What was it all about?

This project improved Australia’s preparedness for the exotic guava root-knot nematode (Meloidogyne enterolobii), a high-risk pest for potatoes, sweetpotatoes, onions and other vegetables. It confirmed that the pest was not present in Australia before its first detection in 2022, giving industry and biosecurity agencies stronger evidence that the incursion is recent and likely limited in spread. This information is critical for guiding decisions about containment, eradication and long-term management.

The project developed and tested two new diagnostic approaches. The first was an artificial intelligence (AI) system that can accurately identify root-knot nematode species from microscope images, delivering fast and reliable results without the need for complex laboratory testing. The second was a new laboratory protocol to recover genetic material from formalin-preserved samples, helping unlock information stored in historic collections. These methods were applied to samples from Australian collections to check for past misidentifications.

The work addressed a major challenge for growers and industry: uncertainty about whether this damaging nematode had been present in Australia for some time or was a recent arrival. Misidentification with other common root-knot nematodes made this difficult to resolve using existing tools.

The outcomes are expected to support better on-farm decision-making, faster diagnostics and stronger biosecurity responses. Over time, these tools could help growers manage root-knot nematodes more effectively, protect productivity, and support trade by improving confidence in pest status and area freedom.