Optoelectronic sensors for detecting insects entering semiochemical traps.
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In a ever globalising world the threat posed by invasive insect species is on the rise. Semiochemical attractants developed for invasive insects allow for early detection of an incursion of invasive insects through trapping networks. These semiochemical technologies are being developed at a rapid pace for many high risk invasive insects. However, the methods used in trapping programs have remained largely the same since the 1970s. Maintaining these grids requires large labour investments, as traps need to be manually inspected. This limits the number of insect species which can be monitored.
A simple sensor capable of detecting insects caught in traps has the potential to reduce labour costs and allow faster detection of invasive insects. In doing this it would free up resources, allowing for more invasive insect surveillance programs to be put in place. Faster detection also means a greater chance of successfully eradicating an invasive insect population. In this thesis I propose a low power, low cost optoelectronic beam break sensor for detecting insects as they enter semiochemical traps. The sensor is based on a single opamp AC coupled transimpedance amplifier which is sensitive to modulated near infrared light but rejects ambient infrared from the sun. This allows for reliable detection of insects in a range of different lighting conditions. It may also be used to identify the species of sensed insects based on their beam disruption patterns in the future.
The sensors efficacy was tested in the field and in the laboratory with both model species and Gypsy moth. It proved to be durable and capable of reliably detecting insects for a small power budget. The data obtained from this sensor appears to contain biometrics which could be used for species identification in the future. While I do not present a polished product ready for immediate field deployment, it is hoped that the work presented can be used to improve invasive insect detection capabilities in the future.