This project developed an understanding of how biotic factors affect the dispersal of rain-splashed asexual spores (conidia) and wind-borne sexual spores (ascospores).

What is the biosecurity problem?

Once an exotic fungal pest has been introduced to a new area (such as via seed or soil) establishment and further spread are influenced largely by the spore dispersal pattern. Long-distance dispersal via wind-borne spores is a common feature of fungal pests, as is short-distance dispersal via rain-splash of spores. Studies that identify the link between environmental factors and spore dispersal can assist in assessing the potential disease risk for agrogeographical zones. Ascochyta species of pulse crops are already within Australia and have rain-splashed asexual spores (conidia) and wind-borne sexual spores (ascospores). These fungi provide an opportunity to study the relationship between the environment and spore dispersal, and to develop risk assessment strategies for exotic pests with similar spore dispersal patterns.

The main outputs of this project were to:

• identify key factors influencing the short-distance (rain-splashed) and long-distance (wind-borne) distribution of spores of exotic foliar pests of annual field crops, using Ascochyta blight as a model.
• determine effect of rainfall, temperature, wind, landscape and host susceptibility on spread of conidia and disease from artificially-inoculated plants placed in crop
• Use controlled conditions to determine the effect of rain and wind on spore dispersal for pests that spread via rain-splash or wind, and
• identify potential disease risk for different agroecological zones.

Who will be the end-users of this research?

This project produced a new PhD graduate trained in Plant Pathology, with specific skills in plant disease epidemiology. The graduate was available for immediate employment within the Biosecurity industry, increasing Australia's capability to respond to disease outbreaks

The main goal of this project was to undertake research that will develop technically sound sample/survey methodologies and systems to enhance the ability to capture a wide range of plant health information in an accurate and cost-effective manner both domestically and internationally.

What is the biosecurity problem?

I aimed to create the necessary tools to significantly reduce the amount of human intervention, as required in present systems. The computational techniques will be required to recognise and identified EPPs in real-time on-board automatic insect traps. The use of imaging technologies based upon hyperspectral and UV ranges to develop a statistical and computational framework for the classification and identification of selected EPPs are challenges.

The main outputs of this project were to:

1. devlop new, better understanding of shape/image descriptors suitable for spectral imagery specially designed for biosecurity surveillance systems
2. create a set of kernel-based, statistical methods that can be used to perform classification of emergency plant pests making use of the descriptors developed in item 1, and
3. develop a framework that will permit the extension of the classification methods developed in item 2 to include domain knowledge. This will involve the development of semi-supervised pattern recognition and interactive computer vision methods based upon statistics that are scalable and capable of real-time analysis.

Who are the end-users of this research?

Automatic and continuous monitoring capabilities of ‘smart traps' have a high potential for commercialisation, both nationally and internationally. Such technology will most likely be adopted by state agencies and plant-based industries involved in early warning networks for emergency plant pests to increase efficiency and reduce cost of monitoring early warning insect traps. Outcomes from this project may also be applicable to a range of biosecurity issues such as semi-automated surveillance systems in quarantine facilities, index databases, building of libraries for future reference, etc.