Automated pheromone trap network for Bt resistance early warning in genetically engineered crops
A scalable, low-cost automated pheromone trap network that delivers real-time lepidopteran moth monitoring to support Bt resistance early warning for genetically engineered crop stewardship. Combines power-efficient hardware with cloud-based data pipelines to expand spatial coverage and temporal continuity of pest surveillance, reducing reliance on costly bioassays and manual scouting.
Overview
This solution addresses two critical challenges in Bt resistance management: existing moth monitoring networks are not designed to detect emerging resistance signals, and bioassay or genetic susceptibility testing is expensive and time-consuming. The offering is an inexpensive automated pheromone trap network that connects low-power field instrumentation with novel data analysis pipelines to expand the spatial extent and temporal continuity of lepidopteran pest monitoring. By linking real-time moth capture data to Bt crop infestation and damage records, the network can serve as an early warning system for emerging Bt resistance, supporting stewardship of genetically engineered cotton and corn.
Technical specifications
Key features:
- Automated pheromone traps equipped with infrared (IR) sensors for moth detection and counting
- Power-efficient hardware design enabling extended field deployment in remote agricultural areas
- Cellular connectivity for transmitting trap data to a cloud computing service in real time
- Cloud-based data visualization and sharing tools for stakeholders, extension agents, and crop managers
- Post-processing algorithms to validate IR sensor readings against manual counts and assess accuracy
- Analytical methods to visualize moth abundance across the sampling region and investigate environmental predictors of captures
- Scalable network architecture demonstrated across five North Carolina counties covering 7,000 square kilometers
How it works:
Traps are deployed across agricultural landscapes where pheromone lures attract target moth species such as cotton bollworm. The IR sensor counts captured moths, and the device transmits counts via cellular signal to a cloud platform. Real-time dashboards allow stakeholders to monitor moth abundance, compare trends across locations, and correlate capture data with Bt crop infestation and damage observations to flag potential resistance emergence.
Technology readiness level
The technology is at an advanced prototype stage. In 2020, a network of 20 automated pheromone traps was deployed across five North Carolina counties, and IR sensor counts are being validated against manual counts along with analysis of moth abundance variability and environmental predictors. The next phase will improve power efficiency, enable real-time cloud data transmission, and scale the network to correlate cotton bollworm abundance with Bt crop damage. The system is positioned to serve as a generalizable, inexpensive model for area-wide lepidopteran pest monitoring networks supporting Bt resistance stewardship programs.
About North Carolina State University
North Carolina State University is a large, comprehensive public land‑grant research university in Raleigh. Its on‑campus research and technology park co‑locates corporate R&D groups, government partners, and faculty labs, enabling shared facilities, prototyping, and agile contracting. Located in North Carolina’s Research Triangle, partners tap a dense regional ecosystem while engaging through a statewide extension network and a mature co‑op program that deliver field deployment and workforce pipelines. Multiple pilot and demonstration facilities support scale‑up and validation toward pre‑commercial readiness. Research is supported by competitive funding from major federal agencies, including NSF, USDA, DOE, and DOD, and a dedicated technology transfer office with clear IP pathways helps accelerate commercialization.
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