Monitoring insect pest populations is a cornerstone of Integrated Pest Management (IPM) systems.  By monitoring pest populations, farmers can learn when pest populations become active in time to use preventive controls as well as gauge the levels to determine if the risk warrants control.  In some systems, this is done by sampling plants to determine infestation levels, in other cropping systems, species-specific pheromone-baited traps are used to monitor for adult moth activity prior to egg laying.  Producers would set these traps throughout their farm, then check them on a weekly basis, record numbers of pests captured, and run insect development models to determine when and if control is needed. While these practices can be very helpful to reduce unnecessary insecticide applications while minimizing insect losses, they take time. As a challenge for many of our farms is finding labor, insect trapping is a practice that is under utilized on many farms and replaced with routine insecticide applications.

To address this, automated insect traps have been developed in the past few years that use artificial intelligence (AI) to identify the insect captured and inform producers and pest activity in their crops.  Most of traps use cameras to photograph insects captured on a sticky card then use AI to determine if the captured insects are the pest of interest or not. Depending on the manufacturer of the trap, the grower would receive an email or check a website to get information on pest activity.  This greatly reduces the time and labor need to monitor pest populations.

in 2024, we worked with a small start-up company in California (FarmSense) that has developed an insect trap for monitoring that uses insect wing beat frequencies and profile of the pest as it flies through a light curtain to identify pests.   Traps were installed in a commercial orchard in Scott County where the producer experienced significant losses to both codling moth and Oriental fruit moth in 2023. The county extension agent (Sharon Flynt) is involved with this project. While these traps had been 'trained' for codling moth on the west coast, they had not been trained or evaluated for Oriental fruit moth.  This year we evaluated them at this commercial orchard and compared them to traditional traps that must be inspected weekly.  While we found that due to the trap design, the traditional traps did capture more pests and were more sensitive, the AI traps did capture and record the pests of concern and may be a lower maintenance alternative for monitoring pests and increasing IPM adoption. The AI traps are about the same price and the cost of the other season-long manual traps but require much less time and labor, they only need to be serviced every 8 weeks rather than weekly.