QAAFI Centre for Horticultural Science

DigiHort

Developing Digital Twins, High Performance Computing and AI technologies to advance horticulture

Delivering affordable, adaptable, adoptable and reliable AgTech platforms and solutions to accelerate innovation of farming facilities and planting systems

Enabling real-world impacts with better yield, lower cost and less pollution

Translating university research to create change

Industry-oriented research

Demands, funds, expertise and insights
From industry


Development, validation and demonstration
From industry


Outputs, outcomes and impacts
From industry


Our Technologies

DigiHort Spray

  • Optimise spray equipment selection, configuration, and operation
  • Minimise agrichemical drift
  • Enhance pesticide distribution and deposition
  • Prevent over- and under-application
  • Make robotic sprayers more precise and responsive, while simpler and cheaper

spray.digihort.ai →

DigiHort Light

  • Analyse light distribution across scales: leaf → canopy → row → orchard
  • Optimise orchard design (layout, canopy architecture, density, terrain, latitude)
  • Inform canopy management (trellis training, pruning, machine trimming, etc.)
  • Accelerate agrivoltaic system design and adoption
     

DigiHort Phenotyping

  • Automated on-canopy fruit detection
  • Precise 3D localisation of individual fruits

 

AI-TC Accelerator

Co-developed with QAAFI Tissue Culture Team

  • Optimise tissue culture media
  • Accelerate large-scale crop propagation

Our Features

Fidelity

High-fidelity digital twins

Geographic and geometric details matching reality
 

Complexity

High-complexity simulations

Tens of billions of individual droplets and explicit rays travelling across digital twins

Performance

High-performance computing with commodity hardware

  • 7-minute spray evaluation vs 1 day with conventional simulation or 2 weeks in field
  • 1-minute tracing of 1 billion rays in orchard digital twin
Accuracy

High-accuracy results

  • Validated against field measurements (mechanistic modelling independent from field results)
  • Unique ID for every fruit, every droplet, and every ray
     


Our Online Digital Twinning Platform
 

Visit digihort.ai →

Our Case Studies

01
Optimise spray decision and practices within commercial farms
02
Evaluate crop protection and energy generation with orchard agrivoltaics
03
Innovation of narrow orchard systems
 

  • Dr Liqi Han

    Research Fellow
    Queensland Alliance for Agriculture and Food Innovation
  • Dr Jian Cao

    Postdoctoral Research Fellow
    Queensland Alliance for Agriculture and Food Innovation

Our Contact Information

Dr Liqi Han

liqi.han@uq.edu.au

QAAFI Communications and Marketing Desk

qaaficomms@uq.edu.au

Our Partners