D3302: Comparing trapview trap captures to standard insect traps

Insect monitoring is a key component of IPM programs, allowing growers and pest managers to understand the pest populations at the field level in order to enact management decisions if thresholds have been exceeded. Standard insect traps have been developed and optimized to monitor pest population dynamics for most key pests on most fruit and vegetable crops. While conventional traps provide a good estimation of insect pressure during the season, they require daily or weekly visits to collect and identify trapped insects, change the pheromone lure or vapor tape, which requires time and labor to perform these routine visits. Trapview has a camera based solution to this problem which incorporates artificial intelligence software to scan the sticky trapping surface inside the trap once every 24 hours to confirm the presence of the pest target while disregarding non-target insects. Each AI image is then reviewed by a human to confirm pests before the results are posted online for the grower or consultant to use. In this study we compared the similarity of the Trapview AI camera trap catch frequency and accuracy against the standard monitoring traps for Codling moth (Cydia pomonella) in apple, Grape berry moth (Paralobesia viteana) in grape and Corn earworm (Helicoverpa zea) in sweet corn.