Abstract
Simple SummaryA 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.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 Sitophilus oryzae (Coleoptera: Curculionidae) adult and larval movement and feeding in stored grain. Development of improved methods to identify sounds of targeted pest insects, distinguishing them from each other and from background noise, is an active area of current research. The most powerful of the new methods may be machine learning. The methods have different strengths and weaknesses depending on the types of background noise and the signal characteristic of target insect sounds. It is likely that they will facilitate automation of detection and decrease costs of managing stored product insects in the future.
Highlights
Acoustic technology has a long history of supporting insect pest managers with decision tools and providing contextual information on insect life history, feeding, and movement [1,2,3,4,5,6,7,8,9]
It has been recently examined in Greece [15,16,17,131,250] and has demonstrated noteworthy efficiency in detecting insect presence inside the grain mass, even in the “critical” density of one or two adult beetles per Kg grain, for a plethora of grain pests such as Acanthoscelides obtectus (Say) (Coleoptera: Chrysomelidae) and Callosobruchus maculatus (F.) (Coleoptera: Chrysomelidae) [17,131], Sitophilus oryzae (L.) (Coleoptera: Curculionidae), R. dominica, Tribolium confusum Jacquelin du Val (Coleoptera: Tenebrionidae), Oryzaephilus surinamensis (L.) (Coleoptera: Silvanidae), Trogoderma granarium Everts (Coleoptera: Dermestidae), C. ferrugineus, Lasioderma serricorne (F.) (Coleoptera: Ptinidae), Ephestia kuehniella Zeller (Lepidoptera: Pyralidae), and Plodia interpunctella Hübner (Lepidoptera: Pyralidae) [15,16,131,250]
As discussed in the subanalysis studies suggesting that such research will be of growing importance for stored sections below, there is an expanding body of insect acoustic signal detection and analysis product insect management over the decade
Summary
Acoustic technology has a long history of supporting insect pest managers with decision tools and providing contextual information on insect life history, feeding, and movement [1,2,3,4,5,6,7,8,9]. The use of acoustic technology in insect pest management applications increased rapidly between. 1980 and 2010 [2] and likely will continue, as global trade and incidental transport of invasive species continue to expand [12,13], heightening the needs for improved detection and monitoring of insects in stored product commodities. 137 papers on insect acoustic detection published over more than a century, and this report adds considerably to the total, focusing on the decade since 2010 but including several relevant papers from previous decades that had not been included in the 2011 report (Table 1).
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