australian agribusinesses compare farming regions?

Businesses can compare regions using consistent measures such as agricultural activity, farm types, commodity concentration, market characteristics and farmer behaviour. The appropriate measures depend on the business decision being assessed.

6. Why is location intelligence important for agribusiness?

Agricultural markets are geographically distributed and differ significantly by region. Location intelligence helps decision-makers understand these differences and allocate sales, marketing, research and operational resources more effectively.

How Can Liquid Fertilisers Optimise Fertiliser Investment for Australian Grain Farmers?

How Can Liquid Fertilisers Optimise Fertiliser Investment for Australian Grain Farmers?

by | Sep 24, 2026 | Agriculture, Grain Farming

For Australian grain farmers, liquid fertilisers are worth considering as part of a broader nutrient management strategy, especially when application timing, placement, handling and logistics affect fertiliser efficiency. The right choice depends on crop nutrient requirements, soil conditions, seasonal moisture, equipment and the cost per unit of nutrient. At KG2 Australia, we use evidence from Australian farming operations to understand how growers make input decisions. Get in touch with us if you want to discuss agricultural insights and on-farm trends.

What Makes Liquid Fertiliser Relevant to Fertiliser Investment?

The value of a fertiliser is not based on its purchase price alone. Fertiliser profitability depends on how well nutrients support crop production compared with the total investment.

Liquid fertilisers can offer practical benefits in some farming systems. They can be applied using specific application equipment and, depending on the formulation and system, included in existing application programs. These factors can affect labour, handling, application timing and logistics.

GRDC research shows that fertiliser placement, product selection and timing should be considered along with soil characteristics, crop root systems and seasonal moisture availability.

How Should Farmers Assess Liquid Fertiliser Efficiency? 

Start with the nutrient requirement, not the fertiliser product.

Soil testing helps identify available nutrients and other factors that may affect crop nutrition. For grain production, testing and interpretation should be considered alongside crop type, yield target, soil type, previous crop, stored soil moisture, and seasonal conditions.

Then compare liquid and granular options based on the whole system:

  • Cost per unit of nutrient
  • Application and spreading costs
  • Storage and handling requirements
  • Compatibility with farm equipment
  • Application timing and placement
  • Potential nutrient losses
  • Labour and logistics
  • Expected crop response and economic return

This approach helps separate fertiliser price from the overall fertiliser investment.

Can Liquid Fertilisers Improve Nutrient Availability and Application Timing?

Liquid fertiliser does not automatically make nutrients more available to crops. Nutrient availability depends on the nutrient source, soil chemistry, moisture, placement, crop demand and environmental conditions.

Application timing also matters. Australian research into nitrogen management shows that crop response can vary with season, application timing, rate and crop growth stage. Product form alone does not determine the outcome.

For nitrogen fertiliser in particular, matching applications to crop demand is important because rainfall, soil conditions and seasonal yield potential affect both nutrient uptake and loss risk.

Is Liquid Fertiliser Better than Granular Fertiliser for Wheat, Barley or Canola?

Not necessarily. Liquid and granular fertilisers have different agronomic, operational and logistical characteristics.

For wheat, barley, canola and other grain crops, the right fertiliser system depends on the nutrient being supplied, soil fertility, crop demand, application method and farm infrastructure.

A liquid option is worth considering when its handling, application or timing benefits suit the farm system. A granular product may be more practical or economical in other situations.

The key comparison is nutrient efficiency and whole-farm economics, rather than simply choosing between liquid and granular fertiliser.

How Can Farmers Reduce Fertiliser Wastage?

Better fertiliser investment starts with applying the right nutrient at the right rate, time and location.

Soil and plant testing, yield information and paddock variability can help improve nutrient decisions. GRDC notes that both under-fertilisation and over-fertilisation can lead to economic losses, showing the importance of matching inputs with crop demand.

Farmers should also consider storage, mixing compatibility, equipment calibration and weather conditions before application. These operational factors can affect how effectively the planned fertiliser program is delivered.

At KG2 Australia, our AgScan® research tracks fertiliser products, rates, timing, application methods and expenditure across Australian agriculture, along with factors such as soil, rainfall and rotation.

What Should Australian Grain Farmers Consider Before Choosing Liquid Fertiliser?

A sound assessment should cover:

  • Crop and target yield.
  • Soil test results and existing nutrient supply.
  • Nutrient source and formulation.
  • Application equipment and placement.
  • Seasonal moisture and rainfall outlook.
  • Storage, handling and compatibility requirements.
  • Cost per unit of nutrient and application cost.
  • Expected agronomic response and economic return.

These factors vary between regions and seasons, so agronomic advice remains important when developing a fertiliser program.

Final Thoughts

Liquid fertilisers can optimise fertiliser investment when their formulation, nutrient supply, application method, timing, logistics and economics align with farm requirements. They are not inherently more efficient than granular fertilisers. A better approach is to assess the complete fertiliser system against crop demand, soil conditions and expected return.

At KG2 Australia, we use farmer research and agricultural data to understand real-world input decisions across Australian farming. Get in touch with us to learn more about current fertiliser practices and trends.

FAQs

1. Are liquid fertilisers cost-effective for Australian grain farmers?

Liquid fertilisers are cost-effective when their total agronomic and operational benefits outweigh their full cost. Compare nutrient cost, application, handling, storage, logistics and expected crop response rather than product price alone.

2. Do liquid fertilisers improve nutrient use efficiency?

Liquid fertilisers do not automatically improve nutrient use efficiency. Efficiency depends on nutrient source, rate, timing, placement, soil conditions, crop demand and seasonal moisture.

3. Are liquid fertilisers better than granular fertilisers?

Neither form is universally better. The right option depends on nutrient requirements, equipment, soil conditions, application logistics, timing, and total cost per unit of nutrient.

4. Can liquid fertilisers be used for wheat, barley and canola?

Yes, liquid fertilisers are used in grain production, but suitability depends on the nutrient, formulation, crop stage, application method and agronomic requirements. Product labels and professional agronomic advice should guide application decisions.

5. How should farmers compare liquid fertiliser prices?

Compare the cost per unit of the required nutrient, then add application, handling, storage and logistics costs. Assess the expected crop response and economic return before choosing between products.

6. What should farmers check before using a liquid fertiliser?

Check soil test results, crop nutrient requirements, formulation, application equipment, compatibility, storage requirements, timing, weather conditions and total cost. Local agronomic advice is useful when conditions or nutrient requirements are uncertain.