Digital Twins in Agriculture — Virtual Farming Workshop

This workshop presents the first findings of a collaborative, industry-translating project demonstrating how Artificial Intelligence (AI) and Machine Learning (ML) can:

• Improve farmers’ decision-making
• Predict and manage disease risks
• Conduct disease management (fungicide spraying) while not compromising environment
• Support technology providers in refining their solutions

The session will introduce our Digital Twin concept and its practical application in real farming environments as well as its entrepreneurial path to commercial implementation. Two real-world agricultural sites have been selected for study:

Serafino Wines, McLaren Vale (SA)

Vineyard digital twin for disease and pest prediction and management

Perennial Pasture Systems, (Vic)

Canola field digital twin for crop health- and performance management

In this project, the University of Adelaide (SA) and Federation University Australia (VIC), in collaboration with technology partners XMPro (QLD), Constellation Technologies (VIC), and Agora High-Tech (SA), are trialling a Predictive / Living Regenerative Digital Twin Platform designed to:

• Reduce disease and pest pressures
• Lever meteorological forecasts to smoothen weather-amplified disease outbreaks
• Recommend concrete types of fungicide, their spraying volume and frequency (re-entry interval, REI)
• Enhance sustainability performance
  (e.g., CO₂ emissions, nutrient pollution)
• Enable real-time monitoring and data-driven responses
• Comply with compliance and circular process design and closed-loop economy

Activity funded by:

The Department of Education through Australia’s Economic Accelerator (AEA) Ignite program