Curtin 4 Agribusiness Profitability (C4AP)

Supporting farm businesses to make more profit from their data

Curtin for Agribusiness Profitability (C4AP) is an initiative within CCDM delivering next generation agribusiness and spatial data analytics research to underpin future farm profitability and sustainability.

In this initiative, researchers work with farm businesses, agronomists and technology companies to support decision making on farm and deliver digital tools that drive profitability and sustainability.

What we do:

C4AP is bringing together expertise from

Farming systems
Spatial science
GIS
Data analytics
Software development
Agribusiness

to visualise and analyse farm data, experiment and predict yield and profitability.

Key features of the research include

Visualise and Analyse Understand spatial variability of crop production and economic returns (profitability) within paddock and across the farm enterprise (data pipelines). Examine multi-season patterns of yield and productivity within a paddock to identify opportunities for change and trial location.

Experiment Design a trial, visualise in-season performance (i.e. NDVI), visualise and analyse harvest yield responses. C4AP are working with AAGI to develop experimental design and statistical analysis for on farm experimentation.

Predict Understanding return on investment (gross margin) within paddock, predictions return on investment when scaling management change from paddock to whole-farm and considering risk in current and future climate scenarios for grain growers.

Our Projects

Agri-Analytics Hub

Since the beginning of farming, growers have been experimenting with different treatments and management strategies, but few have taken it to an advanced scientific level where comprehensive analysis has shown which treatment was best. Increasing demand for a scientifically rigorous decision support tool to help farmers design and analyse strip trials has led to the Agri Analytics Hub, a new collaborative research project with a main aim to help farmers analyse variability in crop performance and profitability at an in-paddock scale.

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On-Farm Water Demand

To build resilience in a changing climate, the On-Farm Water Demand (OFWD) project is designed to address the gap in data on water demand in food production in the Warren-Donnelly catchment in south-west WA. The project has enabled horticulture producers to improve their management of water through data analytics, ensuring more sustainable and profitable food production.

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On-Farm Experimentation

Grower driven experimentation and development of a new tool that accounts for spatial variability across paddocks to generate value through data driven decisions. The OFE Platform, developed by NGIS, uses new spatial analytics methods that help farmers translate outcomes from experiments on small plots across the paddock to maximise return on investment for fertiliser. This project ended 2022.

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Digital Edge: Next generation agribusiness analytics for the Eastern Wheatbelt

Digital Edge aimed to enhance climate resilience in the eastern wheatbelt of WA by helping farmers and agronomists use farm data to improve profitability and sustainability at paddock, farm, and farm enterprise scale. The Yield Profitability Research Dashboard was developed as a research tool for co-designing agribusiness analytics and placement of on-farm experiments. By visualizing paddock statistics, variability (yield/gross margins), and weather observations, it is used to facilitate conversations around risk and return on investment of input (ie. fertilizer) placement. An industry roundtable on data interoperability was conducted in collaboration with SPAA, GGA, DPIRD and CCDM outlining challenges and opportunities beyond machine to machine issues. This project ended 2023.

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Our Resources

On Farm Experimentation Grower Case Studies

The CCDM have developed an analysis tool that accounts for the natural variation in a paddock, which can give the growers confidence to run a paddock scale trial knowing the results of the trial are because of the treatments rather than the natural variation that occurs across a landscape. This booklet contains the experience of three growers Mick Caughey, Ty Kirby and James Heggaton who each had a nutrition issue they were looking to help solve using the analysis tool developed by the project team. It also includes the experience of Luke Dawson, who at the time was an advisor from CSBP Fertilisers, who assisted Mick and Ty in their on farm research.

Download the Case Study

Data Driven Grain Profitability through "On-Farm Experimentation"

This project was designed to develop and deploy new methods of data analytics for large scale farmer implemented trials (On-Farm Experiments) that account for spatial variability across paddocks. It has generated value by contributing to the improvement of farmers’ decisions by improving the accessibility and utility of their own data from trials conducted on their own farm. It has been achieved via three focussed areas of activity: research capacity building, method development using data analytics (demonstration of application) and high-throughput analysis capability (platform development).

Download the Final Report

Our People

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The Centre for Crop and Disease Management (CCDM) is developing a model to describe organisational resilience, and how it determines the viability of Australian farming businesses.

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Podcast

How researchers are developing sclerotinia stem rot resistant canola Jun 13,2025

Article

Triple fungicide resistance detected in Yorke Peninsula barley May 19,2025

Video

Plant physiological responses to fungal diseases | CCDM Research May 02,2025

Tools

Pesticide Resistance Integrated Mapping (PRIM) tool Mar 25,2025