Cotton growers spend thousands of dollars annually monitoring insect pests and beneficials. The information generated from monitoring is used to make pest control decisions. However, insect monitoring is costly, information and labour intensive, and time dependent. Technology is making automated pest monitoring feasible. Automated wireless pest monitoring has the potential to deliver innovative solutions for pest management by reducing pest monitoring costs and labour requirements, and increasing the accuracy of information, in turn leading to targeted insecticide application and sound decision making. CSIRO holds a PCT patent application (PCT AU/AU2011/001396) on a novel insect monitoring device. This wireless device enables capture of real-time, geo-referenced insect images of broad species type, which is communicated to end users as the basis for pest control decisions, and bio-security alerts.

The objective of this project is to determine the feasibility of using the CSIRO Automated Insect Monitoring (AIM) trap for cotton pest management and bio-security monitoring. The project will: firstly fit the AIM device to different insect traps suitable for cotton systems (eg. interception, lure-based), and compare the accuracy of automated image collection to insect specimen collection; secondly compare the data captured using the AIM trap with the current best-practice pest monitoring using beat-sheet sampling, and relate the information to thresholds used for pest control decision making; thirdly provide estimates of price points suitable for adoption of the AIM trap by the cotton industry; and fourthly assess the AIM trap for potential to monitor novel insect threats to Australian cotton.

Although many research facilities around the globe are developing methodologies to automate insect pest and beneficial monitoring, the CSIRO patent applications is specific for image capture. Automated pest monitoring has the potential to revolutionize crop protection because cost-efficient and accurate information capture can lead to better targeting of insecticide application, and less reliance on already short supply of labour for crop scouting. Similarly, the AIM may also capture images of Emergency Plant Pests (EPPs), which in turn may be automated through image algorithms that are linked to bio-security alerts. Such alerts would allow for a rapid response, and reduced harm to the industry. Depending on the outcome of this proposed project, the AIM trap has the potential for commercialization, and global market application.