Surveying disease vectors is currently excessively laborious for continuous and widespread monitoring. Wing beat modulation spectroscopy gives opportunity for species and sex recognition in electronic traps or mosquito target classification in lidar. We used a polarimetric dual-wavelength-band laboratory system to record kHz modulated backscattered light from insects. The system operates in the near and short-wave infrared at 808 nm and 1550 nm and retrieves both co- and depolarized light. Here we give clues on the harmonic content and covariance of four mosquito species and fruit flies. Further, we interpret the interdependence of harmonic strengths when insects transit the probe volume with random heading direction and provide correlation matrices for coherent and incoherent light. Using the obtained parameters, we demonstrate that species that are difficult to distinguish with microscope can be classified with high accuracy. The results are valuable for understanding wingbeat harmonics in relation to heading and valuable for optimal sensor design for disease vector surveillance.
A kHz optical remote sensing system is implemented to determine insect melanization features. This is done by measuring the backscatter signal in the visible and near-infrared (VIS-NIR) and short-wave infrared (SWIR) in situ. It is shown that backscatter cross section in the SWIR is insensitive to melanization and absolute melanization can be derived from the ratio of backscatter cross section of different bands (SWIR/VIS-NIR). We have shown that reflectance from insect is stronger in the SWIR as compared to NIR and VIS. This reveals that melanization plays a big role to determine backscatter cross section. One can use this feature as a tool to improve insect species and age classification. To support the findings, we illustrated melanization feature using three different insects [dead, dried specimens of snow white moth (Spilosoma genus), fox moth (Macrothylacia), and leather beetle (Odontotaenius genus)]. It is shown that reflectance from the leather beetle in the VIS and NIR is more affected by melanization as compared with snow white moth.
kHz optical remote sensing system is implemented to determine melanization and backscatter cross-section in the near infrared (NIR) and shortwave infrared (SWIR) in situ. It is shown that backscatter cross-section in the SWIR is insensitive to melanization and absolute melanization can be derived from the ratio of backscatter cross-section in two bands (SWIR/NIR). We have shown that insects reflect more strongly in the SWIR as compared to NIR and Visible (VIS) in accordance with previous findings. This is illustrated using three different insects (Snow white moth (spilosoma genus), Fox moth (Macrothylacia) and Leather beetle (Odontotaenius genus)) and it is shown that the reflectance of the Leather beetle in the VIS and NIR is more affected by melanization as compared with snow white moth.
Quantitative investigation of insect activity in their natural habitat is a challenging task for entomologists. It is difficult to address questions such as flight direction, predation strength, and overall activities using the current techniques such as traps and sweep nets. A multispectral kHz remote detection system using sunlight as an illumination source is presented. We explore the possibilities of remote optical classification of insects based on their wing-beat frequencies and iridescence features. It is shown that the wing-beat frequency of the fast insect events can be resolved by implementing high-sampling frequency. The iridescence features generated from the change of color in two channels (visible and near-infrared) during wing-beat cycle are presented. We show that the shape of the wing-beat trajectory is different for different insects. The flight direction of an atmospheric insect is also determined using a silicon quadrant detector.
Quantitative investigation of insect activity in their natural habitat is a challenging task for entomologist. It is difficult to address questions such as flight direction, predation strength and overall activities using the current techniques such as traps and sweep nets. A multi-spectral kHz remote detection system using sunlight as an illumination source is presented. We explore possibilities of remote optical classification of insects based on their wing-beat frequencies and iridescence features. It is shown that the wing-beat frequency of the fast insect events can be resolved by implementing high sampling frequency. The iridescence features generated from the change of color in two channels (visible and near infrared) during wing-beat cycle is presented. We show that the shape of the wing-beat trajectory is different for different insects. The flight direction of atmospheric insect is also determined using silicon quadrant detector.
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