Better Trap Design, Identification Automation, and Spatial Monitoring for Better Stored Product Insect Pest Control

Goals / Objectives
The objective is to reduce insect-related postharvest losses by combining automated image identification tools and 3D mapping of indoor spaces to more accurately detect and treat insect populations. Specifically this aims to develop digital tools to monitor (i.e., detect, identify, count) insects and map stored product environments to improve efficiency and efficacy of IPM interventions with timely assistance. This objective is based on the hypothesis that low-cost imaging sensors, large-scale image data, and deep learning algorithms can be integrated to monitor insect species and estimate their population.

Project Methods
The approach is based on three goals. Goal 1) Optimize available traps for processing and storage facilities to better record insect populations within the environment. Goal 2) Develop location-specific and targeted spatial mapping using traditional and automated trapping using 3D modeling for a real-time detection system. Goal 3) Knowledge transfer through tutorials, trap prototypes, and demonstrations of new trapping and mapping tools. Tasks include (1) modifying currently available trapping and monitoring systems based on updated behavioral patterns for stored product insect pests. 2) Evaluate automated, image versions of new and modified traps versus traditional sticky or pitfall traps. 3) Design automated sensing system for 3D design integration. 4) Assay trap prototypes in semi-field, 3D mapped areas to determine spatial variation. 5) Model areas of infestation associated with spatial variation and structural changes in storage and processing facilities. 6) Beta test systems for modeling and targeted pest treatments.