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 Beneficiaries:
#agronomists, #extension agents, #farmers
Unique Keywords:
#corn earworm, #insect, #insect control, #insect management, #insects and pests
Information And Results
Project Summary

Corn earworm (Helicoverpa zea Boddie) has been the target of black light and pheromone trapping networks across North Carolina for decades. Analysis of this historical data has shown that high numbers of corn earworm are positively related to the abundance of soybean in the surrounding landscape (Dorman and Huseth in prep). However, we do not know how to leverage this new analysis into accurate risk predictions for soybean growers. In 2019, the NCSPA funded the development of a real-time pheromone trap targeting corn earworm. Following a period of development and small scale testing, we deployed 20 traps in soybean fields across 5 NC counties. First, we tested the trap durability and identified several improvements that will be needed to move this trap toward commercialization (power usage,
additional weatherizing). Second, we documented a remarkable amount of corn earworm abundance variation in space and time. Here, we propose to refine our trap design and develop predictive data analytics using the near real-time data. Results of this work will provide the foundation for grower accessible corn earworm risk prediction tools.

Project Objectives

1. To deploy an infrared sensor pheromone traps into a real-time automated sensor targeting corn earworm in soybean agroecosystems.

2. To develop data management infrastructure to facilitate data integration into mobile friendly applications.

Project Deliverables

Progress Of Work

Final Project Results

Benefit To Soybean Farmers

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.