Optical identification of bumblebee species: Effect of morphology on wingbeat frequency

Roy, Jeroen van; Baerdemaeker, Josse De; Saeys, Wouter; Ketelaere, Bart De

doi:10.1016/j.compag.2014.09.014

Cited by 20 publications

(22 citation statements)

References 27 publications

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“…Then, we computed the RMS error between the predicted beat speed and ground truth for 50 flying bumblebee video sequences, estimating an error of AE13:6326 flaps/s. To compare this with related work, we notice that van Roy et al [31] provide ranges of uncertainty. Although they use their system with Bombus terrestris and Bombus ignitus, the respective uncertainties in their measurements are AE11:215 and AE15:062 flaps/s.…”

Section: Resultsmentioning

confidence: 99%

“…In their experiments they tethered bumblebees to a rigid needle. More recently, van Roy et al [31] introduced the use of a large area, 100 mm 2 , photovoltaic cell. They applied their method to classify between bumblebees Boombus terrestris (N ¼ 17) and Bombus ignitus (N ¼ 25).…”

Section: Related Workmentioning

confidence: 99%

“…Indeed, Fry et al [9] found, after analyzing the magnitude of the torque and body motion of Drosophila during rapid turns, that inertia, and not friction, dominates the flight dynamics of insects. In addition, wingbeat count could demonstrate to be an effective way to distinguish between different species [31].…”

Section: Introductionmentioning

confidence: 99%

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Frequency analysis of a bumblebee (Bombus impatiens) wingbeat

Santoyo

Azarcoya

Valencia

et al. 2015

Pattern Anal Applic

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The wingbeat of an insect relates directly to energy consumption, is a strong indicator of its rate of metabolism and physical structure, and inversely relates to the length of its wing and to the mass of its body. It is also a principal component in understanding the aerodynamic properties of its flight. In this paper, we introduce a method based on the use of high-speed cameras and computer vision techniques to analyze a bumblebee (Bombus impatiens) wingbeat. We start capturing images with a virtual stereo system when a bumblebee crosses two intersecting laser beams. Then, we detect moving objects using background subtraction. Next, via Fourier analysis of the observed optical flow contraction/expansion, and marginalization of prior knowledge, we estimate the wingbeat frequency. Finally, the information from the two virtual cameras is fused using a robust state estimation. Our system is well prepared to handle occlusions; it works with untethered insects; and it does not require the synchronization of a multi-camera system.

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Section: Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Frequency analysis of a bumblebee (Bombus impatiens) wingbeat

Santoyo

Azarcoya

Valencia

et al. 2015

Pattern Anal Applic

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“…We project that our robust sensors pave the way for many innovative applications not yet in the market, such as the following: a) Electronic beehives [33] that would count the number of incoming and outgoing bees, guard against invasive species and even assess the health of the entering bee, as the health of an insect has an impact on its flying patterns. b) Mosquito traps that will transmit counts per species to alarm for species that are possible carriers of serious diseases and to provide input to statistical vector models that predict the spread of mosquito-borne diseases based on counts of traps at dispersed locations.…”

Section: Discussionmentioning

confidence: 99%

Novel Noise-Robust Optoacoustic Sensors to Identify Insects Through Wingbeats

Potamitis

Rigakis

2015

IEEE Sensors J.

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For certain countries, the production of olive oil and fruits is a significant percentage of the total gross income. Fruit flies affect a yearly crop loss calculated in billions of dollars worldwide. At the top of the hazard scale, certain mosquitoes and flies transmit harmful organisms that cause serious illnesses and even death to humans, pets, and livestock. In this paper, we develop a novel, noise-robust optoacoustic sensors to record insects' wingbeats. Our experiments with various insects of economic and social importance demonstrate that the sensors deliver high SNR recordings of the wing-flap. This paper emphasizes the development of the sensors and successfully analyzes the wingbeats of many insects of economic importance. Accurate analysis of insects' wing-flaps will allow the embedding of the sensors in common traps. The goal is to achieve species classification and remote monitoring of crops, which is currently carried out manually, and to develop reliable decision making regarding the initiation of large-scale spraying.Index Terms-Optoelectronic sensors, precision agriculture, electronic insect traps.

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“…The signal to noise ratio of the backscattered light sensor was at 30-40 dB and often reached 20-30 harmonics. Multispectral signatures look richer than the ones provided by simple one-band sensors but their advantage on classification improvement needs to be clarified and quantified with large-scale experiments (see References [19][20][21] for related work).…”

Section: Discussionmentioning

confidence: 99%

A Multispectral Backscattered Light Recorder of Insects’ Wingbeats

et al. 2019

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Most reported optical recorders of the wingbeat of insects are based on the so-called extinction light, which is the variation of light in the receiver due to the cast shadow of the insect’s wings and main body. In this type of recording devices, the emitter uses light and is placed opposite to the receiver, which is usually a single (or multiple) photodiode. In this work, we present a different kind of wingbeat sensor and its associated recorder that aims to extract a deeper representational signal of the wingbeat event and color characterization of the main body of the insect, namely: a) we record the backscattered light that is richer in harmonics than the extinction light, b) we use three different spectral bands, i.e., a multispectral approach that aims to grasp the melanization and microstructural and color features of the wing and body of the insects, and c) we average at the receiver’s level the backscattered signal from many LEDs that illuminate the wingbeating insect from multiple orientations and thus offer a smoother and more complete signal than one based on a single snapshot. We present all the necessary details to reproduce the device and we analyze many insects of interest like the bee Apis mellifera, the wasp Polistes gallicus, and some insects whose wingbeating characteristics are pending in the current literature, like Drosophila suzukii and Zaprionus, another member of the drosophilidae family.

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Optical identification of bumblebee species: Effect of morphology on wingbeat frequency

Cited by 20 publications

References 27 publications

Frequency analysis of a bumblebee (Bombus impatiens) wingbeat

Frequency analysis of a bumblebee (Bombus impatiens) wingbeat

Novel Noise-Robust Optoacoustic Sensors to Identify Insects Through Wingbeats

A Multispectral Backscattered Light Recorder of Insects’ Wingbeats

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