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Mankin R, Hagstrum D, Guo M, et al. Automated Applications of Acoustics for Stored Product Insect Detection, Monitoring, and Management. Insects. 2021;12(3)doi: 10.3390/insects12030259.
Mankin, R., Hagstrum, D., Guo, M., Eliopoulos, P., & Njoroge, A. (2021). Automated Applications of Acoustics for Stored Product Insect Detection, Monitoring, and Management. Insects, 12(3), . https://doi.org/10.3390/insects12030259
Mankin, Richard, et al. "Automated Applications of Acoustics for Stored Product Insect Detection, Monitoring, and Management." Insects vol. 12,3 (2021). doi: https://doi.org/10.3390/insects12030259
Mankin R, Hagstrum D, Guo M, Eliopoulos P, Njoroge A. Automated Applications of Acoustics for Stored Product Insect Detection, Monitoring, and Management. Insects. 2021 Mar 19;12(3). doi: 10.3390/insects12030259. PMID: 33808747; PMCID: PMC8003406.
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Insects. 2021 Mar 19;12(3). doi: 10.3390/insects12030259.

Automated Applications of Acoustics for Stored Product Insect Detection, Monitoring, and Management.

Insects

Richard Mankin, David Hagstrum, Min Guo, Panagiotis Eliopoulos, Anastasia Njoroge

Affiliations

  1. United States Department of Agriculture, Agricultural Research Service Center for Medical, Agricultural and Veterinary Entomology (CMAVE), Gainesville, FL 32608, USA.
  2. Department of Entomology, Kansas State University, Manhattan, KS 66502, USA.
  3. School of Computer Science, Shaanxi Normal University, Xi'an 710119, China.
  4. Department of Agrotechnology, University of Thessaly, 41500 Larissa, Greece.
  5. Tropical Research and Education Center, Institute of Food and Agricultural Sciences, University of Florida, Homestead, FL 33031, USA.

PMID: 33808747 PMCID: PMC8003406 DOI: 10.3390/insects12030259

Abstract

Acoustic technology provides information difficult to obtain about stored insect behavior, physiology, abundance, and distribution. For example, acoustic detection of immature insects feeding hidden within grain is helpful for accurate monitoring because they can be more abundant than adults and be present in samples without adults. Modern engineering and acoustics have been incorporated into decision support systems for stored product insect management, but with somewhat limited use due to device costs and the skills needed to interpret the data collected. However, inexpensive modern tools may facilitate further incorporation of acoustic technology into the mainstream of pest management and precision agriculture. One such system was tested herein to describe

Keywords: Sitophilus oryzae; Tribolium castaneum; abundance; machine learning; neural networks; population density

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