Automated Applications of Acoustics for Stored Product Insect Detection, Monitoring, and Management
United States Department of Agriculture, Agricultural Research Service Center for Medical, Agricultural and Veterinary Entomology (CMAVE), Gainesville, FL 32608, USA
Department of Entomology, Kansas State University, Manhattan, KS 66502, USA
School of Computer Science, Shaanxi Normal University, Xi’an 710119, China
Department of Agrotechnology, University of Thessaly, 41500 Larissa, Greece
Tropical Research and Education Center, Institute of Food and Agricultural Sciences, University of Florida, Homestead, FL 33031, USA
Author to whom correspondence should be addressed.
Academic Editor: George N. Mbata
Received: 19 February 2021 / Revised: 4 March 2021 / Accepted: 5 March 2021 / Published: 19 March 2021
A variety of different acoustic devices has been commercialized for detection of hidden insect infestations in stored products, trees, and soil, including a recently introduced device demonstrated in this report to successfully detect rice weevil immatures and adults in grain. Several of the systems have incorporated digital signal processing and statistical analyses such as neural networks and machine learning to distinguish targeted pests from each other and from background noise, enabling automated monitoring of the abundance and distribution of pest insects in stored products, and potentially reducing the need for chemical control. Current and previously available devices are reviewed in the context of the extensive research in stored product insect acoustic detection since 2011. It is expected that further development of acoustic technology for detection and management of stored product insect pests will continue, facilitating automation and decreasing detection and management costs.