Project Details:

Title:
Leveraging Real-time Insect Traps and Data Analytics to Improve Corn Earworm Risk Prediction

Parent Project: This is the first year of this project.
Checkoff Organization:North Carolina Soybean Producers Association
Categories:Insects and pests
Organization Project Code:21-122
Project Year:2021
Lead Principal Investigator:Anders Huseth (North Carolina State University)
Co-Principal Investigators:
Keywords:

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Information and Results

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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

Performance Metrics

Project Years