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Vibro-Acoustic Signatures of Various Insects in Stored Products
Daniel Kadyrov1, Alexander Sutin1, Nikolay Sedunov1
1Department of Civil, Environmental & Ocean Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, USA.
Sensors (Basel, Switzerland)
|October 26, 2024
Summary
Early detection of stored product insects is vital. The Acoustic Stored Product Insect Detection System (A-SPIDS) uses vibroacoustic signatures to identify pests like the mealworm beetle, aiding supply chain security.
Area of Science:
- Agricultural Science
- Food Science
- Acoustics
Background:
- Stored products are vulnerable to insect infestations, posing risks to food security and supply chains.
- Early detection of pests is critical to prevent widespread contamination and the introduction of invasive species.
- Existing detection methods may lack the sensitivity or efficiency required for real-time monitoring.
Purpose of the Study:
- To develop and evaluate an acoustic detection system for identifying insects in stored products.
- To characterize the vibroacoustic signatures of common stored product insects.
- To establish metrics for reliable insect detection using signal processing techniques.
Main Methods:
- Development of the Acoustic Stored Product Insect Detection System (A-SPIDS) with piezoelectric sensors and microphones.
- Recording vibroacoustic signatures of insects (e.g., *Tenebrio molitor*, *Tribolium confusum*) in various food materials.
- Implementation of a normalization method using ambient noise and calculation of Normalized Signal Pulse Amplitude (NSPA) and Normalized Spectral Energy Level (NSEL).
Main Results:
- The A-SPIDS system successfully recorded distinct vibroacoustic signatures of tested insects.
- NSPA and NSEL metrics were developed to quantify insect signal strength relative to noise.
- High NSPA values (up to 70 dB for *T. molitor* in corn flakes) indicated effective detection potential.
Conclusions:
- The A-SPIDS system and derived metrics (NSPA, NSEL) represent a promising approach for early insect detection in stored products.
- The developed method provides a foundation for creating reliable algorithms for automated pest identification.
- Acoustic monitoring offers a non-invasive and sensitive method for safeguarding stored food supplies.
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