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Journal articles on the topic 'Insect tracking'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Ratnayake, Malika Nisal, Adrian G. Dyer, and Alan Dorin. "Tracking individual honeybees among wildflower clusters with computer vision-facilitated pollinator monitoring." PLOS ONE 16, no. 2 (February 11, 2021): e0239504. http://dx.doi.org/10.1371/journal.pone.0239504.

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Monitoring animals in their natural habitat is essential for advancement of animal behavioural studies, especially in pollination studies. Non-invasive techniques are preferred for these purposes as they reduce opportunities for research apparatus to interfere with behaviour. One potentially valuable approach is image-based tracking. However, the complexity of tracking unmarked wild animals using video is challenging in uncontrolled outdoor environments. Out-of-the-box algorithms currently present several problems in this context that can compromise accuracy, especially in cases of occlusion in a 3D environment. To address the issue, we present a novel hybrid detection and tracking algorithm to monitor unmarked insects outdoors. Our software can detect an insect, identify when a tracked insect becomes occluded from view and when it re-emerges, determine when an insect exits the camera field of view, and our software assembles a series of insect locations into a coherent trajectory. The insect detecting component of the software uses background subtraction and deep learning-based detection together to accurately and efficiently locate the insect among a cluster of wildflowers. We applied our method to track honeybees foraging outdoors using a new dataset that includes complex background detail, wind-blown foliage, and insects moving into and out of occlusion beneath leaves and among three-dimensional plant structures. We evaluated our software against human observations and previous techniques. It tracked honeybees at a rate of 86.6% on our dataset, 43% higher than the computationally more expensive, standalone deep learning model YOLOv2. We illustrate the value of our approach to quantify fine-scale foraging of honeybees. The ability to track unmarked insect pollinators in this way will help researchers better understand pollination ecology. The increased efficiency of our hybrid approach paves the way for the application of deep learning-based techniques to animal tracking in real-time using low-powered devices suitable for continuous monitoring.

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2

Shen, Minmin, Chen Li, Wei Huang, Paul Szyszka, Kimiaki Shirahama, Marcin Grzegorzek, Dorit Merhof, and Oliver Deussen. "Interactive tracking of insect posture." Pattern Recognition 48, no. 11 (November 2015): 3560–71. http://dx.doi.org/10.1016/j.patcog.2015.05.011.

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3

Pannequin, Rémi, Mélanie Jouaiti, Mohamed Boutayeb, Philippe Lucas, and Dominique Martinez. "Automatic tracking of free-flying insects using a cable-driven robot." Science Robotics 5, no. 43 (June 10, 2020): eabb2890. http://dx.doi.org/10.1126/scirobotics.abb2890.

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Flying insects have evolved to develop efficient strategies to navigate in natural environments. Yet, studying them experimentally is difficult because of their small size and high speed of motion. Consequently, previous studies were limited to tethered flights, hovering flights, or restricted flights within confined laboratory chambers. Here, we report the development of a cable-driven parallel robot, named lab-on-cables, for tracking and interacting with a free-flying insect. In this approach, cameras are mounted on cables, so as to move automatically with the insect. We designed a reactive controller that minimizes the online tracking error between the position of the flying insect, provided by an embedded stereo-vision system, and the position of the moving lab, computed from the cable lengths. We validated the lab-on-cables with Agrotis ipsilon moths (ca. 2 centimeters long) flying freely up to 3 meters per second. We further demonstrated, using prerecorded trajectories, the possibility to track other insects such as fruit flies or mosquitoes. The lab-on-cables is relevant to free-flight studies and may be used in combination with stimulus delivery to assess sensory modulation of flight behavior (e.g., pheromone-controlled anemotaxis in moths).

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4

Cai, Z. J., and Li Jiang Zeng. "A Fast Search Coil Sensing Method for Tracking Systems." Key Engineering Materials 295-296 (October 2005): 601–6. http://dx.doi.org/10.4028/www.scientific.net/kem.295-296.601.

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It is important to track a free flying insect to investigate its flight performance. Conventional video tracking systems are difficult to track a highly maneuverable insect, because the capture frequency of the camera is limited and it can hardly get the position of the insect in real time. We proposed a fast sensing method for insect tracking based on magnetic search coil sensors. It can simultaneously determine the orientation and position of the sensors. We constructed a system, calibrated the magnetic device. We developed a set of calculating methods and measured several positions and angles of coil sensors. The results show that it can rapidly provide the tracking feedback information to meet the requirement for insect tracking.

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5

Schachat, Sandra R., Conrad C. Labandeira, Matthew R. Saltzman, Bradley D. Cramer, Jonathan L. Payne, and C. Kevin Boyce. "Phanerozoic p O 2 and the early evolution of terrestrial animals." Proceedings of the Royal Society B: Biological Sciences 285, no. 1871 (January 24, 2018): 20172631. http://dx.doi.org/10.1098/rspb.2017.2631.

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Concurrent gaps in the Late Devonian/Mississippian fossil records of insects and tetrapods (i.e. Romer's Gap) have been attributed to physiological suppression by low atmospheric p O 2 . Here, updated stable isotope inputs inform a reconstruction of Phanerozoic oxygen levels that contradicts the low oxygen hypothesis (and contradicts the purported role of oxygen in the evolution of gigantic insects during the late Palaeozoic), but reconciles isotope-based calculations with other proxies, like charcoal. Furthermore, statistical analysis demonstrates that the gap between the first Devonian insect and earliest diverse insect assemblages of the Pennsylvanian (Bashkirian Stage) requires no special explanation if insects were neither diverse nor abundant prior to the evolution of wings. Rather than tracking physiological constraint, the fossil record may accurately record the transformative evolutionary impact of insect flight.

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6

Fang, Linlin, Weiming Tian, Rui Wang, Chao Zhou, and Cheng Hu. "Design of Insect Target Tracking Algorithm in Clutter Based on the Multidimensional Feature Fusion Strategy." Remote Sensing 13, no. 18 (September 18, 2021): 3744. http://dx.doi.org/10.3390/rs13183744.

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Entomological radar is an effective means of monitoring insect migration, and can realize long-distance and large-scale rapid monitoring. The stable tracking of individual insect targets is the basic premise underlying the identification of insect species and the study of insect migration mechanisms. However, the complex motion trajectory and large number of false measurements decrease the performance of insect target tracking. In this paper, an insect target tracking algorithm in clutter was designed based on the multidimensional feature fusion strategy (ITT-MFF). Firstly, multiple feature parameters of measurements were fused to calculate the membership of measurements and target, thereby improving the data association accuracy in the presence of clutter. Secondly, a distance-correction factor was introduced to the probabilistic data association (PDA) algorithm to accomplish multi-target data association with a low computational cost. Finally, simulation scenarios with different target numbers and clutter densities were constructed to verify the effectiveness of the proposed method. The tracking result comparisons of the experimental data acquired from a Ku-band entomological radar also indicate that the proposed method can effectively reduce computational cost while maintaining high tracking precision, and is suitable for engineering implementation.

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7

Kinyuru, J. N., and N. W. Ndung’u. "Promoting edible insects in Kenya: historical, present and future perspectives towards establishment of a sustainable value chain." Journal of Insects as Food and Feed 6, no. 1 (February 6, 2020): 51–58. http://dx.doi.org/10.3920/jiff2019.0016.

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This paper discusses the current state and priorities of Kenya-based research and innovations on insects as food and feed with a view to establishing a vibrant insects’ value chain. The paper is divided into sections that focus on historical insect consumption, farming, utilisation and entrepreneurial priorities. The paper also introduces a new quadrat model for utilisation of edible insects which shows an interrelationship between edible insects, crops, animals and humans. The paper attempts to identify attempts on identifying social and psychological barriers to insects’ acceptance as food and feed since insects are intimately connected to strong cultural and regional values. We conclude with recommendations about the future priorities of edible insect field which include: tracking of production volumes, new innovations to support automation and industrial production, research on consumer attitudes and behaviour that is culturally sensitive, systematic, and large-scale; enactment of national and regional regulations to support the industry and unequivocal acknowledgment of the impacts of developments in the edible insect industry to national and regional development.

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8

Viikari, Ville, Jonathan Chisum, and Heikki Seppä. "Wireless passive photo detector for insect tracking." Microwave and Optical Technology Letters 52, no. 10 (July 14, 2010): 2312–15. http://dx.doi.org/10.1002/mop.25427.

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9

Bagheri, Zahra M., Steven D. Wiederman, Benjamin S. Cazzolato, Steven Grainger, and David C. O'Carroll. "Properties of neuronal facilitation that improve target tracking in natural pursuit simulations." Journal of The Royal Society Interface 12, no. 108 (July 2015): 20150083. http://dx.doi.org/10.1098/rsif.2015.0083.

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Although flying insects have limited visual acuity (approx. 1°) and relatively small brains, many species pursue tiny targets against cluttered backgrounds with high success. Our previous computational model, inspired by electrophysiological recordings from insect ‘small target motion detector’ (STMD) neurons, did not account for several key properties described from the biological system. These include the recent observations of response ‘facilitation’ (a slow build-up of response to targets that move on long, continuous trajectories) and ‘selective attention’, a competitive mechanism that selects one target from alternatives. Here, we present an elaborated STMD-inspired model, implemented in a closed loop target-tracking system that uses an active saccadic gaze fixation strategy inspired by insect pursuit. We test this system against heavily cluttered natural scenes. Inclusion of facilitation not only substantially improves success for even short-duration pursuits, but it also enhances the ability to ‘attend’ to one target in the presence of distracters. Our model predicts optimal facilitation parameters that are static in space and dynamic in time, changing with respect to the amount of background clutter and the intended purpose of the pursuit. Our results provide insights into insect neurophysiology and show the potential of this algorithm for implementation in artificial visual systems and robotic applications.

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10

Dixon, A. F. G., V. A. Drake, and A. G. Gatehouse. "Insect Migration: Tracking Resources Through Space and Time." Journal of Applied Ecology 33, no. 4 (August 1996): 907. http://dx.doi.org/10.2307/2404963.

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11

Gibo, David L., V. A. Drake, and A. G. Gatehouse. "Insect Migration: Tracking Resources through Space and Time." Ecology 77, no. 8 (December 1996): 2575. http://dx.doi.org/10.2307/2265759.

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12

Walker, Thomas J., V. A. Drake, and A. G. Gatehouse. "Insect Migration: Tracking Resources through Space and Time." Florida Entomologist 79, no. 3 (September 1996): 474. http://dx.doi.org/10.2307/3495603.

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13

van Huis, A. "Insect migration: Tracking resources through space and time." Endeavour 20, no. 3 (January 1996): 136. http://dx.doi.org/10.1016/0160-9327(96)88975-7.

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14

Hill, Jane, V. A. Drake, and A. G. Gatehouse. "Insect Migration: Tracking Resources Through Space and Time." Journal of Animal Ecology 65, no. 6 (November 1996): 852. http://dx.doi.org/10.2307/5686.

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15

Bjerge, Kim, Jakob Bonde Nielsen, Martin Videbæk Sepstrup, Flemming Helsing-Nielsen, and Toke Thomas Høye. "An Automated Light Trap to Monitor Moths (Lepidoptera) Using Computer Vision-Based Tracking and Deep Learning." Sensors 21, no. 2 (January 6, 2021): 343. http://dx.doi.org/10.3390/s21020343.

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Insect monitoring methods are typically very time-consuming and involve substantial investment in species identification following manual trapping in the field. Insect traps are often only serviced weekly, resulting in low temporal resolution of the monitoring data, which hampers the ecological interpretation. This paper presents a portable computer vision system capable of attracting and detecting live insects. More specifically, the paper proposes detection and classification of species by recording images of live individuals attracted to a light trap. An Automated Moth Trap (AMT) with multiple light sources and a camera was designed to attract and monitor live insects during twilight and night hours. A computer vision algorithm referred to as Moth Classification and Counting (MCC), based on deep learning analysis of the captured images, tracked and counted the number of insects and identified moth species. Observations over 48 nights resulted in the capture of more than 250,000 images with an average of 5675 images per night. A customized convolutional neural network was trained on 2000 labeled images of live moths represented by eight different classes, achieving a high validation F1-score of 0.93. The algorithm measured an average classification and tracking F1-score of 0.71 and a tracking detection rate of 0.79. Overall, the proposed computer vision system and algorithm showed promising results as a low-cost solution for non-destructive and automatic monitoring of moths.

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16

Howard, Scarlett R., Malika Nisal Ratnayake, Adrian G. Dyer, Jair E. Garcia, and Alan Dorin. "Towards precision apiculture: Traditional and technological insect monitoring methods in strawberry and raspberry crop polytunnels tell different pollination stories." PLOS ONE 16, no. 5 (May 14, 2021): e0251572. http://dx.doi.org/10.1371/journal.pone.0251572.

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Over one third of crops are animal pollinated, with insects being the largest group. In some crops, including strawberries, fruit yield, weight, quality, aesthetics and shelf life increase with insect pollination. Many crops are protected from extreme weather in polytunnels, but the impacts of polytunnels on insects are poorly understood. Polytunnels could reduce pollination services, especially if insects have access issues. Here we examine the distribution and activity of honeybees and non-honeybee wild insects on a commercial fruit farm. We evaluated whether insect distributions are impacted by flower type (strawberry; raspberry; weed), or distance from polytunnel edges. We compared passive pan-trapping and active quadrat observations to establish their suitability for monitoring insect distribution and behaviour on a farm. To understand the relative value of honeybees compared to other insects for strawberry pollination, the primary crop at the site, we enhanced our observations with video data analysed using insect tracking software to document the time spent by insects on flowers. The results show honeybees strongly prefer raspberry and weed flowers over strawberry flowers and that location within the polytunnel impacts insect distributions. Consistent with recent studies, we also show that pan-traps are ineffective to sample honeybee numbers. While the pan-traps and quadrat observations tend to suggest that investment in managed honeybees for strawberry pollination might be ineffective due to consistent low numbers within the crop, the camera data provides contrary evidence. Although honeybees were relatively scarce among strawberry crops, camera data shows they spent more time visiting flowers than other insects. Our results demonstrate that a commercial fruit farm is a complex ecosystem influencing pollinator diversity and abundance through a range of factors. We show that monitoring methods may differ in their valuation of relative contributions of insects to crop pollination.

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17

Stöckl, Anna L., Klara Kihlström, Steven Chandler, and Simon Sponberg. "Comparative system identification of flower tracking performance in three hawkmoth species reveals adaptations for dim light vision." Philosophical Transactions of the Royal Society B: Biological Sciences 372, no. 1717 (April 5, 2017): 20160078. http://dx.doi.org/10.1098/rstb.2016.0078.

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Flight control in insects is heavily dependent on vision. Thus, in dim light, the decreased reliability of visual signal detection also prompts consequences for insect flight. We have an emerging understanding of the neural mechanisms that different species employ to adapt the visual system to low light. However, much less explored are comparative analyses of how low light affects the flight behaviour of insect species, and the corresponding links between physiological adaptations and behaviour. We investigated whether the flower tracking behaviour of three hawkmoth species with different diel activity patterns revealed luminance-dependent adaptations, using a system identification approach. We found clear luminance-dependent differences in flower tracking in all three species, which were explained by a simple luminance-dependent delay model, which generalized across species. We discuss physiological and anatomical explanations for the variance in tracking responses, which could not be explained by such simple models. Differences between species could not be explained by the simple delay model. However, in several cases, they could be explained through the addition on a second model parameter, a simple scaling term, that captures the responsiveness of each species to flower movements. Thus, we demonstrate here that much of the variance in the luminance-dependent flower tracking responses of hawkmoths with different diel activity patterns can be captured by simple models of neural processing. This article is part of the themed issue ‘Vision in dim light’.

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18

Guo, Wei, Qingjie Zhao, and Dongbing Gu. "Visual Tracking Using an Insect Vision Embedded Particle Filter." Mathematical Problems in Engineering 2015 (2015): 1–16. http://dx.doi.org/10.1155/2015/573131.

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Particle filtering (PF) based object tracking algorithms have drawn great attention from lots of scholars. The core of PF is to predict the possible location of the target via the state transition model. One commonly adopted approach is resorting to prior motion cues under the smooth motion assumption, which performs well when the target moves with a relatively stable velocity. However, it would possibly fail if the target is undergoing abrupt motion. To address this problem, inspired by insect vision, we propose a simple yet effective visual tracking framework based on PF. Utilizing the neuronal computational model of the insect vision, we estimate the motion of the target in a novel way so as to refine the position state of propagated particles using more accurate transition mode. Furthermore, we design a novel sample optimization framework where local and global search strategies are jointly used. In addition, we propose a new method to monitor long duration severe occlusion and we could recover the target. Experiments on publicly available benchmark video sequences demonstrate that the proposed tracking algorithm outperforms the state-of-the art methods in challenging scenarios, especially for tracking target which is undergoing abrupt motion or fast movement.

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19

Cheng, Bo, and Xinyan Deng. "A Neural Adaptive Controller in Flapping Flight." Journal of Robotics and Mechatronics 24, no. 4 (August 20, 2012): 602–11. http://dx.doi.org/10.20965/jrm.2012.p0602.

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In this paper, we propose a neural adaptive controller for attitude control in a flapping-wing insect model. The model is nonlinear and subjected to periodic force/torque generated by nominal wing kinematics. Two sets of model parameters are obtained from the fruit flyDrosophila melanogasterand the honey beeApis mellifera. Attitude control is achieved by modifying the wing kinematics on a stroke-by-stroke basis. The controller is based on filtered-error with neural network models approximating system nonlinearities. Lyapunov-based stability analysis shows the asymptotic convergence of system outputs. We present simulation results for angular position stabilization and trajectory tracking. Trajectory tracking is illustrated by two cases: saccadic turning and sinusoidal variation in the yaw angle. The proposed controller successfully regulates flight orientation – roll, pitch and yaw angles – by generating desired torque resulting from tuning parameterized wing motion. Results furthermore show similarities between simulated and observed turning from real insects, suggesting some inherent properties in insect flight dynamics and control. The proposed controller has potential applications in future flapping-wing Micro Air Vehicles (MAVs).

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20

Kumari, Meera, and S. M. Rezaul Hasan. "A New CMOS Implementation for Miniaturized Active RFID Insect Tag and VHF Insect Tracking." IEEE Journal of Radio Frequency Identification 4, no. 2 (June 2020): 124–36. http://dx.doi.org/10.1109/jrfid.2020.2964313.

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21

Colpitts, B. G., and G. Boiteau. "Harmonic Radar Transceiver Design: Miniature Tags for Insect Tracking." IEEE Transactions on Antennas and Propagation 52, no. 11 (November 2004): 2825–32. http://dx.doi.org/10.1109/tap.2004.835166.

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22

Pang, Rich, Floris van Breugel, Michael Dickinson, Jeffrey A. Riffell, and Adrienne Fairhall. "History dependence in insect flight decisions during odor tracking." PLOS Computational Biology 14, no. 2 (February 12, 2018): e1005969. http://dx.doi.org/10.1371/journal.pcbi.1005969.

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23

Sakakibara, Jun, Junichiro Kita, and Naoyuki Osato. "Note: High-speed optical tracking of a flying insect." Review of Scientific Instruments 83, no. 3 (March 2012): 036103. http://dx.doi.org/10.1063/1.3694569.

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24

Hallworth, Michael T., Peter P. Marra, Kent P. McFarland, Sara Zahendra, and Colin E. Studds. "Tracking dragons: stable isotopes reveal the annual cycle of a long-distance migratory insect." Biology Letters 14, no. 12 (December 2018): 20180741. http://dx.doi.org/10.1098/rsbl.2018.0741.

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Insect migration is globally ubiquitous and can involve continental-scale movements and complex life histories. Apart from select species of migratory moths and butterflies, little is known about the structure of the annual cycle for migratory insects. Using stable-hydrogen isotope analysis of 852 wing samples from eight countries spanning 140 years, combined with 21 years of citizen science data, we determined the full annual cycle of a large migratory dragonfly, the common green darner ( Anax junius ). We demonstrate that darners undertake complex long-distance annual migrations governed largely by temperature that involve at least three generations. In spring, the first generation makes a long-distance northbound movement (further than 650 km) from southern to northern range limits, lays eggs and dies. A second generation emerges and returns south (further than 680 km), where they lay eggs and die. Finally, a third resident generation emerges, reproducing locally and giving rise to the cohort that migrates north the following spring. Since migration timing and nymph development are highly dependent on temperature, continued climate change could lead to fundamental changes in the biology for this and similar migratory insects.

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Masson, Florent, Anna Zaidman-Rémy, and Abdelaziz Heddi. "Antimicrobial peptides and cell processes tracking endosymbiont dynamics." Philosophical Transactions of the Royal Society B: Biological Sciences 371, no. 1695 (May 26, 2016): 20150298. http://dx.doi.org/10.1098/rstb.2015.0298.

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Many insects sustain long-term relationships with intracellular symbiotic bacteria that provide them with essential nutrients. Such endosymbiotic relationships likely emerged from ancestral infections of the host by free-living bacteria, the genomes of which experience drastic gene losses and rearrangements during the host–symbiont coevolution. While it is well documented that endosymbiont genome shrinkage results in the loss of bacterial virulence genes, whether and how the host immune system evolves towards the tolerance and control of bacterial partners remains elusive. Remarkably, many insects rely on a ‘compartmentalization strategy’ that consists in secluding endosymbionts within specialized host cells, the bacteriocytes, thus preventing direct symbiont contact with the host systemic immune system. In this review, we compile recent advances in the understanding of the bacteriocyte immune and cellular regulators involved in endosymbiont maintenance and control. We focus on the cereal weevils Sitophilus spp., in which bacteriocytes form bacteriome organs that strikingly evolve in structure and number according to insect development and physiological needs. We discuss how weevils track endosymbiont dynamics through at least two mechanisms: (i) a bacteriome local antimicrobial peptide synthesis that regulates endosymbiont cell cytokinesis and helps to maintain a homeostatic state within bacteriocytes and (ii) some cellular processes such as apoptosis and autophagy which adjust endosymbiont load to the host developmental requirements, hence ensuring a fine-tuned integration of symbiosis costs and benefits. This article is part of the themed issue ‘Evolutionary ecology of arthropod antimicrobial peptides’.

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Iyer, Vikram, Ali Najafi, Johannes James, Sawyer Fuller, and Shyamnath Gollakota. "Wireless steerable vision for live insects and insect-scale robots." Science Robotics 5, no. 44 (July 15, 2020): eabb0839. http://dx.doi.org/10.1126/scirobotics.abb0839.

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Vision serves as an essential sensory input for insects but consumes substantial energy resources. The cost to support sensitive photoreceptors has led many insects to develop high visual acuity in only small retinal regions and evolve to move their visual systems independent of their bodies through head motion. By understanding the trade-offs made by insect vision systems in nature, we can design better vision systems for insect-scale robotics in a way that balances energy, computation, and mass. Here, we report a fully wireless, power-autonomous, mechanically steerable vision system that imitates head motion in a form factor small enough to mount on the back of a live beetle or a similarly sized terrestrial robot. Our electronics and actuator weigh 248 milligrams and can steer the camera over 60° based on commands from a smartphone. The camera streams “first person” 160 pixels–by–120 pixels monochrome video at 1 to 5 frames per second (fps) to a Bluetooth radio from up to 120 meters away. We mounted this vision system on two species of freely walking live beetles, demonstrating that triggering image capture using an onboard accelerometer achieves operational times of up to 6 hours with a 10–milliamp hour battery. We also built a small, terrestrial robot (1.6 centimeters by 2 centimeters) that can move at up to 3.5 centimeters per second, support vision, and operate for 63 to 260 minutes. Our results demonstrate that steerable vision can enable object tracking and wide-angle views for 26 to 84 times lower energy than moving the whole robot.

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Ben-Dov, Omri, and Tsevi Beatus. "Model-Based Tracking of Fruit Flies in Free Flight." Insects 13, no. 11 (November 3, 2022): 1018. http://dx.doi.org/10.3390/insects13111018.

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Insect flight is a complex interdisciplinary phenomenon. Understanding its multiple aspects, such as flight control, sensory integration, physiology and genetics, often requires the analysis of large amounts of free flight kinematic data. Yet, one of the main bottlenecks in this field is automatically and accurately extracting such data from multi-view videos. Here, we present a model-based method for the pose estimation of free-flying fruit flies from multi-view high-speed videos. To obtain a faithful representation of the fly with minimum free parameters, our method uses a 3D model that includes two new aspects of wing deformation: a non-fixed wing hinge and a twisting wing surface. The method is demonstrated for free and perturbed flight. Our method does not use prior assumptions on the kinematics apart from the continuity of the wing pitch angle. Hence, this method can be readily adjusted for other insect species.

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Gerken, Alison, and James Campbell. "Using Long-term Capture Data to Predict Trogoderma variabile Ballion and Plodia interpunctella (Hübner) Population Patterns." Insects 10, no. 4 (March 30, 2019): 93. http://dx.doi.org/10.3390/insects10040093.

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Insects can infest facilities that house and process post-harvest grains and grain-based products. Integrated pest management tactics rely on tracking insect populations and using this information to select and target management tactics. Our ability to predict when and where to best focus treatment relies on an understanding of long-term trends, but often any available monitoring data are limited in its duration. Here we present data collected over a 10-year period at a flour mill in the central part of the United States. Using traps placed both inside and outside a flour mill and baited with pheromone-lures for Plodia interpunctella (Hübner), Indianmeal moth, and Trogoderma variabile Ballion, warehouse beetle, we examine environmental and spatial variability in insect captures. We find that both species, inside and outside the mill, are highly influenced by seasonal patterns, with peaks of insect captures during the warm season (April through September). There is also consistency across time and space in trap capture for P. interpunctella with traps in an open location consistently capturing high numbers of insects. In contrast, T. variabile lacked consistency in trap capture but were most often not found in the same trap locations as P. interpunctella. Fumigations conducted within the facility appeared to have little impact on insect captures inside, with dynamics appearing to be driven more by broader seasonal patterns in activity. These data and analyses suggest that there is a larger population of these insects that are readily moving in and out of the structures, while fumigation treatments are only impacting a small portion of the overall population and tactics targeting immigration may be an important addition to the pest management program.

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29

Solbreck, C. "Book review: Insect migration: Tracking resources through space and time." Entomologia Experimentalis et Applicata 82, no. 3 (March 1997): 355–56. http://dx.doi.org/10.1046/j.1570-7458.1997.00150.x.

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30

Schade, John D., Marcia Kyle, S. E. Hobbie, W. F. Fagan, and J. J. Elser. "Stoichiometric tracking of soil nutrients by a desert insect herbivore." Ecology Letters 6, no. 2 (February 2003): 96–101. http://dx.doi.org/10.1046/j.1461-0248.2003.00409.x.

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31

Knight, Samantha M., Grace M. Pitman, D. T. Tyler Flockhart, and D. Ryan Norris. "Radio-tracking reveals how wind and temperature influence the pace of daytime insect migration." Biology Letters 15, no. 7 (July 2019): 20190327. http://dx.doi.org/10.1098/rsbl.2019.0327.

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Insects represent the most diverse and functionally important group of flying migratory animals around the globe, yet their small size makes tracking even large migratory species challenging. We attached miniaturized radio transmitters (less than 300 mg) to monarch butterflies ( Danaus plexippus ) and common green darner dragonflies ( Anax junius ) and tracked their autumn migratory movements through southern Ontario, Canada and into the United States using an automated array of over 100 telemetry towers. The farthest estimated distance a monarch travelled in a single day was 143 km at a wind-assisted groundspeed of 31 km h −1 (8.7 m s −1 ) and the farthest estimated distance a green darner travelled in a single day was 122 km with a wind-assisted groundspeed of up to 77 km h −1 (21.5 m s −1 ). For both species, increased temperature and wind assistance positively influenced the pace of migration, but there was no effect of precipitation. While limitations to tracking such small animals remain, our approach and results represent a fundamental advance in understanding the natural history of insect migration and environmental factors that govern their movements.

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Islam, Md Saiful, and Imraan A. Faruque. "Experimental identification of individual insect visual tracking delays in free flight and their effects on visual swarm patterns." PLOS ONE 17, no. 11 (November 28, 2022): e0278167. http://dx.doi.org/10.1371/journal.pone.0278167.

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Insects are model systems for swarming robotic agents, yet engineered descriptions do not fully explain the mechanisms by which they provide onboard sensing and feedback to support such motions; in particular, the exact value and population distribution of visuomotor processing delays are not yet quantified, nor the effect of such delays on a visually-interconnected swarm. This study measures untethered insects performing a solo in-flight visual tracking task and applies system identification techniques to build an experimentally-consistent model of the visual tracking behaviors, and then integrates the measured experimental delay and its variation into a visually interconnected swarm model to develop theoretical and simulated solutions and stability limits. The experimental techniques include the development of a moving visual stimulus and real-time multi camera based tracking system called VISIONS (Visual Input System Identification from Outputs of Naturalistic Swarms) providing the capability to recognize and simultaneously track both a visual stimulus (input) and an insect at a frame rate of 60-120 Hz. A frequency domain analysis of honeybee tracking trajectories is conducted via fast Fourier and Chirp Z transforms, identifying a coherent linear region and its model structure. The model output is compared in time and frequency domain simulations. The experimentally measured delays are then related to probability density functions, and both the measured delays and their distribution are incorporated as inter-agent interaction delays in a second order swarming dynamics model. Linear stability and bifurcation analysis on the long range asymptotic behavior is used to identify delay distributions leading to a family of solutions with stable and unstable swarm center of mass (barycenter) locations. Numerical simulations are used to verify these results with both continuous and measured distributions. The results of this experiment quantify a model structure and temporal lag (transport delay) in the closed loop dynamics, and show that this delay varies across 50 individuals from 5-110ms, with an average delay of 22ms and a standard deviation of 40ms. When analyzed within the swarm model, the measured delays support a diversity of solutions and indicate an unstable barycenter.

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Lavrenko, Anastasia, Benjamen Litchfield, Graeme Woodward, and Stephen Pawson. "Design and Evaluation of a Compact Harmonic Transponder for Insect Tracking." IEEE Microwave and Wireless Components Letters 30, no. 4 (April 2020): 445–48. http://dx.doi.org/10.1109/lmwc.2020.2972744.

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Harvey, D. J., Tien-Fu Lu, and M. A. Keller. "Comparing Insect-Inspired Chemical Plume Tracking Algorithms Using a Mobile Robot." IEEE Transactions on Robotics 24, no. 2 (April 2008): 307–17. http://dx.doi.org/10.1109/tro.2007.912090.

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35

Suchan, Tomasz, Gerard Talavera, Llorenç Sáez, Michał Ronikier, and Roger Vila. "Pollen metabarcoding as a tool for tracking long‐distance insect migrations." Molecular Ecology Resources 19, no. 1 (November 8, 2018): 149–62. http://dx.doi.org/10.1111/1755-0998.12948.

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Shortall, Chris R., Sarah A. M. Perryman, Kirstie Halsey, and Jon S. West. "The Potential of Fluorescence Imaging to Distinguish Insect Pest and Non-pest Species." Outlooks on Pest Management 33, no. 1 (February 1, 2022): 13–16. http://dx.doi.org/10.1564/v33_feb_05.

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Studying the presence and movement of insects is important in biological research for practical purposes regarding control of pests and environmental monitoring. Detection of insects by conventional trapping (e.g. the Rothamsted Insect Survey) and tracking technologies (e.g. the Rothamsted Radar Entomology Unit) have been effective for monitoring and forecasting pest migration but often require significant investment in capital costs and/or staff time. Insect detection using imaging of natural fluorescence (without additional fluorescent dyes) has been considered less, and much of the work on natural fluorescence in the animal world has been on marine organisms. Work on terrestrial arthropods has been more limited and restricted primarily to non-insect arthropods. Very early work on the distribution of fluorescent pigments in butterflies was demonstrated using long wave mercury vapour lamps followed by more work in the 1950s on butterflies, arthropods; including beetles, spiders and millipedes, cockroaches and eggs of Orthoptera. These studies often involved qualitative approaches; dissecting the animals and investigating internal organs and fluids for fluorescence as well as whole body studies. More recent studies have included quantitative work on butterflies and pest insects plus fluorescence studies in damselflies, moths, millipedes, bees and spiders. Fluorescence in juvenile stages is a property used for detection of flies and beetles in food stuffs. The vast majority of insects, however, have not been investigated for fluorescence and even in those taxa that have been studied, e.g. butterflies, the dataset is incomplete. The easiest way to observe fluorescence is to illuminate a subject with a known waveband of light in otherwise darkness and view or record an image via a filter that blocks the wavelength of the illuminating light. Any light viewed or captured at a different wavelength to the illumination, must have been produced by fluorescence. In contrast, some living organisms themselves can produce light or luminescence by internal chemical means. This work aimed to look at the potential of using natural fluorescence to detect and identify insects, particularly pests.

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Hanapi, Ummi Fairuz, Chean Yeah Yong, Zee Hong Goh, Noorjahan Banu Alitheen, Swee Keong Yeap, and Wen Siang Tan. "Tracking the virus-like particles of Macrobrachium rosenbergii nodavirus in insect cells." PeerJ 5 (February 8, 2017): e2947. http://dx.doi.org/10.7717/peerj.2947.

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Macrobrachium rosenbergii nodavirus (MrNv) poses a major threat to the prawn industry. Currently, no effective vaccine and treatment are available to prevent the spread of MrNv. Its infection mechanism and localisation in a host cell are also not well characterised. The MrNv capsid protein (MrNvc) produced in Escherichia coli self-assembled into virus-like particles (VLPs) resembling the native virus. Thus, fluorescein labelled MrNvc VLPs were employed as a model to study the virus entry and localisation in Spodoptera frugiperda, Sf9 cells. Through fluorescence microscopy and sub-cellular fractionation, the MrNvc was shown to enter Sf9 cells, and eventually arrived at the nucleus. The presence of MrNvc within the cytoplasm and nucleus of Sf9 cells was further confirmed by the Z-stack imaging. The presence of ammonium chloride (NH4Cl), genistein, methyl-β-cyclodextrin or chlorpromazine (CPZ) inhibited the entry of MrNvc into Sf9 cells, but cytochalasin D did not inhibit this process. This suggests that the internalisation of MrNvc VLPs is facilitated by caveolae- and clathrin-mediated endocytosis. The whole internalisation process of MrNvc VLPs into a Sf9 cell was recorded with live cell imaging. We have also identified a potential nuclear localisation signal (NLS) of MrNvc through deletion mutagenesis and verified by classical-NLS mapping. Overall, this study provides an insight into the journey of MrNvc VLPs in insect cells.

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Szyszka, Paul, Richard C. Gerkin, C. Giovanni Galizia, and Brian H. Smith. "High-speed odor transduction and pulse tracking by insect olfactory receptor neurons." Proceedings of the National Academy of Sciences 111, no. 47 (November 10, 2014): 16925–30. http://dx.doi.org/10.1073/pnas.1412051111.

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Guerra, Rodrigo da Silva, Hitoshi Aonuma, Koh Hosoda, and Minoru Asada. "Semi-automatic behavior analysis using robot/insect mixed society and video tracking." Journal of Neuroscience Methods 191, no. 1 (August 2010): 138–44. http://dx.doi.org/10.1016/j.jneumeth.2010.06.013.

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Johnson, Scott N., Derek B. Read, and Peter J. Gregory. "Tracking larval insect movement within soil using high resolution X-ray microtomography." Ecological Entomology 29, no. 1 (February 2004): 117–22. http://dx.doi.org/10.1111/j.0307-6946.2004.00567.x.

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Lushai, Gugs, and Hugh D. Loxdale. "Tracking movement in small insect pests, with special reference to aphid populations." International Journal of Pest Management 50, no. 4 (October 2004): 307–15. http://dx.doi.org/10.1080/09670870412331286049.

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Widenfalk, Olof, Christer Solbreck, and Hanna L. Bergeå. "Small-scale resource tracking in a population of a long-lived insect." Ecology and Evolution 2, no. 11 (September 24, 2012): 2659–68. http://dx.doi.org/10.1002/ece3.378.

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43

Couturier, Lydie, Juan Luna, Khalil Mazouni, Claire Mestdagh, Minh-Son Phan, Francis Corson, and Francois Schweisguth. "HaloTag-based reporters for sparse labeling and cell tracking." Fly 16, no. 1 (November 2, 2022): 360–66. http://dx.doi.org/10.1080/19336934.2022.2142460.

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Kohl, Kristina L., Lauren K. Harrell, Joseph F. Mudge, Seenivasan Subbiah, John Kasumba, Etem Osma, Apurba K. Barman, and Todd A. Anderson. "Tracking neonicotinoids following their use as cotton seed treatments." PeerJ 7 (April 19, 2019): e6805. http://dx.doi.org/10.7717/peerj.6805.

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Neonicotinoids are a leading class of insecticides on the global market, accounting for nearly 25%. They are widely used in both agricultural and residential settings. Causing neuron failure by irreversibly binding to the insect nicotinic acetylcholine receptor, neonicotinoids offer broad spectrum efficacy against a variety of pests. However, because they are non-selective with regard to insect species, there has been some concern with neonicotinoid use over threats to pollinators such as honeybees, and potential indirect effects to migratory waterfowl as a result of invertebrate prey population depletion. In order to study occurrence and fate of neonicotinoids (thiamethoxam and imidacloprid), we analyzed cotton leaves on plants grown from neonicotinoid-treated seeds and corresponding soil samples between cotton rows. Neonicotinoid concentration data from cotton leaves appears to be consistent with the claim that seed treatments protect plants for 3–4 weeks; by 30 days post-planting, neonicotinoid concentrations fell, in general, to 200 ng/g or lower. This represents about a 10-fold decrease from plant concentrations at approximately 2 weeks post-planting. It was found that neonicotinoids used as seed treatments remained present in the soil for months post planting and could be available for runoff. To that end, 21 playa wetlands were sampled; 10 had at least one quantifiable neonicotinoid present, three of which were classified as grassland or rangeland playas, two were urban, and the remaining five were cropland playas. In several instances, neonicotinoid concentrations in playas exceeded EPA chronic benchmarks for aquatic invertebrates.

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45

Mendes, Davide, Sofia Branco, Maria Rosa Paiva, Stefan Schütz, Eduardo P. Mateus, and Marco Gomes da Silva. "Unveiling Chemical Cues of Insect-Tree and Insect-Insect Interactions for the Eucalyptus Weevil and Its Egg Parasitoid by Multidimensional Gas Chromatographic Methods." Molecules 27, no. 13 (June 23, 2022): 4042. http://dx.doi.org/10.3390/molecules27134042.

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Multidimensional gas chromatography is, presently, an established and powerful analytical tool, due to higher resolving power than the classical 1D chromatographic approaches. Applied to multiple areas, it allows to isolate, detect and identify a larger number of compounds present in complex matrices, even in trace amounts. Research was conducted to determine which compounds, emitted by host plants of the eucalyptus weevil, Gonipterus platensis, might mediate host selection behavior. The identification of a pheromone blend of G. platensis is presented, revealing to be more attractive to weevils of both sexes, than the individual compounds. The volatile organic compounds (VOCs) were collected by headspace solid phase microextraction (HS-SPME), MonoTrapTM disks, and simultaneous distillation-extraction (SDE). Combining one dimensional (1D) and two-dimensional (2D) chromatographic systems—comprehensive and heart-cut two-dimensional gas chromatography (GC×GC and H/C-MD-GC, respectively) with mass spectrometry (MS) and electroantennographic (EAD) detection, enabled the selection and identification of pertinent semiochemicals which were detected by the insect antennal olfactory system. The behavioral effect of a selected blend of compounds was assessed in a two-arm olfactometer with ten parallel walking chambers, coupled to video tracking and data analysis software. An active blend, composed by cis and trans-verbenol, verbenene, myrtenol and trans-pinocarveol was achieved.

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Guo, Jianglong, Xiaowei Fu, Shengyuan Zhao, Xiujing Shen, Kris A. G. Wyckhuys, and Kongming Wu. "Long-term shifts in abundance of (migratory) crop-feeding and beneficial insect species in northeastern Asia." Journal of Pest Science 93, no. 2 (January 3, 2020): 583–94. http://dx.doi.org/10.1007/s10340-019-01191-9.

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AbstractVast numbers of insects annually engage in trans-latitudinal migration and thereby impact structure and functioning of natural and man-made ecosystems. In eastern Asia, long-distance migration has historically been studied for single insect species rather than diverse species complexes. Here, we assessed migration dynamics of multiple economically important migratory species on an island in the Bohai Strait, China. Drawing upon 15-year trapping records of > 2.5 million specimens, we unveil inter- and intra-annual shifts in the species composition and abundance of migrant individuals. Migrants belonged to 9 orders and 36 families, primarily consisting of Lepidoptera (79% individuals), Odonata (8%), and Coleoptera (4%). Seven crop-feeding noctuids, e.g., Helicoverpa armigera (Hübner), Mythimna separata (Walker), represented 54% of the total trapping records. Trap catches exhibited marked seasonal variation, with the highest capture rate during early fall. Yearly abundance of migratory noctuids was coupled with that of their associated natural enemies. Although overall trap catches did not decrease over the monitoring period, the entire order of Odonata experienced a 14.1% annual rate of decline. Furthermore, 19 out of 108 species exhibited a progressively declining abundance over time, including the cosmopolitan cutworm Agrotis ipsilon (Hufnagel) and the insectivorous dragonfly Pantala flavescens Fabricius. Our work provides unprecedented insights into insect migration dynamics in eastern Asia, helps fine-tune forecasting and early-warning systems of crop pests, and thereby guides integrated pest management within local agro-landscapes. Also, a long-term tracking of migrant insect populations can shine light on the fate of (insect-mediated) ecosystem services and trophic dynamic processes at a macroscale.

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Land, Michael F. "Visual tracking and pursuit: Humans and arthropods compared." Journal of Insect Physiology 38, no. 12 (December 1992): 939–51. http://dx.doi.org/10.1016/0022-1910(92)90002-u.

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Wright, Mark G., and Michael J. Samways. "Insect species richness tracking plant species richness in a diverse flora: gall-insects in the Cape Floristic Region, South Africa." Oecologia 115, no. 3 (July 3, 1998): 427–33. http://dx.doi.org/10.1007/s004420050537.

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49

Chirarattananon, Pakpong, Kevin Y. Ma, and Robert J. Wood. "Perching with a robotic insect using adaptive tracking control and iterative learning control." International Journal of Robotics Research 35, no. 10 (July 11, 2016): 1185–206. http://dx.doi.org/10.1177/0278364916632896.

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50

Edwards, John. "Insect Migration: Tracking Resources Through Space and Time.V. A. Drake , A. G. Gatehouse." Quarterly Review of Biology 72, no. 1 (March 1997): 82–83. http://dx.doi.org/10.1086/419696.

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