Search Results (41)

Honeybee (Apis mellifera) flight and vertical locomotion were investigated using high-speed imaging and schlieren flow visualization. Free-flight recordings were analyzed to extract wingbeat frequency, projected stroke amplitude, wingtip trajectories, and membrane deformation. The wingtip trajectory exhibited a pronounced asymmetry between upstroke and downstroke, suggesting a dominant role of the downstroke in thrust production. Significant membrane deformation was observed near stroke reversal, indicating strong wing flexibility and dynamic modulation of wing shape during flapping. A novel support-based framework was introduced to characterize vertical locomotion through the support polygon formed by leg contact points and the displacement of its centroid relative to the body. This movement function quantified changes in support distribution and revealed adaptive leg-contact strategies during wall climbing. Schlieren visualization provided qualitative evidence of wingtip vortex formation, although finer wake structures remained difficult to resolve. These findings provide new experimental observations of honeybee flight kinematics and introduce a quantitative framework for analyzing vertical locomotion using support redistribution metrics. Full article

Tracking multiple targets within a group is a challenging task in the radar field, especially for a bird flock. Targets in a group are usually closely spaced and exhibit similar characteristics. Additionally, the tracking radar typically employs a narrow beam to achieve a high range–angular resolution, resulting in incomplete measurements within the limited beamwidth. These factors lead to false association and track fragmentation in target tracking. However, in addition to kinematic characteristics, birds exhibit temporally correlated micro-Doppler signatures because of their wingbeat behavior, which can be utilized in target tracking. Therefore, this paper proposes an adaptive TPHD tracking method using Doppler features. First, a Doppler temporal contrastive network is designed to learn the micro-Doppler representation for the association of birds. Then, the learned feature is fused with kinematic parameters, using XGBoost to guide the weight update in the filter. Moreover, adaptive mechanisms are incorporated into the TPHD filter to achieve stable tracking under incomplete measurements. Simulation and experimental results verified the effectiveness of the proposed method and showed better tracking performance than the competing method. Full article

The clover cutworm, Anarta trifolii (Lepidoptera: Noctuidae), constitutes a polyphagous pest known for causing sporadic, local outbreaks that significantly damage Beta vulgaris, Gossypium hirsutum, Brassica oleracea and others. Evidence supports the occurrence of seasonal migration in this species, but the determinants of A. trifolii flight performance remain unexplored. Understanding the species’ flight performance is essential for predicting its long-distance dispersal, identifying source and sink populations, and improving regional pest forecasting. We characterized flight performance and its influencing factors via computer-monitored flight mills. Maximum flight performance was achieved in A. trifolii adults at two days, followed by a significant decline with increasing age. At 24 °C and 80% relative humidity (RH), in a 12 h test, males and females aged two days achieved total flight distances of 38.90 ± 1.21 km and 31.70 ± 1.56 km, respectively. In a 24 h test, three-day-old adults reached a maximum flight speed of 19.68 km/h, a sustained flight duration of 17.38 h, a total flight duration of 23.89 h, a sustained flight distance of 69.64 km, and a total flight distance of 96.56 km. The flight performance of A. trifolii was significantly affected by both temperature and RH, with the maximum flight capacity achieved at 18–28 °C and 35–80% RH. Flight performance was significantly enhanced when A. trifolii were fed honey or sucrose. Moreover, the wingbeat frequency of A. trifolii adults varied among age groups, ranging from 31.90 to 57.65 Hz. In females, the wingbeat frequency peaked at 2 days old (46.72 ± 0.25 Hz), whereas in males it peaked at 10 days old (47.18 ± 0.66 Hz). These results advance the fundamental understanding of A. trifolii migration and offer practical applications, including improved pest management strategies, optimized use of chemical insecticides and biological control agents, and enhanced decision-making in integrated pest management programs. Full article

The aerodynamics of avian flight provides critical inspiration for the design of bioinspired aerial vehicles, yet the quantitative characterization of free-flight wing kinematics remains challenging. This study employs a neural-network-based motion tracking approach (DeepLabCut) to analyze wingbeat kinematics in free-flying birds from video data. We automatically digitize key wing points and reconstruct three-dimensional trajectories to quantify asymmetric flapping patterns. Our analysis reveals that while wing oscillations approximate sinusoidal motion, they exhibit statistically significant velocity differences between upstroke and downstroke phases, confirming the stroke asymmetry of avian flapping. Furthermore, using video of a flying frigatebird (Fregata ariel), we quantify the changes in the effective wing area throughout the wingbeat cycle, showing a ~19% variation that significantly impacts lift generation efficiency. These findings provide quantitative benchmarks for avian-inspired wing design and offer insights for optimizing flapping kinematics in bioinspired aerial systems, particularly for enhancing takeoff and landing capabilities in micro air vehicles. Full article

We developed an intelligent acoustic health monitoring system for honeybee colonies based on wingbeat frequency analysis, offering a practical solution for modernizing apicultural practices. The system employs a three-layer architecture—the Internet of Things, fog, and cloud—to achieve real-time, non-invasive hive condition assessment. At the edge level, a Raspberry Pi and low-noise microphone continuously capture in-hive audio, which is converted into spectrograms using short-time Fourier transform (STFT). These are analyzed by a deep learning classification model deployed on the fog layer to distinguish four critical queen-related states: original queen present, queen absent, new queen rejected, and new queen accepted. The cloud layer supports data storage, visualization, and model refinement through manual annotations. Our results show that both the vision Transformer and CNN models perform effectively in classifying complex hive states, each contributing to the overall classification task, demonstrating the system’s potential for improving colony management and early intervention. This work contributes to precision apiculture by enabling scalable, real-time queen status monitoring through acoustic sensing and deep learning. Full article

This paper investigates the flight kinematics and unsteady aerodynamics of butterfly flight using high-speed schlieren imaging. Butterfly trajectories are reconstructed to examine flight control mechanisms, with particular emphasis on thorax-driven manoeuvring and body reorientation. By reconstructing free-flight trajectories utilizing image recognition algorithms, we isolate the mechanisms of flight control, with particular emphasis on how thoracic oscillation drives manoeuvring and body reorientation. Phase-resolved analysis reveals distinct wingbeat modes, including clap-and-fling motions associated with hovering and low-speed ascent. Schlieren visualization further captures a detailed view of the wake topology, displaying the formation and evolution of wingtip vortices during the downstroke, as well as attached and entrained flow structures during cupped wing configurations. The results demonstrate the strong coupling between body dynamics, wing kinematics, and wake structure, highlighting how butterflies combine aerodynamic and inertial mechanisms to achieve efficient lift generation and control. These findings provide biomimetic insights relevant to the design of flapping wing micro air vehicles, particularly for low-speed flight, hover efficiency, and passive stability and control through body–wing coupling. Full article

Understanding how birds adjust their flight in response to biomechanical characteristics and environmental conditions can be useful for interpreting homing behavior. This study investigates homing pigeons’ (Columba livia) flight behavior using multi-sensor biologgers, integrating GPS, tri-axial accelerometer, pressure, and temperature sensors. Flight biomechanics were assessed by extracting: wingbeat frequency from the Short-Time Fourier Transform of the total acceleration signal and peak-to-peak acceleration from the dorso-ventral component. Landscape characteristics were provided by classifying land cover along the route using a geographic atlas and by computing flight altitude above ground level through the combination of pressure-derived altitude and a digital elevation model. The results reveal a progressive decrease in wingbeat frequency along the homing route, showing a linear relationship with traveled distance. To assess whether this pattern can be interpreted in terms of flight regulation, flight altitude was modeled as a function of biomechanical and environmental variables using a linear mixed-effect approach. The analysis indicates that flight altitude is significantly affected by wingbeat frequency as well as by temperature, ground speed, and land cover, with wingbeat frequency and temperature showing the strongest negative association. Full article

Manta ray tourism has become a multi-million-dollar industry proposed as a conservation tool in recent decades; however, its impacts remain unclear. We use drones and Markov models to quantify the effects of diver presence on a juvenile population of the recently described Atlantic manta ray (Mobula yarae) off the coast of Florida. We contrast diver effects on behavioral states (avoidance, feeding, and neutral), examine the responses of individual manta rays, and estimate the energetic costs of diver presence. Diver presence significantly influenced manta ray behavior. Manta rays spent 37% of their time avoiding divers, with neutral and feeding manta rays having an increased probability of transitioning to avoidance states in the presence of divers. We found a significant difference in the proportion of time individual manta rays spent in avoidance, with some individuals being highly avoidant (up to 70%), while others were less affected by diver presence (<20% avoidance). While wingbeat frequency did not change in the presence of divers, manta rays with divers spent significantly more time with their cephalic fins unfurled. Our findings suggest that tourism could negatively impact this small, vulnerable population, making it unsuitable for development. We recommend similar behavioral and kinematic assessments to guide sustainable wildlife tourism management. Full article

The wing kinematics of birds plays a significant role in their excellent unsteady aerodynamic performance. However, most studies investigate the influence of different kinematic parameters of flapping wings on their aerodynamic performance based on simple harmonic motions, which neglect the aerodynamic effects of the real flapping motion. The purpose of this article was to study the effects of wing kinematics on aerodynamic performance for a pigeon-inspired flapping wing. In this article, the dynamic geometric shape of a flapping wing was reconstructed based on data of the pigeon wing profile. The 3D wingbeat kinematics of a flying pigeon was extracted from the motion trajectories of the wingtip and the wrist during cruise flight. Then, we used a hybrid RANS/LES method to study the effects of wing kinematics on the aerodynamic performance and flow patterns of the pigeon-inspired flapping wing. First, we investigated the effects of dynamic spanwise twisting on the lift and thrust performance of the flapping wing. Numerical results show that the twisting motion weakens the leading-edge vortex (LEV) on the upper surface of the wing during the downstroke by reducing the effective angle of attack, thereby significantly reducing the time-averaged lift and power consumption. Then, we further studied the effects of the 3D sweeping motion on the aerodynamic performance of the flapping wing. Backward sweeping reduces the wing area and weakens the LEV on the lower surface of the wing, which increases the lift and reduces the aerodynamic power consumption significantly during the upstroke, leading to a high lift efficiency. These conclusions are significant for improving the aerodynamic performance of bionic flapping-wing micro air vehicles. Full article

While the formation flight of birds offers numerous benefits, such as reduced predation risk, improved orientation, and enhanced communication, the aerodynamic interactions between birds are not fully understood due to their inherent complexity. This study explores the wake vortex dynamics of two flying birds and their influence on aerodynamic forces, based on their relative positions in a group. Using a computational finite volume method, the 3D vortex patterns in the wake of Canada Geese (Branta canadensis) flying at 1000 m altitude and 13.9 m/s airspeed were modeled. The results reveal a complex, undulating vortex structure shaped by the wingbeat amplitude and frequency. The analysis shows that trailing birds positioning their wingtips within the upwash region of vortices that are generated by a leading bird significantly reduce drag and enhance lift, achieving up to a 32% improvement in aerodynamic efficiency, calculated as the lift-to-drag ratio. An optimal separation distance of approximately one wavelength (3.47 m) between birds has been identified, leading to a 7% reduction in both mean drag force and aerodynamic power requirements. These findings, extrapolated to larger bird groups, offer valuable insights into the organization and optimal positioning of birds flying in V-formations, advancing our understanding of collective flight dynamics. Full article

Citrus tristeza virus (CTV) is a vector-borne virus that poses a significant threat to citrus production worldwide, inducing a variety of symptoms. Therefore, a detailed knowledge of local aphids, identification of viruliferous species, and the development of new monitoring tools are necessary to improve CTV control strategies. Herein, a 2-year survey was conducted to assess the frequency of aphid species infesting several citrus pilot orchards. Plot findings based on morphological and molecular identification revealed Aphis spiraecola (ranged from 44–100%) as the most abundant aphid species, followed by A. gossypii (<50%). Toxoptera aurantii, Myzus persicae, and A. craccivora were present in low numbers, and A. citricidus was not detected. Due to the absence of CTV detection in aphids and citrus trees from the pilot orchards, a complementary survey was conducted in CTV-infected fields. Three aphid species were identified as CTV-positive by RT-PCR, suggesting that they may be viruliferous, with A. spiraecola as predominant, followed by A. gossypii and T. aurantii. Additionally, we developed a non-invasive procedure for identifying aphid species using wingbeat analysis. This method provides a faster alternative to traditional identification techniques by taxonomic keys based on morphological features or PCR, although its accuracy is lower (approximately 95% for the two species tested). Overall, this work provides a detailed study of aphid species composition in citrus orchards, identifies the predominant local putative CTV vector, and introduces a novel sensor for aphid monitoring, contributing to improved epidemic forecasting and sustainable disease management strategies. Full article

Excessive mating is a significant welfare concern for floor-reared broiler breeder hens. Perches have shown potential as a solution to mitigate this issue; however, limited research is available on the design parameters of perches. Understanding the jumping characteristics of broiler breeder hens is crucial for designing safe and functional perches. In this study, perching platforms were selected to ensure the safety of hens during jumps. Videos of hens performing voluntary jumps from varying heights (35, 40, 45, and 50 cm) were analyzed using Tracker (version 6.2.0) software. The results showed that the take-off latency (TL) and jump duration (JD) increased with height increases, with downward jumps exhibiting a 66.1% and 10.7% higher TL and JD than those of upward jumps (based on mean values), respectively. However, the latency to achieve balance (LAB) decreased by 76.5% during downward jumps (based on mean values). During upward jumps, both the wing-beating frequencies during the jump (WBJD) and after landing (WBL) increased with height increases. The interaction between the height and direction of jumping significantly affected the horizontal displacement (body) and angles (body and head) during the JL phase (p < 0.05). The body horizontal displacement during downward jumps was up to 70.3% higher than that during upward jumps (based on mean values), while the downward body angles were more minor than those during upward jumps. The lowest body and head angles of downward jumps were 42.2° ± 5.4° and 33.4° ± 5.6°, respectively. The results related to TL and LAB are expected to provide guidance for designing appropriate heights in perching facilities. Meanwhile, the findings on horizontal displacement and jump angles offer valuable insights for the safe distance and angle design between perching platforms. Full article

Birds have remarkable flight capabilities due to their adaptive wing morphology. However, studying live birds is time-consuming and laborious, and obtaining information about the complete wingbeat cycle is difficult. To address this issue and provide a complete dataset, we recorded comprehensive motion capture wing trajectory data from five free-flying pigeons (Columba livia). Five key motion parameters are used to quantitatively characterize wing kinematics: flapping, sweeping, twisting, folding and bending. In addition, the forelimb skeleton is mapped using an open-chain three-bar mechanism model. By systematically evaluating the relationship of joint degrees of freedom (DOFs), we configured the model as a 3-DOF shoulder, 1-DOF elbow and 2-DOF wrist. Based on the correlation analysis between wingbeat kinematics and joint movement, we found that the strongly correlated shoulder and wrist roll within the stroke plane cause wing flap and bending. There is also a strong correlation between shoulder, elbow and wrist yaw out of the stroke plane, which causes wing sweep and fold. By simplifying the wing morphing, we developed three flapping wing robots, each with different DOFs inside and outside the stroke plane. This study provides insight into the design of flapping wing robots capable of mimicking the 3D wing motion of pigeons. Full article

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. Full article

The diamondback moth, Plutella xylostella L. (Lepidoptera: Plutellidae), is a cosmopolitan horticultural pest that is undergoing a fast, climate-driven range expansion. Its wide geographic distribution, pest status, and high incidence of insecticide resistance are directly tied to long-distance migration. Wingbeat frequency (WBF) is a key aspect of P. xylostella migratory behavior, but has received limited scientific attention. Here, we investigated the effects of environmental parameters, age, adult nutrition, and sex on P. xylostella WBF. Across experimental regimes, WBF ranged from 31.39 Hz to 78.87 Hz. Over a 10–35 °C range, the WBF of both male and female moths increased with temperature up to 62.96 Hz. Though male WBF was unaffected by humidity, females exhibited the highest WBF at 15% relative humidity (RH). WBF was unaffected by adult age, but adult nutrition exerted important impacts. Specifically, the WBF of moths fed honey water (54.66 Hz) was higher than that of water-fed individuals (49.42 Hz). Lastly, males consistently exhibited a higher WBF than females. By uncovering the biological and (nutritional) ecological determinants of diamondback moth flight, our work provides invaluable guidance to radar-based monitoring, migration forecasting, and the targeted deployment of preventative mitigation tactics. Full article