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The challenge

Building further trust in Australian produce

Australia's unique ecosystem allows for a thriving agriculture industry.

Key to international and domestic trade of fresh produce is managing biosecurity risks to prevent the spread of pest, weed or disease.

Australia has built a strong reputation in managing biosecurity risks, which we can further enhance with new digital technologies that provide evidence of pest-free status.

This could open new markets for Australian produce. 

We are developing optical scanning technologies to help protect Australia’s agriculture industry and boost trade related economic prosperity. ©  iStock

Our response

Imaging tech that can be used in packhouses

We have developed an automated, non-destructive solution that can be used in fruit packhouses to provide further assurance that produce is pest free when it leaves the packing house.

Our approach combines imaging technology with AI. It has led to the development of an optical scanner that detects pest damage on the surface of the fruit.

It can be added to existing optical graders used in packhouses for sorting produce, providing an efficient and cost-effective solution.

The results

Tests show high accuracy for identifying pest damage

A prototype has been tested on cherries and blueberries with particular focus on Queensland fruit flies, showing an accuracy rate of greater than 95 per cent.

As it easily integrates with current systems in place, there is potential for this technology to be used across both import and export commodities for a wide range of produce and pests and disease.

The next steps are to work with a commercial partner to undertake trials in packhouses to see how the technology could be used in conjunction with current biosecurity measures for greater assurance.

We are also investigating X-ray technologies for pest detection.

Comparison images of a fruit fly infested cherry with an RGB image and an optically scanned image showing the detection of fruit fly eggs and larvae.  
Comparison images of a fruit fly infested cherry with an RGB image and an optically scanned image showing the detection of fruit fly eggs and larvae.

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