Pest and disease detection is particularly challenging when managing crops that extend for 100s or 1000s of hectares. More efficient, targeted and accurate monitoring over such vast distances offers enormous benefits in terms of monitoring and early detection of pests. This project is has investigated the application of sUAS to detect and monitor high priority in-field plant biosecurity threats.
By combining modern digital photography with sUASs, agricultural producers and consultants will have the capacity to detect pest insects and diseases before outbreaks occur. The technology is applicable across scales (plant-paddock-region), can monitor across a range of host plants (e.g. wheat, vineyards, orchards) and in diverse environments. Targets pests including sugarcane aphid, yellow stripe rust, and myrtle rust were used to develop a generalized decision matrix to direct biosecurity surveillance programs to better predict the likelihood of pest presence and potential areas for surveillance.
The cost of surveillance over wide areas of both production and natural systems is substantial and is often required to maintain market access (management) or detect new incursions. The future of effective and efficient biosecurity surveillance programs and pest management in general, will require a higher level of automation and technical sophistication and an increased dependence on affordable technologies. Reliable yet effective sampling efforts are imperative to the future of plant biosecurity and food security in general. Through better understanding of this technology and acceptance of its application, this tool will contribute to our ability to survey large areas, and those that are inaccessible, more effectively.