Towards an Automated Acoustic Detection Algorithm for Wood-Boring Beetle Larvae (Coleoptera: Cerambycidae and Buprestidae)

Sutin, Alexander; Yakubovskiy, Alexander; Salloum, Hady; Flynn, Timothy; Sedunov, Nikolay; Nadel, Hannah

doi:10.1093/jee/toz016

Cited by 22 publications

(21 citation statements)

References 15 publications

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“…Merges the advantage of a color vision system with that of spectroscopic system [142]. Provides both spectral and spatial features for accurate segmentation and identification of region of interest, it can detect internal defects [140] HSI data are voluminous, contain huge redundant data that requires tedious analysis to upgrade to multispectral images by selecting useful wavelengths), its hardware is costly, different chemometric methods are required to extract useful information [140] X-ray imaging Can detect internal defects causing density differences, such as cavities High costs, poor penetration in materials with high water content, and difficulty in effectively differentiating normal and infested tissues with similar densities [143] MRI No harmful ionizing radiation, high-resolution visual information of internal structure, it gives quality 2D and 3D images [144] High costs, large dimensions, and heaviness [86,90] Thermal imaging Easy handling and portability [144] Sensitivity to the environmental condition and relatively high costs to obtain high-resolution images [93] Acoustic Sensitive, efficient, and clear detection capabilities of various insects [145]. Inexpensive, automatic, and continuous monitoring [19] Prone to background noise [19].…”

Section: Hsimentioning

confidence: 99%

Non-Destructive Technologies for Detecting Insect Infestation in Fruits and Vegetables under Postharvest Conditions: A Critical Review

Adedeji

Ekramirad

Rady

et al. 2020

Foods

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In the last two decades, food scientists have attempted to develop new technologies that can improve the detection of insect infestation in fruits and vegetables under postharvest conditions using a multitude of non-destructive technologies. While consumers’ expectations for higher nutritive and sensorial value of fresh produce has increased over time, they have also become more critical on using insecticides or synthetic chemicals to preserve food quality from insects’ attacks or enhance the quality attributes of minimally processed fresh produce. In addition, the increasingly stringent quarantine measures by regulatory agencies for commercial import–export of fresh produce needs more reliable technologies for quickly detecting insect infestation in fruits and vegetables before their commercialization. For these reasons, the food industry investigates alternative and non-destructive means to improve food quality. Several studies have been conducted on the development of rapid, accurate, and reliable insect infestation monitoring systems to replace invasive and subjective methods that are often inefficient. There are still major limitations to the effective in-field, as well as postharvest on-line, monitoring applications. This review presents a general overview of current non-destructive techniques for the detection of insect damage in fruits and vegetables and discusses basic principles and applications. The paper also elaborates on the specific post-harvest fruit infestation detection methods, which include principles, protocols, specific application examples, merits, and limitations. The methods reviewed include those based on spectroscopy, imaging, acoustic sensing, and chemical interactions, with greater emphasis on the noninvasive methods. This review also discusses the current research gaps as well as the future research directions for non-destructive methods’ application in the detection and classification of insect infestation in fruits and vegetables.

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Section: Hsimentioning

confidence: 99%

Non-Destructive Technologies for Detecting Insect Infestation in Fruits and Vegetables under Postharvest Conditions: A Critical Review

Adedeji

Ekramirad

Rady

et al. 2020

Foods

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“…A mildly intrusive and widely applied method for inspection of commodities is based on inserting a piezoelectric probe in the tree trunk to listen for potential internal audio activity due to feeding and locomotion (i.e. passive acoustic detection) [11][12][13][14][15][16][17][18]. The feeding activity is audible [12][13][14][15][16][17] in two of the biological stages of the insect a) when the mature larvae tunnel into the sapwood or heartwood to form a pupal chamber (February-April), and b) after their exoskeleton is fully hardened and the adults dig emergence tunnels through the bark to exit the trunk (late spring to summer).…”

Section: Imentioning

confidence: 99%

“…In the context of this work, audio is based on the vibrations caused by the pests cracking the tree fibres. It is possible that elsewhere, different types of wood and different borers produce sounds with different spectral content but extended literature of the field (see [12][13][14][15][16][17][18][19][20][21][22][23][24] and the references therein) show that acoustic emission cannot be avoided. We then examine the vibrational soundscape of trees in urban spaces and forests and analyse the practical benefit of automatic remote surveillance of trees against borers.…”

Section: Imentioning

confidence: 99%

TreeVibes: Modern tools for Global Monitoring of Trees Against Borers

Rigakis¹,

Potamitis²,

Tatlas³

et al. 2020

Preprint

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Is there a wood-feeding insect inside a tree or wooden structure? We investigate several ways on how deep learning approaches can massively scan recordings of vibrations stemming from probed trees to infer their infestation state with wood-boring insects that feed and move inside wood. The recordings come from remotely controlled devices that sample the internal soundscape of trees on a 24/7 basis and wirelessly transmit brief recordings of the registered vibrations to a cloud server. We discuss the different sources of vibrations that can be picked up from trees in urban environments and how deep learning methods can focus on those originating from borers. Our goal is to match the problem of the accelerated—due to global trade and climate change— establishment of invasive xylophagus insects by increasing the capacity of inspection agencies. We aim at introducing permanent, cost-effective, automatic monitoring of trees based on deep learning techniques, in commodity entry point as well as in wild, urban and cultivated areas in order to effect large-scale, sustainable pest-risk analysis and management of wood boring insects such as those from the Cerambycidae family (longhorn beetles).

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“…There is a wide bibliography [4] on optical [5,6], laser vibrometry [7], piezoelectric sensors, and accelerometers [8][9][10][11], used to detect locomotion and feeding sound of larvae or adult pests inside the tree trunk. A mildly intrusive and widely applied method for inspection of commodities is based on inserting a piezoelectric probe in the tree trunk to listen for potential internal audio activity due to feeding and locomotion (i.e., passive acoustic detection) [12][13][14][15][16][17][18][19]. The feeding activity is audible [13][14][15][16][17][18] in two of the biological stages of the insect a) when the mature larvae tunnel into the sapwood or heartwood to form a pupal chamber (February-April), and b) after their exoskeleton is fully hardened and the adults dig emergence tunnels through the bark to exit the trunk (late spring to summer).…”

Section: Introductionmentioning

confidence: 99%

“…A mildly intrusive and widely applied method for inspection of commodities is based on inserting a piezoelectric probe in the tree trunk to listen for potential internal audio activity due to feeding and locomotion (i.e., passive acoustic detection) [12][13][14][15][16][17][18][19]. The feeding activity is audible [13][14][15][16][17][18] in two of the biological stages of the insect a) when the mature larvae tunnel into the sapwood or heartwood to form a pupal chamber (February-April), and b) after their exoskeleton is fully hardened and the adults dig emergence tunnels through the bark to exit the trunk (late spring to summer). The larva activity has a lower audio imprint than adult activity whereas during the egg and pupation stages in the pupal chamber the pest is inaudible.…”

Section: Introductionmentioning

confidence: 99%

TreeVibes: Modern Tools for Global Monitoring of Trees for Borers

et al. 2021

View full text Add to dashboard Cite

Is there a wood-feeding insect inside a tree or wooden structure? We investigate several ways of how deep learning approaches can massively scan recordings of vibrations stemming from probed trees to infer their infestation state with wood-boring insects that feed and move inside wood. The recordings come from remotely controlled devices that sample the internal soundscape of trees on a 24/7 basis and wirelessly transmit brief recordings of the registered vibrations to a cloud server. We discuss the different sources of vibrations that can be picked up from trees in urban environments and how deep learning methods can focus on those originating from borers. Our goal is to match the problem of the accelerated—due to global trade and climate change— establishment of invasive xylophagus insects by increasing the capacity of inspection agencies. We aim at introducing permanent, cost-effective, automatic monitoring of trees based on deep learning techniques, in commodity entry points as well as in wild, urban and cultivated areas in order to effect large-scale, sustainable pest-risk analysis and management of wood boring insects such as those from the Cerambycidae family (longhorn beetles).

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Towards an Automated Acoustic Detection Algorithm for Wood-Boring Beetle Larvae (Coleoptera: Cerambycidae and Buprestidae)

Cited by 22 publications

References 15 publications

Non-Destructive Technologies for Detecting Insect Infestation in Fruits and Vegetables under Postharvest Conditions: A Critical Review

Non-Destructive Technologies for Detecting Insect Infestation in Fruits and Vegetables under Postharvest Conditions: A Critical Review

TreeVibes: Modern tools for Global Monitoring of Trees Against Borers

TreeVibes: Modern Tools for Global Monitoring of Trees for Borers

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