A New Approach for Detecting Sublethal Effects of Neonicotinoids on Bumblebees Using Optical Sensor Technology

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Standard

A New Approach for Detecting Sublethal Effects of Neonicotinoids on Bumblebees Using Optical Sensor Technology. / Chatzaki, Vasileia; Montoro, Marta; El-Rashid, Rámi; Jensen, Annette Bruun; Lecocq, Antoine.

I: Insects, Bind 14, Nr. 8, 713, 2023.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Chatzaki, V, Montoro, M, El-Rashid, R, Jensen, AB & Lecocq, A 2023, 'A New Approach for Detecting Sublethal Effects of Neonicotinoids on Bumblebees Using Optical Sensor Technology', Insects, bind 14, nr. 8, 713. https://doi.org/10.3390/insects14080713

APA

Chatzaki, V., Montoro, M., El-Rashid, R., Jensen, A. B., & Lecocq, A. (2023). A New Approach for Detecting Sublethal Effects of Neonicotinoids on Bumblebees Using Optical Sensor Technology. Insects, 14(8), [713]. https://doi.org/10.3390/insects14080713

Vancouver

Chatzaki V, Montoro M, El-Rashid R, Jensen AB, Lecocq A. A New Approach for Detecting Sublethal Effects of Neonicotinoids on Bumblebees Using Optical Sensor Technology. Insects. 2023;14(8). 713. https://doi.org/10.3390/insects14080713

Author

Chatzaki, Vasileia ; Montoro, Marta ; El-Rashid, Rámi ; Jensen, Annette Bruun ; Lecocq, Antoine. / A New Approach for Detecting Sublethal Effects of Neonicotinoids on Bumblebees Using Optical Sensor Technology. I: Insects. 2023 ; Bind 14, Nr. 8.

Bibtex

@article{b6befa158d1e4bd0b4dae89e035ba0e9,
title = "A New Approach for Detecting Sublethal Effects of Neonicotinoids on Bumblebees Using Optical Sensor Technology",
abstract = "Among insects, bees are important pollinators, providing many vital ecosystem services. The recent pollinator decline is threatening both their diversity and abundance. One of the main drivers of this decline is the extensive use of pesticides. Neonicotinoids, one of the most popular groups of pesticides, can be toxic to bees. In fact, numerous studies have found that neonicotinoids can cause sublethal effects, which can impair the biology, physiology, and colony survival of the bees. Yet, there are still knowledge gaps, and more research is needed to better understand the interaction between neonicotinoids and bees, especially in the field. A new optical sensor, which can automatically identify flying insects using machine learning, has been created to continuously monitor insect activity in the field. This study investigated the potential use of this sensor as a tool for monitoring the sublethal effects of pesticides on bumblebees. Bombus terrestris workers were orally exposed to field-realistic doses of imidacloprid. Two types of exposures were tested: acute and chronic. The flight activity of pesticide-exposed and non-exposed bumblebees was recorded, and the events of the insect flights recorded by the sensor were used in two ways: to extract the values of the wingbeat frequency and to train machine learning models. The results showed that the trained model was able to recognize differences between the events created by pesticide-exposed bumblebees and the control bumblebees. This study demonstrates the possibility of the optical sensor for use as a tool to monitor bees that have been exposed to sublethal doses of pesticides. The optical sensor can provide data that could be helpful in managing and, ideally, mitigating the decline of pollinators from one of their most major threats, pesticides.",
keywords = "acute exposure, bumblebees, chronic exposure, convolutional neural networks, infrared sensor, insect monitoring, pesticide",
author = "Vasileia Chatzaki and Marta Montoro and R{\'a}mi El-Rashid and Jensen, {Annette Bruun} and Antoine Lecocq",
note = "Publisher Copyright: {\textcopyright} 2023 by the authors.",
year = "2023",
doi = "10.3390/insects14080713",
language = "English",
volume = "14",
journal = "Insects",
issn = "2075-4450",
publisher = "M D P I AG",
number = "8",

}

RIS

TY - JOUR

T1 - A New Approach for Detecting Sublethal Effects of Neonicotinoids on Bumblebees Using Optical Sensor Technology

AU - Chatzaki, Vasileia

AU - Montoro, Marta

AU - El-Rashid, Rámi

AU - Jensen, Annette Bruun

AU - Lecocq, Antoine

N1 - Publisher Copyright: © 2023 by the authors.

PY - 2023

Y1 - 2023

N2 - Among insects, bees are important pollinators, providing many vital ecosystem services. The recent pollinator decline is threatening both their diversity and abundance. One of the main drivers of this decline is the extensive use of pesticides. Neonicotinoids, one of the most popular groups of pesticides, can be toxic to bees. In fact, numerous studies have found that neonicotinoids can cause sublethal effects, which can impair the biology, physiology, and colony survival of the bees. Yet, there are still knowledge gaps, and more research is needed to better understand the interaction between neonicotinoids and bees, especially in the field. A new optical sensor, which can automatically identify flying insects using machine learning, has been created to continuously monitor insect activity in the field. This study investigated the potential use of this sensor as a tool for monitoring the sublethal effects of pesticides on bumblebees. Bombus terrestris workers were orally exposed to field-realistic doses of imidacloprid. Two types of exposures were tested: acute and chronic. The flight activity of pesticide-exposed and non-exposed bumblebees was recorded, and the events of the insect flights recorded by the sensor were used in two ways: to extract the values of the wingbeat frequency and to train machine learning models. The results showed that the trained model was able to recognize differences between the events created by pesticide-exposed bumblebees and the control bumblebees. This study demonstrates the possibility of the optical sensor for use as a tool to monitor bees that have been exposed to sublethal doses of pesticides. The optical sensor can provide data that could be helpful in managing and, ideally, mitigating the decline of pollinators from one of their most major threats, pesticides.

AB - Among insects, bees are important pollinators, providing many vital ecosystem services. The recent pollinator decline is threatening both their diversity and abundance. One of the main drivers of this decline is the extensive use of pesticides. Neonicotinoids, one of the most popular groups of pesticides, can be toxic to bees. In fact, numerous studies have found that neonicotinoids can cause sublethal effects, which can impair the biology, physiology, and colony survival of the bees. Yet, there are still knowledge gaps, and more research is needed to better understand the interaction between neonicotinoids and bees, especially in the field. A new optical sensor, which can automatically identify flying insects using machine learning, has been created to continuously monitor insect activity in the field. This study investigated the potential use of this sensor as a tool for monitoring the sublethal effects of pesticides on bumblebees. Bombus terrestris workers were orally exposed to field-realistic doses of imidacloprid. Two types of exposures were tested: acute and chronic. The flight activity of pesticide-exposed and non-exposed bumblebees was recorded, and the events of the insect flights recorded by the sensor were used in two ways: to extract the values of the wingbeat frequency and to train machine learning models. The results showed that the trained model was able to recognize differences between the events created by pesticide-exposed bumblebees and the control bumblebees. This study demonstrates the possibility of the optical sensor for use as a tool to monitor bees that have been exposed to sublethal doses of pesticides. The optical sensor can provide data that could be helpful in managing and, ideally, mitigating the decline of pollinators from one of their most major threats, pesticides.

KW - acute exposure

KW - bumblebees

KW - chronic exposure

KW - convolutional neural networks

KW - infrared sensor

KW - insect monitoring

KW - pesticide

U2 - 10.3390/insects14080713

DO - 10.3390/insects14080713

M3 - Journal article

C2 - 37623423

AN - SCOPUS:85169065611

VL - 14

JO - Insects

JF - Insects

SN - 2075-4450

IS - 8

M1 - 713

ER -

ID: 366508162