2021
Leveraging Real-time Insect Traps and Data Analytics to Improve Corn Earworm Risk Prediction
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Contributor/Checkoff:
North Carolina Soybean Producers Association
Category:
Sustainable Production
Keywords:
Biotic stressCrop protectionField management Pest
Parent Project:
This is the first year of this project.
Lead Principal Investigator:
Anders Huseth, North Carolina State University
Co-Principal Investigators:
Project Code:
21-122
Contributing Organization (Checkoff):
North Carolina Soybean Producers Association
$18,500
Institution Funded:
North Carolina State University
$18,500
Brief Project Summary:

Corn earworm has been the target of black light and pheromone trapping networks across North Carolina for decades. This network generates information shared with soybean growers. Although the information provides an indication of adult corn earworm activity, the time lag between moth counting and online data availability limits growers’ ability to time scouting, determine economic thresholds and apply insecticides. Automation of earworm-specific trapping networks addresses this need with seamless data integration into web and phone app interfaces. This project seeks to develop an infrared sensor specifically designed to retrofit Hartstack pheromone traps into a real-time automated sensor targeting corn earworm and measure daily corn earworm activity.

Key Benefactors:
farmers, agronomists, extension agents

Information And Results
Project Deliverables

Final Project Results

The United Soybean Research Retention policy will display final reports with the project once completed but working files will be purged after three years. And financial information after seven years. All pertinent information is in the final report or if you want more information, please contact the project lead at your state soybean organization or principal investigator listed on the project.