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Saha T, Genoud AP, Williams GM, Russell GJ, Thomas BP. Monitoring Mosquito Abundance: Comparing an Optical Sensor with a Trapping Method. INSECTS 2024; 15:584. [PMID: 39194789 DOI: 10.3390/insects15080584] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/28/2024] [Revised: 07/29/2024] [Accepted: 07/30/2024] [Indexed: 08/29/2024]
Abstract
Optical sensors have shown significant promise in offering additional data to track insect populations. This article presents a comparative study between abundance measurements obtained from a novel near-infrared optical sensor and physical traps. The optical instrument, named an Entomological Bistatic Optical Sensor System, or eBoss, is a non-destructive sensor operating in the near-infrared spectral range and designed to continuously monitor the population of flying insects. The research compares the mosquito aerial density (#/m3) obtained through the eBoss with trap counts from eight physical traps during an eight-month field study. The eBoss recorded over 302,000 insect sightings and assessed the aerial density of all airborne insects as well as male and female mosquitoes specifically with a resolution of one minute. This capability allows for monitoring population trends throughout the season as well as daily activity peaks. The results affirmed the correlation between the two methods. While optical instruments do not match traps in terms of taxonomic accuracy, the eBoss offered greater temporal resolution (one minute versus roughly three days) and statistical significance owing to its much larger sample size. These outcomes further indicate that entomological optical sensors can provide valuable complementary data to more common methods to monitor flying insect populations, such as mosquitoes or pollinators.
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Affiliation(s)
- Topu Saha
- Department of Physics, New Jersey Institute of Technology, University Heights, Newark, NJ 07102, USA
| | - Adrien P Genoud
- Centre national de la recherche scientifique, Institut Lumière Matière, Universite Claude Bernard Lyon 1, UMR5306, F-69622 Villeurbanne, France
| | - Gregory M Williams
- Center for Vector Biology, Rutgers University, New Brunswick, NJ 08901, USA
| | - Gareth J Russell
- Department of Biological Sciences, New Jersey Institute of Technology, University Heights, Newark, NJ 07102, USA
| | - Benjamin P Thomas
- Department of Physics, New Jersey Institute of Technology, University Heights, Newark, NJ 07102, USA
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Saha T, Genoud AP, Park JH, Thomas BP. Temperature Dependency of Insect's Wingbeat Frequencies: An Empirical Approach to Temperature Correction. INSECTS 2024; 15:342. [PMID: 38786898 PMCID: PMC11121811 DOI: 10.3390/insects15050342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Revised: 05/06/2024] [Accepted: 05/09/2024] [Indexed: 05/25/2024]
Abstract
This study examines the relationship between the wingbeat frequency of flying insects and ambient temperature, leveraging data from over 302,000 insect observations obtained using a near-infrared optical sensor during an eight-month field experiment. By measuring the wingbeat frequency as well as wing and body optical cross-sections of each insect in conjunction with the ambient temperature, we identified five clusters of insects and analyzed how their average wingbeat frequencies evolved over temperatures ranging from 10 °C to 38 °C. Our findings reveal a positive correlation between temperature and wingbeat frequency, with a more pronounced increase observed at higher wingbeat frequencies. Frequencies increased on average by 2.02 Hz/°C at 50 Hz, and up to 9.63 Hz/°C at 525 Hz, and a general model is proposed. This model offers a valuable tool for correcting wingbeat frequencies with temperature, enhancing the accuracy of insect clustering by optical and acoustic sensors. While this approach does not account for species-specific responses to temperature changes, our research provides a general insight, based on all species present during the field experiment, into the intricate dynamics of insect flight behavior in relation to environmental factors.
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Affiliation(s)
- Topu Saha
- Department of Physics, New Jersey Institute of Technology, University Heights, Newark, NJ 07102, USA;
| | - Adrien P. Genoud
- Institut Lumière Matière, UMR 5306, Université Claude Bernard Lyon 1, CNRS, F-69100 Villeurbanne, France;
| | - Jung H. Park
- Department of Data Science, New Jersey Institute of Technology, University Heights, Newark, NJ 07102, USA;
| | - Benjamin P. Thomas
- Department of Physics, New Jersey Institute of Technology, University Heights, Newark, NJ 07102, USA;
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Patt JM, Makagon A, Norton B, Marvit M, Rutschman P, Neligeorge M, Salesin J. An optical system to detect, surveil, and kill flying insect vectors of human and crop pathogens. Sci Rep 2024; 14:8174. [PMID: 38589427 PMCID: PMC11002038 DOI: 10.1038/s41598-024-57804-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Accepted: 03/21/2024] [Indexed: 04/10/2024] Open
Abstract
Sustainable and effective means to control flying insect vectors are critically needed, especially with widespread insecticide resistance and global climate change. Understanding and controlling vectors requires accurate information about their movement and activity, which is often lacking. The Photonic Fence (PF) is an optical system that uses machine vision, infrared light, and lasers to identify, track, and interdict vectors in flight. The PF examines an insect's outline, flight speed, and other flight parameters and if these match those of a targeted vector species, then a low-power, retina-safe laser kills it. We report on proof-of-concept tests of a large, field-sized PF (30 mL × 3 mH) conducted with Aedes aegypti, a mosquito that transmits dangerous arboviruses, and Diaphorina citri, a psyllid which transmits the fatal huanglongbing disease of citrus. In tests with the laser engaged, < 1% and 3% of A. aegypti and D. citri, respectfully, were recovered versus a 38% and 19% recovery when the lacer was silenced. The PF tracked, but did not intercept the orchid bee, Euglossa dilemma. The system effectively intercepted flying vectors, but not bees, at a distance of 30 m, heralding the use of photonic energy, rather than chemicals, to control flying vectors.
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Affiliation(s)
- Joseph M Patt
- United States Department of Agriculture, Agricultural Research Service, Fort Pierce, FL, 34945, USA.
| | - Arty Makagon
- Global Health Labs (Formerly Global Good Fund I, LLC), Bellevue, WA, 98007, USA
| | - Bryan Norton
- Global Health Labs (Formerly Global Good Fund I, LLC), Bellevue, WA, 98007, USA
| | - Maclen Marvit
- Global Health Labs (Formerly Global Good Fund I, LLC), Bellevue, WA, 98007, USA
| | - Phillip Rutschman
- Global Health Labs (Formerly Global Good Fund I, LLC), Bellevue, WA, 98007, USA
| | - Matt Neligeorge
- Global Health Labs (Formerly Global Good Fund I, LLC), Bellevue, WA, 98007, USA
| | - Jeremy Salesin
- Global Health Labs (Formerly Global Good Fund I, LLC), Bellevue, WA, 98007, USA
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González-Pérez MI, Faulhaber B, Aranda C, Williams M, Villalonga P, Silva M, Costa Osório H, Encarnaçao J, Talavera S, Busquets N. Field evaluation of an automated mosquito surveillance system which classifies Aedes and Culex mosquitoes by genus and sex. Parasit Vectors 2024; 17:97. [PMID: 38424626 PMCID: PMC10905882 DOI: 10.1186/s13071-024-06177-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 02/05/2024] [Indexed: 03/02/2024] Open
Abstract
BACKGROUND Mosquito-borne diseases are a major concern for public and veterinary health authorities, highlighting the importance of effective vector surveillance and control programs. Traditional surveillance methods are labor-intensive and do not provide high temporal resolution, which may hinder a full assessment of the risk of mosquito-borne pathogen transmission. Emerging technologies for automated remote mosquito monitoring have the potential to address these limitations; however, few studies have tested the performance of such systems in the field. METHODS In the present work, an optical sensor coupled to the entrance of a standard mosquito suction trap was used to record 14,067 mosquito flights of Aedes and Culex genera at four temperature regimes in the laboratory, and the resulting dataset was used to train a machine learning (ML) model. The trap, sensor, and ML model, which form the core of an automated mosquito surveillance system, were tested in the field for two classification purposes: to discriminate Aedes and Culex mosquitoes from other insects that enter the trap and to classify the target mosquitoes by genus and sex. The field performance of the system was assessed using balanced accuracy and regression metrics by comparing the classifications made by the system with those made by the manual inspection of the trap. RESULTS The field system discriminated the target mosquitoes (Aedes and Culex genera) with a balanced accuracy of 95.5% and classified the genus and sex of those mosquitoes with a balanced accuracy of 88.8%. An analysis of the daily and seasonal temporal dynamics of Aedes and Culex mosquito populations was also performed using the time-stamped classifications from the system. CONCLUSIONS This study reports results for automated mosquito genus and sex classification using an optical sensor coupled to a mosquito trap in the field with highly balanced accuracy. The compatibility of the sensor with commercial mosquito traps enables the sensor to be integrated into conventional mosquito surveillance methods to provide accurate automatic monitoring with high temporal resolution of Aedes and Culex mosquitoes, two of the most concerning genera in terms of arbovirus transmission.
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Affiliation(s)
- María I González-Pérez
- IRTA, Programa de Sanitat Animal, Centre de Recerca en Sanitat Animal (CReSA), Campus de la Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
- Unitat mixta d'Investigació IRTA-UAB en Sanitat Animal, Centre de Recerca en Sanitat Animal (CReSA), Campus de La Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
| | | | - Carles Aranda
- IRTA, Programa de Sanitat Animal, Centre de Recerca en Sanitat Animal (CReSA), Campus de la Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
- Unitat mixta d'Investigació IRTA-UAB en Sanitat Animal, Centre de Recerca en Sanitat Animal (CReSA), Campus de La Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
- Servei de Control de Mosquits del Consell Comarcal del Baix Llobregat, El Prat de Llobregat, Spain
| | | | | | - Manuel Silva
- National Institute of Health/Centre for Vectors and Infectious Diseases Research, Águas de Moura, Portugal
| | - Hugo Costa Osório
- National Institute of Health/Centre for Vectors and Infectious Diseases Research, Águas de Moura, Portugal
- Instituto de Saúde Ambiental, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal
| | | | - Sandra Talavera
- IRTA, Programa de Sanitat Animal, Centre de Recerca en Sanitat Animal (CReSA), Campus de la Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
- Unitat mixta d'Investigació IRTA-UAB en Sanitat Animal, Centre de Recerca en Sanitat Animal (CReSA), Campus de La Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
| | - Núria Busquets
- IRTA, Programa de Sanitat Animal, Centre de Recerca en Sanitat Animal (CReSA), Campus de la Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain.
- Unitat mixta d'Investigació IRTA-UAB en Sanitat Animal, Centre de Recerca en Sanitat Animal (CReSA), Campus de La Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain.
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Li M, Runemark A, Hernandez J, Rota J, Bygebjerg R, Brydegaard M. Discrimination of Hover Fly Species and Sexes by Wing Interference Signals. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2304657. [PMID: 37847885 PMCID: PMC10700183 DOI: 10.1002/advs.202304657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 09/08/2023] [Indexed: 10/19/2023]
Abstract
Remote automated surveillance of insect abundance and diversity is poised to revolutionize insect decline studies. The study reveals spectral analysis of thin-film wing interference signals (WISs) can discriminate free-flying insects beyond what can be accomplished by machine vision. Detectable by photonic sensors, WISs are robust indicators enabling species and sex identification. The first quantitative survey of insect wing thickness and modulation through shortwave-infrared hyperspectral imaging of 600 wings from 30 hover fly species is presented. Fringy spectral reflectance of WIS can be explained by four optical parameters, including membrane thickness. Using a Naïve Bayes Classifier with five parameters that can be retrieved remotely, 91% is achieved accuracy in identification of species and sexes. WIS-based surveillance is therefore a potent tool for remote insect identification and surveillance.
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Affiliation(s)
- Meng Li
- Department of PhysicsLund UniversitySölvegatan 14cLund22363Sweden
| | - Anna Runemark
- Department of BiologyLund UniversitySölvegatan 35Lund22362Sweden
| | | | - Jadranka Rota
- Biological Museum, Department of BiologyLund UniversitySölvegatan 37Lund22362Sweden
| | - Rune Bygebjerg
- Biological Museum, Department of BiologyLund UniversitySölvegatan 37Lund22362Sweden
| | - Mikkel Brydegaard
- Department of PhysicsLund UniversitySölvegatan 14cLund22363Sweden
- Department of BiologyLund UniversitySölvegatan 35Lund22362Sweden
- Norsk Elektro OptikkØstensjøveien 34Oslo0667Norway
- FaunaPhotonicsStøberigade 14Copenhagen2450Denmark
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Li Y, Han Z, Nessler R, Yi Z, Hemmer P, Brick R, Sokolov AV, Scully MO. Optical multiband polarimetric modulation sensing for gender and species identification of flying native solitary pollinators. iScience 2023; 26:108265. [PMID: 38026192 PMCID: PMC10654587 DOI: 10.1016/j.isci.2023.108265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Revised: 07/13/2023] [Accepted: 10/17/2023] [Indexed: 12/01/2023] Open
Abstract
Native pollinators are crucial to local ecosystems but are under threat with the introduction of managed pollinators, e.g., honeybees (Apis mellifera). We explored the feasibility of employing the entomological lidar technique in native pollinator abundance studies. This study included individuals of both genders of three common solitary bee species, Osmia californica, Osmia lignaria, and Osmia ribifloris, native to North America. Properties including optical cross-section, degree of linear polarization, and wingbeat power spectra at all three wavelengths have been extracted from the insect signals collected by a compact stand-off sensing system. These properties are then used in the classification analysis. For species with temporal and spatial overlapping, the highest accuracies of our method exceed 96% (O. ribifloris & O. lignaria) and 93% (O. lignaria & O. californica). The benefit of employing the seasonal activity and foraging preference information in enhancing identification accuracy has been emphasized.
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Affiliation(s)
- Yiyun Li
- Institute for Quantum Science and Engineering, Department of Physics and Astronomy, Texas, A&M University, College Station, TX 77843–4242, USA
| | - Zehua Han
- Institute for Quantum Science and Engineering, Department of Physics and Astronomy, Texas, A&M University, College Station, TX 77843–4242, USA
| | - Reed Nessler
- Institute for Quantum Science and Engineering, Department of Physics and Astronomy, Texas, A&M University, College Station, TX 77843–4242, USA
| | - Zhenhuan Yi
- Institute for Quantum Science and Engineering, Department of Physics and Astronomy, Texas, A&M University, College Station, TX 77843–4242, USA
| | - Philip Hemmer
- Institute for Quantum Science and Engineering, Department of Physics and Astronomy, Texas, A&M University, College Station, TX 77843–4242, USA
- Department of Electrical & Computer Engineering, Texas, A&M University, College Station, TX 77843–3127, USA
| | - Robert Brick
- Institute for Quantum Science and Engineering, Department of Physics and Astronomy, Texas, A&M University, College Station, TX 77843–4242, USA
| | - Alexei V. Sokolov
- Institute for Quantum Science and Engineering, Department of Physics and Astronomy, Texas, A&M University, College Station, TX 77843–4242, USA
- Department of Physics, Baylor University, Waco, TX 76798, USA
| | - Marlan O. Scully
- Institute for Quantum Science and Engineering, Department of Physics and Astronomy, Texas, A&M University, College Station, TX 77843–4242, USA
- Department of Physics, Baylor University, Waco, TX 76798, USA
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7
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Maia LJ, de Oliveira CH, Silva AB, Souza PAA, Müller NFD, Cardoso JDC, Ribeiro BM, de Abreu FVS, Campos FS. Arbovirus surveillance in mosquitoes: Historical methods, emerging technologies, and challenges ahead. Exp Biol Med (Maywood) 2023; 248:2072-2082. [PMID: 38183286 PMCID: PMC10800135 DOI: 10.1177/15353702231209415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2024] Open
Abstract
Arboviruses cause millions of infections each year; however, only limited options are available for treatment and pharmacological prevention. Mosquitoes are among the most important vectors for the transmission of several pathogens to humans. Despite advances, the sampling, viral detection, and control methods for these insects remain ineffective. Challenges arise with the increase in mosquito populations due to climate change, insecticide resistance, and human interference affecting natural habitats, which contribute to the increasing difficulty in controlling the spread of arboviruses. Therefore, prioritizing arbovirus surveillance is essential for effective epidemic preparedness. In this review, we offer a concise historical account of the discovery and monitoring of arboviruses in mosquitoes, from mosquito capture to viral detection. We then analyzed the advantages and limitations of these traditional methods. Furthermore, we investigated the potential of emerging technologies to address these limitations, including the implementation of next-generation sequencing, paper-based devices, spectroscopic detectors, and synthetic biosensors. We also provide perspectives on recurring issues and areas of interest such as insect-specific viruses.
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Affiliation(s)
- Luis Janssen Maia
- Instituto de Ciências Biológicas, Departamento de Biologia Celular, Laboratório de Baculovírus, Universidade de Brasília, Brasília 70910-900, Brasil
| | - Cirilo Henrique de Oliveira
- Laboratório de Comportamento de Insetos, Instituto Federal do Norte de Minas Gerais, Salinas 39560-000, Brasil
| | - Arthur Batista Silva
- Laboratório de Bioinformática e Biotecnologia, Universidade Federal do Tocantins, Gurupi 77402-970, Brasil
| | - Pedro Augusto Almeida Souza
- Laboratório de Comportamento de Insetos, Instituto Federal do Norte de Minas Gerais, Salinas 39560-000, Brasil
| | - Nicolas Felipe Drumm Müller
- Instituto de Ciências Básicas da Saúde, Universidade Federal do Rio Grande do Sul, Porto Alegre 90035-003, Brasil
| | - Jader da Cruz Cardoso
- Divisão de Vigilância Ambiental em Saúde, Centro Estadual de Vigilância em Saúde, Secretaria Estadual de Saúde do Rio Grande do Sul, Porto Alegre 90610-000, Brasil
| | - Bergmann Morais Ribeiro
- Instituto de Ciências Biológicas, Departamento de Biologia Celular, Laboratório de Baculovírus, Universidade de Brasília, Brasília 70910-900, Brasil
| | | | - Fabrício Souza Campos
- Laboratório de Bioinformática e Biotecnologia, Universidade Federal do Tocantins, Gurupi 77402-970, Brasil
- Instituto de Ciências Básicas da Saúde, Universidade Federal do Rio Grande do Sul, Porto Alegre 90035-003, Brasil
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Saha T, Genoud AP, Williams GM, Thomas BP. Monitoring the abundance of flying insects and atmospheric conditions during a 9-month campaign using an entomological optical sensor. Sci Rep 2023; 13:15606. [PMID: 37731042 PMCID: PMC10511543 DOI: 10.1038/s41598-023-42884-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 09/15/2023] [Indexed: 09/22/2023] Open
Abstract
Monitoring the dynamics of insect populations is key to assessing the impact of human activities on insect populations. However, traditional methodologies relying on physical traps have inherent limitations in accurately monitoring insect abundance. Here, we present findings from a 9-month campaign conducted in New Jersey, USA, utilizing a near-infrared optical sensor known as eBoss. From April to December 2022, the eBoss derived the aerial density (insect/m3) and biomass density (mg/m3) with a 1-min resolution from a total of 302,093 insect observations. The data collected were analyzed in relation to air temperature, relative humidity, and wind speed. The results revealed that the abundance of flying insects exhibited an initial increase from April to June, reaching a peak of 0.094 insect/m3 and 1.34 mg/m3, followed by a subsequent decline towards the end of the year. Our investigation showed a surge in insect abundance above 12.5 °C, with particularly high levels observed between 19 and 31 °C. The impact of relative humidity and wind speed on insect populations was also explored. Overall, this campaign demonstrated the efficacy of photonic sensors in gathering novel and extensive data for the field of entomology, paving the way for improved understanding and management of insect populations.
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Affiliation(s)
- Topu Saha
- Department of Physics, New Jersey Institute of Technology, Newark, NJ, USA
| | - Adrien P Genoud
- Institute of Light and Matter, Claude Bernard University, Lyon, France
| | | | - Benjamin P Thomas
- Department of Physics, New Jersey Institute of Technology, Newark, NJ, USA.
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Müller L, Li M, Månefjord H, Salvador J, Reistad N, Hernandez J, Kirkeby C, Runemark A, Brydegaard M. Remote Nanoscopy with Infrared Elastic Hyperspectral Lidar. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2207110. [PMID: 36965063 DOI: 10.1002/advs.202207110] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 02/17/2023] [Indexed: 05/27/2023]
Abstract
Monitoring insects of different species to understand the factors affecting their diversity and decline is a major challenge. Laser remote sensing and spectroscopy offer promising novel solutions to this. Coherent scattering from thin wing membranes also known as wing interference patterns (WIPs) have recently been demonstrated to be species specific. The colors of WIPs arise due to unique fringy spectra, which can be retrieved over long distances. To demonstrate this, a new concept of infrared (950-1650 nm) hyperspectral lidar with 64 spectral bands based on a supercontinuum light source using ray-tracing and 3D printing is developed. A lidar with an unprecedented number of spectral channels, high signal-to-noise ratio, and spatio-temporal resolution enabling detection of free-flying insects and their wingbeats. As proof of principle, coherent scatter from a damselfly wing at 87 m distance without averaging (4 ms recording) is retrieved. The fringed signal properties are used to determine an effective wing membrane thickness of 1412 nm with ±4 nm precision matching laboratory recordings of the same wing. Similar signals from free flying insects (2 ms recording) are later recorded. The accuracy and the method's potential are discussed to discriminate species by capturing coherent features from free-flying insects.
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Affiliation(s)
- Lauro Müller
- Department of Physics, Lund University, Sölvegatan 14c, Lund, 22363, Sweden
| | - Meng Li
- Department of Physics, Lund University, Sölvegatan 14c, Lund, 22363, Sweden
| | - Hampus Månefjord
- Department of Physics, Lund University, Sölvegatan 14c, Lund, 22363, Sweden
| | - Jacobo Salvador
- Department of Physics, Lund University, Sölvegatan 14c, Lund, 22363, Sweden
| | - Nina Reistad
- Department of Physics, Lund University, Sölvegatan 14c, Lund, 22363, Sweden
- Centre for Environmental and Climate Science, Lund University, Sölvegatan 37, Lund, SE-223 62, Sweden
| | - Julio Hernandez
- Norsk Elektro Optikk A/S, Østensjøveien 34, Oslo, 0667, Norway
| | - Carsten Kirkeby
- Department of Veterinary and Animal Sciences, Copenhagen University, Frederiksberg, 1870, Denmark
- FaunaPhotonics, Støberigade 14, Copenhagen, 2450, Denmark
| | - Anna Runemark
- Department of Biology, Lund University, Sölvegatan 35, Lund, 22362, Sweden
| | - Mikkel Brydegaard
- Department of Physics, Lund University, Sölvegatan 14c, Lund, 22363, Sweden
- Norsk Elektro Optikk A/S, Østensjøveien 34, Oslo, 0667, Norway
- FaunaPhotonics, Støberigade 14, Copenhagen, 2450, Denmark
- Department of Biology, Lund University, Sölvegatan 35, Lund, 22362, Sweden
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10
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Genoud AP, Saha T, Williams GM, Thomas BP. Insect biomass density: measurement of seasonal and daily variations using an entomological optical sensor. APPLIED PHYSICS. B, LASERS AND OPTICS 2023; 129:26. [PMID: 36685802 PMCID: PMC9845170 DOI: 10.1007/s00340-023-07973-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 01/09/2023] [Indexed: 05/06/2023]
Abstract
Insects are major actors in Earth's ecosystems and their recent decline in abundance and diversity is alarming. The monitoring of insects is paramount to understand the cause of this decline and guide conservation policies. In this contribution, an infrared laser-based system is used to remotely monitor the biomass density of flying insects in the wild. By measuring the optical extinction caused by insects crossing the 36-m long laser beam, the Entomological Bistatic Optical Sensor System used in this study can evaluate the mass of each specimen. At the field location, between July and December 2021, the instrument made a total of 262,870 observations of insects for which the average dry mass was 17.1 mg and the median 3.4 mg. The daily average mass of flying insects per meter cube of air at the field location has been retrieved throughout the season and ranged between near 0 to 1.2 mg/m3. Thanks to its temporal resolution in the minute range, daily variations of biomass density have been observed as well. These measurements show daily activity patterns changing with the season, as large increases in biomass density were evident around sunset and sunrise during Summer but not during Fall.
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Affiliation(s)
- Adrien P. Genoud
- Department of Physics, New Jersey Institute of Technology, Newark, NJ USA
| | - Topu Saha
- Department of Physics, New Jersey Institute of Technology, Newark, NJ USA
| | | | - Benjamin P. Thomas
- Department of Physics, New Jersey Institute of Technology, Newark, NJ USA
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11
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González-Pérez MI, Faulhaber B, Williams M, Brosa J, Aranda C, Pujol N, Verdún M, Villalonga P, Encarnação J, Busquets N, Talavera S. A novel optical sensor system for the automatic classification of mosquitoes by genus and sex with high levels of accuracy. Parasit Vectors 2022; 15:190. [PMID: 35668486 PMCID: PMC9169302 DOI: 10.1186/s13071-022-05324-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 05/13/2022] [Indexed: 11/10/2022] Open
Abstract
Background Every year, more than 700,000 people die from vector-borne diseases, mainly transmitted by mosquitoes. Vector surveillance plays a major role in the control of these diseases and requires accurate and rapid taxonomical identification. New approaches to mosquito surveillance include the use of acoustic and optical sensors in combination with machine learning techniques to provide an automatic classification of mosquitoes based on their flight characteristics, including wingbeat frequency. The development and application of these methods could enable the remote monitoring of mosquito populations in the field, which could lead to significant improvements in vector surveillance. Methods A novel optical sensor prototype coupled to a commercial mosquito trap was tested in laboratory conditions for the automatic classification of mosquitoes by genus and sex. Recordings of > 4300 laboratory-reared mosquitoes of Aedes and Culex genera were made using the sensor. The chosen genera include mosquito species that have a major impact on public health in many parts of the world. Five features were extracted from each recording to form balanced datasets and used for the training and evaluation of five different machine learning algorithms to achieve the best model for mosquito classification. Results The best accuracy results achieved using machine learning were: 94.2% for genus classification, 99.4% for sex classification of Aedes, and 100% for sex classification of Culex. The best algorithms and features were deep neural network with spectrogram for genus classification and gradient boosting with Mel Frequency Cepstrum Coefficients among others for sex classification of either genus. Conclusions To our knowledge, this is the first time that a sensor coupled to a standard mosquito suction trap has provided automatic classification of mosquito genus and sex with high accuracy using a large number of unique samples with class balance. This system represents an improvement of the state of the art in mosquito surveillance and encourages future use of the sensor for remote, real-time characterization of mosquito populations. Graphical abstract ![]()
Supplementary Information The online version contains supplementary material available at 10.1186/s13071-022-05324-5.
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Affiliation(s)
- María I González-Pérez
- IRTA, Centre de Recerca en Sanitat Animal (CReSA, IRTA-UAB), Campus de la Universitat Autònoma de Barcelona, Bellaterra, Cerdanyola del Vallès, Spain
| | | | | | - Josep Brosa
- IRTA, Centre de Recerca en Sanitat Animal (CReSA, IRTA-UAB), Campus de la Universitat Autònoma de Barcelona, Bellaterra, Cerdanyola del Vallès, Spain
| | - Carles Aranda
- IRTA, Centre de Recerca en Sanitat Animal (CReSA, IRTA-UAB), Campus de la Universitat Autònoma de Barcelona, Bellaterra, Cerdanyola del Vallès, Spain.,Servei de Control de Mosquits del Consell Comarcal del Baix Llobregat, Barcelona, Spain
| | - Nuria Pujol
- IRTA, Centre de Recerca en Sanitat Animal (CReSA, IRTA-UAB), Campus de la Universitat Autònoma de Barcelona, Bellaterra, Cerdanyola del Vallès, Spain
| | - Marta Verdún
- IRTA, Centre de Recerca en Sanitat Animal (CReSA, IRTA-UAB), Campus de la Universitat Autònoma de Barcelona, Bellaterra, Cerdanyola del Vallès, Spain
| | | | | | - Núria Busquets
- IRTA, Centre de Recerca en Sanitat Animal (CReSA, IRTA-UAB), Campus de la Universitat Autònoma de Barcelona, Bellaterra, Cerdanyola del Vallès, Spain
| | - Sandra Talavera
- IRTA, Centre de Recerca en Sanitat Animal (CReSA, IRTA-UAB), Campus de la Universitat Autònoma de Barcelona, Bellaterra, Cerdanyola del Vallès, Spain.
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Genoud AP, Williams GM, Thomas BP. Continuous monitoring of aerial density and circadian rhythms of flying insects in a semi-urban environment. PLoS One 2021; 16:e0260167. [PMID: 34793570 PMCID: PMC8601533 DOI: 10.1371/journal.pone.0260167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Accepted: 11/03/2021] [Indexed: 11/21/2022] Open
Abstract
Although small in size, insects are a quintessential part of terrestrial ecosystems due to their large number and diversity. While captured insects can be thoroughly studied in laboratory conditions, their population dynamics and abundance in the wild remain largely unknown due to the lack of accurate methodologies to count them. Here, we present the results of a field experiment where the activity of insects has been monitored continuously over 3 months using an entomological stand-off optical sensor (ESOS). Because its near-infrared laser is imperceptible to insects, the instrument provides an unbiased and absolute measurement of the aerial density (flying insect/m3) with a temporal resolution down to the minute. Multiple clusters of insects are differentiated based on their wingbeat frequency and ratios between wing and body optical cross-sections. The collected data allowed for the study of the circadian rhythm and daily activities as well as the aerial density dynamic over the whole campaign for each cluster individually. These measurements have been compared with traps for validation of this new methodology. We believe that this new type of data can unlock many of the current limitations in the collection of entomological data, especially when studying the population dynamics of insects with large impacts on our society, such as pollinators or vectors of infectious diseases.
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Affiliation(s)
- Adrien P. Genoud
- Department of Physics, New Jersey Institute of Technology, Newark, New Jersey, United States of America
| | - Gregory M. Williams
- Center for Vector Biology, Rutgers University, New Brunswick, New Jersey, United States of America
| | - Benjamin P. Thomas
- Department of Physics, New Jersey Institute of Technology, Newark, New Jersey, United States of America
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Li M, Jansson S, Runemark A, Peterson J, Kirkeby CT, Jönsson AM, Brydegaard M. Bark beetles as lidar targets and prospects of photonic surveillance. JOURNAL OF BIOPHOTONICS 2021; 14:e202000420. [PMID: 33249777 DOI: 10.1002/jbio.202000420] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Revised: 11/20/2020] [Accepted: 11/26/2020] [Indexed: 06/12/2023]
Abstract
Forestry is raising concern about the outbreaks of European spruce bark beetle, Ips typographus, causing extensive damage to the spruce forest and timber values. Precise monitoring of these beetles is a necessary step towards preventing outbreaks. Current commercial monitoring methods are catch-based and lack in both temporal and spatial resolution. In this work, light scattering from beetles is characterized, and the feasibility of entomological lidar as a tool for long-term monitoring of bark beetles is explored. Laboratory optical properties, wing thickness, and wingbeat frequency of bark beetles are reported, and these parameters can infer target identity in lidar data. Lidar results from a Swedish forest with controlled bark beetle release event are presented. The capability of lidar to simultaneously monitor both insects and a pheromone plume mixed with chemical smoke governing the dispersal of many insects is demonstrated. In conclusion, entomological lidar is a promising tool for monitoring bark beetles.
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Affiliation(s)
- Meng Li
- Department of Physics, Lund University, Lund, Sweden
| | - Samuel Jansson
- Department of Physics, Lund University, Lund, Sweden
- Department of Biology, Lund University, Lund, Sweden
| | - Anna Runemark
- Department of Biology, Lund University, Lund, Sweden
| | | | | | - Anna Maria Jönsson
- Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
| | - Mikkel Brydegaard
- Department of Physics, Lund University, Lund, Sweden
- Department of Biology, Lund University, Lund, Sweden
- Norsk Elektro Optikk AS, Prost Stabels vei 22, Skedsmokorset, Norway
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14
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Jansson S, Malmqvist E, Mlacha Y, Ignell R, Okumu F, Killeen G, Kirkeby C, Brydegaard M. Real-time dispersal of malaria vectors in rural Africa monitored with lidar. PLoS One 2021; 16:e0247803. [PMID: 33662005 PMCID: PMC7932069 DOI: 10.1371/journal.pone.0247803] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Accepted: 02/12/2021] [Indexed: 11/18/2022] Open
Abstract
Lack of tools for detailed, real-time observation of mosquito behavior with high spatio-temporal resolution limits progress towards improved malaria vector control. We deployed a high-resolution entomological lidar to monitor a half-kilometer static transect positioned over rice fields outside a Tanzanian village. A quarter of a million in situ insect observations were classified, and several insect taxa were identified based on their modulation signatures. We observed distinct range distributions of male and female mosquitoes in relation to the village periphery, and spatio-temporal behavioral features, such as swarming. Furthermore, we observed that the spatial distributions of males and females change independently of each other during the day, and were able to estimate the daily dispersal of mosquitoes towards and away from the village. The findings of this study demonstrate how lidar-based monitoring could dramatically improve our understanding of malaria vector ecology and control options.
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Affiliation(s)
- Samuel Jansson
- Lund Laser Centre, Department of Physics, Lund University, Lund, Sweden
- Center for Animal Movement Research, Department of Biology, Lund University, Lund, Sweden
- * E-mail:
| | - Elin Malmqvist
- Lund Laser Centre, Department of Physics, Lund University, Lund, Sweden
- Center for Animal Movement Research, Department of Biology, Lund University, Lund, Sweden
| | - Yeromin Mlacha
- Environmental Health and Ecological Sciences Department, Ifakara Health Institute, Ifakara, Tanzania
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Rickard Ignell
- Disease Vector Group, Department of Plant Protection Biology, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | - Fredros Okumu
- Environmental Health and Ecological Sciences Department, Ifakara Health Institute, Ifakara, Tanzania
- School of Public Health, University of Witwatersrand, Johannesburg, South Africa
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, United Kingdom
| | - Gerry Killeen
- Environmental Health and Ecological Sciences Department, Ifakara Health Institute, Ifakara, Tanzania
- Department of Vector Biology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
| | - Carsten Kirkeby
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg, Denmark
- FaunaPhotonics APS, Copenhagen N, Denmark
| | - Mikkel Brydegaard
- Lund Laser Centre, Department of Physics, Lund University, Lund, Sweden
- Center for Animal Movement Research, Department of Biology, Lund University, Lund, Sweden
- FaunaPhotonics APS, Copenhagen N, Denmark
- Norsk Elektro Optikk AS, Skedsmokorset, Norway
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Genoud AP, Torsiello J, Belson M, Thomas BP. Entomological photonic sensors: Estimating insect population density, its uncertainty and temporal resolution from transit data. ECOL INFORM 2021. [DOI: 10.1016/j.ecoinf.2020.101186] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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16
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A comparison of supervised machine learning algorithms for mosquito identification from backscattered optical signals. ECOL INFORM 2020. [DOI: 10.1016/j.ecoinf.2020.101090] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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Brydegaard M, Jansson S, Malmqvist E, Mlacha YP, Gebru A, Okumu F, Killeen GF, Kirkeby C. Lidar reveals activity anomaly of malaria vectors during pan-African eclipse. SCIENCE ADVANCES 2020; 6:eaay5487. [PMID: 32426490 PMCID: PMC7220366 DOI: 10.1126/sciadv.aay5487] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Accepted: 03/03/2020] [Indexed: 05/22/2023]
Abstract
Yearly, a quarter billion people are infected and a half a million killed by the mosquito-borne disease malaria. Lack of real-time observational tools for continuously assessing the unperturbed mosquito flight activity in situ limits progress toward improved vector control. We deployed a high-resolution entomological lidar to monitor a half-kilometer static transect adjacent to a Tanzanian village. We evaluated one-third million insect observations during five nights, four days, and one annular solar eclipse. We demonstrate in situ lidar classification of several insect families and their sexes based on their modulation signatures. We were able to compare the fine-scale spatiotemporal activity patterns of malaria vectors during ordinary days and an eclipse to disentangle phototactic activity patterns from the circadian mechanism. We observed an increased insect activity during the eclipse attributable to mosquitoes. These unprecedented findings demonstrate how lidar-based monitoring of distinct mosquito activities could advance our understanding of vector ecology.
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Affiliation(s)
- Mikkel Brydegaard
- Norsk Elektro Optikk AS, Prost Stabels vei 22, N-2019 Skedsmokorset, Norway
- Lund Laser Centre, Department of Physics, Lund University, Sölvegatan 14, SE-22362 Lund, Sweden
- Center for Animal Movement Research, Department of Biology, Lund University, Sölvegatan 35, SE-22362 Lund, Sweden
- FaunaPhotonics APS, Ole Maaløes Vej 3, DK-2200 Copenhagen N, Denmark
- Corresponding author. (M.B.); (C.K.)
| | - Samuel Jansson
- Lund Laser Centre, Department of Physics, Lund University, Sölvegatan 14, SE-22362 Lund, Sweden
- Center for Animal Movement Research, Department of Biology, Lund University, Sölvegatan 35, SE-22362 Lund, Sweden
| | - Elin Malmqvist
- Lund Laser Centre, Department of Physics, Lund University, Sölvegatan 14, SE-22362 Lund, Sweden
- Center for Animal Movement Research, Department of Biology, Lund University, Sölvegatan 35, SE-22362 Lund, Sweden
| | - Yeromin P. Mlacha
- Environmental Health and Ecological Sciences Department, Ifakara Health Institute, P.O. Box 53, Off Mlabani Street, Ifakara, Tanzania
- Swiss Tropical and Public Health Institute, Socinstrasse 57, 4051 Basel, Switzerland
- University of Basel, Petersplatz 1, 4003 Basel, Switzerland
| | - Alem Gebru
- Lund Laser Centre, Department of Physics, Lund University, Sölvegatan 14, SE-22362 Lund, Sweden
- Center for Animal Movement Research, Department of Biology, Lund University, Sölvegatan 35, SE-22362 Lund, Sweden
- FaunaPhotonics APS, Ole Maaløes Vej 3, DK-2200 Copenhagen N, Denmark
| | - Fredros Okumu
- Environmental Health and Ecological Sciences Department, Ifakara Health Institute, P.O. Box 53, Off Mlabani Street, Ifakara, Tanzania
- School of Public Health, University of Witwatersrand, 9 York Rd, 2193 Johannesburg, South Africa
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Graham Kerr Building, Glasgow G12 8QQ, UK
| | - Gerry F. Killeen
- Environmental Health and Ecological Sciences Department, Ifakara Health Institute, P.O. Box 53, Off Mlabani Street, Ifakara, Tanzania
- Department of Vector Biology, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool L35QA, UK
- School of Biological, Earth & Environmental Sciences and Environmental Research Institute, University College Cork, Cork, Republic of Ireland
| | - Carsten Kirkeby
- FaunaPhotonics APS, Ole Maaløes Vej 3, DK-2200 Copenhagen N, Denmark
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Grønnegårdsvej 8, 1870 Frederiksberg, Denmark
- Corresponding author. (M.B.); (C.K.)
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Balla E, Flórián N, Gergócs V, Gránicz L, Tóth F, Németh T, Dombos M. An Opto-electronic Sensor-ring to Detect Arthropods of Significantly Different Body Sizes. SENSORS 2020; 20:s20040982. [PMID: 32059444 PMCID: PMC7070424 DOI: 10.3390/s20040982] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 02/03/2020] [Accepted: 02/07/2020] [Indexed: 01/28/2023]
Abstract
Arthropods, including pollinators and pests, have high positive and negative impacts on human well-being and the economy, and there is an increasing need to monitor their activity and population growth. The monitoring of arthropod species is a time-consuming and financially demanding process. Automatic detection can be a solution to this problem. Here, we describe the setup and operation mechanism of an infrared opto-electronic sensor-ring, which can be used for both small and large arthropods. The sensor-ring consists of 16 infrared (IR) photodiodes along a semicircle in front of an infrared LED. Using 3D printing, we constructed two types of sensor-ring: one with a wider sensing field for detection of large arthropods (flying, crawling, surface-living) in the size range of 2-35 mm; and another one with a narrower sensing field for soil microarthropods in the size range of 0.1-2 mm. We examined the detection accuracy and reliability of the two types of sensor-ring in the laboratory by using particles, and dead and living arthropods at two different sensitivity levels. For the wider sensor-ring, the 95% detectability level was reached with grain particles of 0.9 mm size. This result allowed us to detect all of the macroarthropods that were applied in the tests and that might be encountered in pest management. In the case of living microarthropods with different colors and shapes, when we used the narrower sensor-ring, we achieved the 95% detectability level at 1.1 mm, 0.9 mm, and 0.5 mm in the cases of F. candida, H. nitidus, and H. aculeifer, respectively. The unique potential of arthropod-detecting sensors lies in their real-time measurement system; the data are automatically forwarded to the server, and the end-user receives pest abundance data daily or even immediately. This technological innovation will allow us to make pest management more effective.
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Affiliation(s)
- Esztella Balla
- Department of Fluid Mechanics, Faculty of Mechanical Engineering, Budapest University of Technology and Economics, Bertalan Lajos utca 4-6, H-1111 Budapest, Hungary;
| | - Norbert Flórián
- Centre for Agricultural Research, Institute for Soil Sciences and Agricultural Chemistry, Herman Ottó út 15, H-1022 Budapest, Hungary; (N.F.); (V.G.); (L.G.); (F.T.); (T.N.)
| | - Veronika Gergócs
- Centre for Agricultural Research, Institute for Soil Sciences and Agricultural Chemistry, Herman Ottó út 15, H-1022 Budapest, Hungary; (N.F.); (V.G.); (L.G.); (F.T.); (T.N.)
| | - Laura Gránicz
- Centre for Agricultural Research, Institute for Soil Sciences and Agricultural Chemistry, Herman Ottó út 15, H-1022 Budapest, Hungary; (N.F.); (V.G.); (L.G.); (F.T.); (T.N.)
| | - Franciska Tóth
- Centre for Agricultural Research, Institute for Soil Sciences and Agricultural Chemistry, Herman Ottó út 15, H-1022 Budapest, Hungary; (N.F.); (V.G.); (L.G.); (F.T.); (T.N.)
| | - Tímea Németh
- Centre for Agricultural Research, Institute for Soil Sciences and Agricultural Chemistry, Herman Ottó út 15, H-1022 Budapest, Hungary; (N.F.); (V.G.); (L.G.); (F.T.); (T.N.)
| | - Miklós Dombos
- Centre for Agricultural Research, Institute for Soil Sciences and Agricultural Chemistry, Herman Ottó út 15, H-1022 Budapest, Hungary; (N.F.); (V.G.); (L.G.); (F.T.); (T.N.)
- Correspondence:
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