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Insect Biometrics: Optoacoustic Signal Processing and Its Applications to Remote Monitoring of McPhail Type Traps.

Potamitis I, Rigakis I, Fysarakis K - PLoS ONE (2015)

Bottom Line: Pests can be controlled with ground pesticide sprays, the efficiency of which depends on knowing the time, location and extent of infestations as early as possible.We introduce the term 'insect biometrics' in the context of entomology as a measure of a characteristic of the insect (in our case, the spectrum of its wingbeat) that allows us to identify its species and make devices to help face old enemies with modern means.Our experiments assess the potential of delivering reliable data that can be used to initialize reliably the spraying process at large scales but to also monitor the impact of the spraying process as it eliminates the time-lag between acquiring and delivering insect counts to a central agency.

View Article: PubMed Central - PubMed

Affiliation: Department of Music Technology & Acoustics, Technological Educational Institute of Crete, E. Daskalaki Perivolia, 74100, Rethymno Crete, Greece.

ABSTRACT
Monitoring traps are important components of integrated pest management applied against important fruit fly pests, including Bactrocera oleae (Gmelin) and Ceratitis capitata (Widemann), Diptera of the Tephritidae family, which effect a crop-loss/per year calculated in billions of euros worldwide. Pests can be controlled with ground pesticide sprays, the efficiency of which depends on knowing the time, location and extent of infestations as early as possible. Trap inspection is currently carried out manually, using the McPhail trap, and the mass spraying is decided based on a decision protocol. We introduce the term 'insect biometrics' in the context of entomology as a measure of a characteristic of the insect (in our case, the spectrum of its wingbeat) that allows us to identify its species and make devices to help face old enemies with modern means. We modify a McPhail type trap into becoming electronic by installing an array of photoreceptors coupled to an infrared emitter, guarding the entrance of the trap. The beating wings of insects flying in the trap intercept the light and the light fluctuation is turned to a recording. Custom-made electronics are developed that are placed as an external add-on kit, without altering the internal space of the trap. Counts from the trap are transmitted using a mobile communication network. This trap introduces a new automated remote-monitoring method different to audio and vision-based systems. We evaluate our trap in large number of insects in the laboratory by enclosing the electronic trap in insectary cages. Our experiments assess the potential of delivering reliable data that can be used to initialize reliably the spraying process at large scales but to also monitor the impact of the spraying process as it eliminates the time-lag between acquiring and delivering insect counts to a central agency.

No MeSH data available.


Related in: MedlinePlus

(top) A typical 200 ms B.oleae. wingbeat event recorded as the insect crossed the optical sensor (18°C). (bottom) Magnitude spectral density.The fundamental frequency of B. oleae typically drifts between 170 and 210 Hz.
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pone.0140474.g002: (top) A typical 200 ms B.oleae. wingbeat event recorded as the insect crossed the optical sensor (18°C). (bottom) Magnitude spectral density.The fundamental frequency of B. oleae typically drifts between 170 and 210 Hz.

Mentions: It takes a flying B. oleae 30–50 ms to cross the beam in a direct quick flight but can reach to 300 ms in slower types of flying patterns and even more in rare cases. The light fluctuation is recorded by the sensor as it crosses the light path from emitter to receiver and subsequently analyzed (see Fig 2 for a typical case of an in-flight recording). Fourier transform can reveal how the energy of the recorded signal is distributed on its constituent frequencies. The basic idea can be grasped in Fig 3, exploiting an analogy to the way in which the human ears and brain discriminate among musical instruments [12]. This figure shows two different real recordings of musical instruments playing the same note (A4). Though they sound alike, the human ear can easily discern from which instrument they originate. They sound alike because they play the same note and share the common fundamental frequency of 440 Hz (corresponding to A4). The sound of the instrument is not a pure sine and therefore, does not only demonstrate a single frequency at 440 Hz but also possesses harmonics (frequencies at integer multiples of the fundamental). The identity of the instrument is captured in the relative distribution of energy on the harmonics. Note in Fig 3- (right) how the flute and the violin share the same fundamental but the distribution of energy on the harmonics is quite different. If the flute and violin in Fig 3 where the sounds made from insects’ wingbeat, they would correspond to the -not uncommon- case where two insects beat their wings with exactly the same frequency. Insect species can still be recognized due to the differences on the relative energy levels of the wingbeat harmonics. Even the slightest morphological differences (i.e. size, shape, and mass of the wings) as well as stiffness and kinetic properties of the muscle system controlling flight will be reflected on the wingbeat spectrum.


Insect Biometrics: Optoacoustic Signal Processing and Its Applications to Remote Monitoring of McPhail Type Traps.

Potamitis I, Rigakis I, Fysarakis K - PLoS ONE (2015)

(top) A typical 200 ms B.oleae. wingbeat event recorded as the insect crossed the optical sensor (18°C). (bottom) Magnitude spectral density.The fundamental frequency of B. oleae typically drifts between 170 and 210 Hz.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4636391&req=5

pone.0140474.g002: (top) A typical 200 ms B.oleae. wingbeat event recorded as the insect crossed the optical sensor (18°C). (bottom) Magnitude spectral density.The fundamental frequency of B. oleae typically drifts between 170 and 210 Hz.
Mentions: It takes a flying B. oleae 30–50 ms to cross the beam in a direct quick flight but can reach to 300 ms in slower types of flying patterns and even more in rare cases. The light fluctuation is recorded by the sensor as it crosses the light path from emitter to receiver and subsequently analyzed (see Fig 2 for a typical case of an in-flight recording). Fourier transform can reveal how the energy of the recorded signal is distributed on its constituent frequencies. The basic idea can be grasped in Fig 3, exploiting an analogy to the way in which the human ears and brain discriminate among musical instruments [12]. This figure shows two different real recordings of musical instruments playing the same note (A4). Though they sound alike, the human ear can easily discern from which instrument they originate. They sound alike because they play the same note and share the common fundamental frequency of 440 Hz (corresponding to A4). The sound of the instrument is not a pure sine and therefore, does not only demonstrate a single frequency at 440 Hz but also possesses harmonics (frequencies at integer multiples of the fundamental). The identity of the instrument is captured in the relative distribution of energy on the harmonics. Note in Fig 3- (right) how the flute and the violin share the same fundamental but the distribution of energy on the harmonics is quite different. If the flute and violin in Fig 3 where the sounds made from insects’ wingbeat, they would correspond to the -not uncommon- case where two insects beat their wings with exactly the same frequency. Insect species can still be recognized due to the differences on the relative energy levels of the wingbeat harmonics. Even the slightest morphological differences (i.e. size, shape, and mass of the wings) as well as stiffness and kinetic properties of the muscle system controlling flight will be reflected on the wingbeat spectrum.

Bottom Line: Pests can be controlled with ground pesticide sprays, the efficiency of which depends on knowing the time, location and extent of infestations as early as possible.We introduce the term 'insect biometrics' in the context of entomology as a measure of a characteristic of the insect (in our case, the spectrum of its wingbeat) that allows us to identify its species and make devices to help face old enemies with modern means.Our experiments assess the potential of delivering reliable data that can be used to initialize reliably the spraying process at large scales but to also monitor the impact of the spraying process as it eliminates the time-lag between acquiring and delivering insect counts to a central agency.

View Article: PubMed Central - PubMed

Affiliation: Department of Music Technology & Acoustics, Technological Educational Institute of Crete, E. Daskalaki Perivolia, 74100, Rethymno Crete, Greece.

ABSTRACT
Monitoring traps are important components of integrated pest management applied against important fruit fly pests, including Bactrocera oleae (Gmelin) and Ceratitis capitata (Widemann), Diptera of the Tephritidae family, which effect a crop-loss/per year calculated in billions of euros worldwide. Pests can be controlled with ground pesticide sprays, the efficiency of which depends on knowing the time, location and extent of infestations as early as possible. Trap inspection is currently carried out manually, using the McPhail trap, and the mass spraying is decided based on a decision protocol. We introduce the term 'insect biometrics' in the context of entomology as a measure of a characteristic of the insect (in our case, the spectrum of its wingbeat) that allows us to identify its species and make devices to help face old enemies with modern means. We modify a McPhail type trap into becoming electronic by installing an array of photoreceptors coupled to an infrared emitter, guarding the entrance of the trap. The beating wings of insects flying in the trap intercept the light and the light fluctuation is turned to a recording. Custom-made electronics are developed that are placed as an external add-on kit, without altering the internal space of the trap. Counts from the trap are transmitted using a mobile communication network. This trap introduces a new automated remote-monitoring method different to audio and vision-based systems. We evaluate our trap in large number of insects in the laboratory by enclosing the electronic trap in insectary cages. Our experiments assess the potential of delivering reliable data that can be used to initialize reliably the spraying process at large scales but to also monitor the impact of the spraying process as it eliminates the time-lag between acquiring and delivering insect counts to a central agency.

No MeSH data available.


Related in: MedlinePlus