Location: Stored Product Insect and Engineering Research
Project Number: 3020-43000-034-037-A
Project Type: Cooperative Agreement
Start Date: Sep 1, 2025
End Date: Aug 31, 2026
Objective:
Over 1.3 billion tons of postharvest commodities amounting to over $100 billion US dollars are annually lost after harvest with damage caused by stored product insects being a major factor. Economic losses from insect infestations in milled and finished food products can be even greater as product values increase significantly as they move through the supply chain. This project aims to improve automated stored product insect trapping systems and enhance the ability to target areas of concern in a variety of stored product facilities. Stakeholders value cost-effective strategies for mitigating insect infestations and detection is key to save money and time in remediation efforts. Here, we propose methods to develop streamlined methods to tailor treatments by focusing on 1) trap optimization for better population estimation and detection of insects; 2) three-dimensional floor plan mapping of areas of concern within storage and processing facilities; and 3) stakeholder engagement and beta-testing of automated modified traps . Our proposal includes researchers from Kansas and Tennessee, states which have increased interest in protecting stored products ranging from corn, wheat, hops, and more. Protecting these stored products is critical for food protection efforts as we enter a time of increasing pressure on protecting agricultural products, and addresses USDA Strategic Goals 2 and 4, which help to reduce health risk and environmental effects from pests and management strategies.
The objectives of this agreement are to assess trapping systems for automated insect detection by 1) adapting current traps for image collection; 2) designing modeling components for insect detection and for 2D floor plan mapping of unique spaces; and 3) perform economic analyses of traditional versus automated trapping procedures.
Approach:
For the first objective we will modify current trapping designs by first assessing the insects’ ability to get into the traps with and without lids; determine image quality of insects within traps; develop new traps with a variety of surfaces and angles of deployment; compare new and traditional traps for trapping success. Results will include behavioral data on trap captures and modified trapping systems for deployment in semi-field conditions.
For the second objective, digital floor plans will be developed for a variety of stored product environments, highlighting areas of high-risk of infestation, using LiDAR scans; adapt image-based sensing system for the 2D floor plan maps; create classification models for species identification from these trapping systems; beta-test automated robotic platform for pest monitoring. Results will be a new mobile system for driving a robotic system to a trap, using the image acquisition tools, and image-classification models to make classifications of insects present.
For the third objective, the newly designed traps (Obj. 1) and models (Obj. 2) will be tested in semi-field experimental locations where time to check a trap and immediacy of data will be compared to traditional trap checking procedures done by a trained technician. Evaluation of ease of use of the new technology will be assessed as well as cost-benefit to the new system. Educational and extension material including a step-by-step how to will be developed. Results will include direct assessment of the new technology and feasibility measures for warehouse and farm storage managers to track insect pests.