Detection of small moving objects is an important research area with applications including monitoring of flying insects, studying their foraging behavior, using insect pollinators to monitor ...flowering and pollination of crops, surveillance of honeybee colonies, and tracking movement of honeybees. However, due to the lack of distinctive shape and textural details on small objects, direct application of modern object detection methods based on convolutional neural networks (CNNs) shows considerably lower performance. In this paper we propose a method for the detection of small moving objects in videos recorded using unmanned aerial vehicles equipped with standard video cameras. The main steps of the proposed method are video stabilization, background estimation and subtraction, frame segmentation using a CNN, and thresholding the segmented frame. However, for training a CNN it is required that a large labeled dataset is available. Manual labelling of small moving objects in videos is very difficult and time consuming, and such labeled datasets do not exist at the moment. To circumvent this problem, we propose training a CNN using synthetic videos generated by adding small blob-like objects to video sequences with real-world backgrounds. The experimental results on detection of flying honeybees show that by using a combination of classical computer vision techniques and CNNs, as well as synthetic training sets, the proposed approach overcomes the problems associated with direct application of CNNs to the given problem and achieves an average F1-score of 0.86 in tests on real-world videos.
Honeybee health and the species' gut microbiota are interconnected. Also noteworthy are the multiple niches present within hives, each with distinct microbiotas and all coexisting, which we termed ..."apibiome". External stressors (e.g. anthropization) can compromise microbial balance and bee resilience. We hypothesised that (1) the bacterial communities of hives located in areas with different degrees of anthropization differ in composition, and (2) due to interactions between the multiple microbiomes within the apibiome, changes in the community of a niche would impact the bacteria present in other hive sections. We characterised the bacterial consortia of different niches (bee gut, bee bread, hive entrance and internal hive air) of 43 hives from 3 different environments (agricultural, semi-natural and natural) through 16S rRNA amplicon sequencing. Agricultural samples presented lower community evenness, depletion of beneficial bacteria, and increased recruitment of stress related pathways (predicted via PICRUSt2). The taxonomic and functional composition of gut and hive entrance followed an environmental gradient. Arsenophonus emerged as a possible indicator of anthropization, gradually decreasing in abundance from agriculture to the natural environment in multiple niches. Importantly, after 16 days of exposure to a semi-natural landscape hives showed intermediate profiles, suggesting alleviation of microbial dysbiosis through reduction of anthropization.
Humanitarian demining is a worldwide effort and the range of climates and environments prevent any one detection method being suitable for all sites, so more tools are required for safe and efficient ...explosives sensing. Landmines emit a chemical flux over time, and honeybees can collect the trace residues of explosives (as particles or as vapour) on their body hairs. This capability was exploited using a passive method allowing the honeybees to freely forage in a mined area, where trace explosives present in the environment stuck to the honeybee body, which were subsequently transferred onto an adsorbent material for analysis by a fluorescent polymer sensor. Potential false positive sources were investigated, namely common bee pheromones, the anti-varroa pesticide Amitraz, and the environment around a clean apiary, and no significant response was found to any from the sensor. The mined site gave a substantial response in the optical sensor films, with quenching efficiencies of up to 38%. A model was adapted to estimate the mass of explosives returned to the colony, which may be useful for estimating the number of mines in a given area.
•Collection and detection of trace explosives is challenging in real-world environments.•Honeybees are used to passively collect explosives on body hair via free-flying.•Returning to the colony, the bees deposit explosives onto a sorbing preconcentrator for analysis by optical sensor.•Several potential distractant chemicals are tested and found not to give false positives.•A model has been developed to estimate the amount of explosive returned to the colony by the foraging bees.
Agrochemicals and biocides are suspected to cause a dysbiosis of honey bee microbiota, decreasing colonies ability to respond to the environment. As a first step to investigate agriculture and ...beekeeping impact, hives bacteriomes from an anthropized environment (Agri-env) were compared to that of pristine’s (Prist-env). 16S rRNA sequencing evidenced differences in richness and composition between sample types (Gut (G), Brood (B), Bee-bread (BB)) and environments. Higher opportunist loads and shifts toward taxa capable of metabolizing insecticides were observed in G and B at Agri-env, while beneficial bacteria were enriched in Prist-env. Bacteria in BB did not differ, the acidity of the niche outweighing the influence of external factors. Results showed the environment plays a major role in shaping honey bee microbiota, the agricultural realm inducing a bacterial disruption that would let to colonies vulnerability. In contrast, a less susceptible bee will be promoted in less anthropized locations.
Legacy landmines in post-conflict areas are a non-discriminatory lethal hazard and can still be triggered decades after the conflict has ended. Efforts to detect these explosive devices are ...expensive, time-consuming, and dangerous to humans and animals involved. While methods such as metal detectors and sniffer dogs have successfully been used in humanitarian demining, more tools are required for both site surveying and accurate mine detection. Honeybees have emerged in recent years as efficient bioaccumulation and biomonitoring animals. The system reported here uses two complementary landmine detection methods: passive sampling and active search. Passive sampling aims to confirm the presence of explosive materials in a mine-suspected area by the analysis of explosive material brought back to the colony on honeybee bodies returning from foraging trips. Analysis is performed by light-emitting chemical sensors detecting explosives thermally desorbed from a preconcentrator strip. The active search is intended to be able to pinpoint the place where individual landmines are most likely to be present. Used together, both methods are anticipated to be useful in an end-to-end process for area surveying, suspected hazardous area reduction, and post-clearing internal and external quality control in humanitarian demining.
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•Honeybees and organic semiconductor films can indicate explosive contamination.•Conditioned honeybees can subsequently be used to locate explosive plumes.•Reconditioning prolonged interest of honeybees for target odour.•Camera-equipped UAVs can remotely track the honeybee trajectory.•Computer vision algorithms can detect landmines by analyzing honeybee movements in video.
The survival and performance of 597 honey bee colonies, representing five subspecies and 16 different genotypes, were comparatively studied in 20 apiaries across Europe. Started in October 2009, ...15.7% of the colonies survived without any therapeutic treatment against diseases until spring 2012. The survival duration was strongly affected by environmental factors (apiary effects) and, to a lesser degree, by the genotypes and origin of queens. Varroa was identified as a main cause of losses (38.4%), followed by queen problems (16.9%) and Nosema infection (7.3%). On average, colonies with queens from local origin survived 83 days longer compared to non-local origins (p < 0.001). This result demonstrates strong genotype by environment interactions. Consequently, the conservation of bee diversity and the support of local breeding activities must be prioritised in order to prevent colony losses, to optimize a sustainable productivity and to enable a continuous adaptation to environmental changes.
Diseases are known to be one of the major contributors to colony losses. Within a Europe-wide experiment on genotype-environment interactions, an initial 621 colonies were set up and maintained from ...2009 to 2012. The colonies were monitored to investigate the occurrence and levels of key pathogens. These included the mite Varroa destructor (mites per 10 g bees), Nosema spp. (spore loads and species determination), and viruses (presence/absence of acute bee paralysis virus (ABPV) and deformed wing virus (DWV)). Data from 2010 to the spring of 2011 are analysed in relation to the parameters: genotype, environment, and origin (local vs. non-local) of the colonies in the experiment. The relative importance of different pathogens as indicators of colony death within the experiment is compared. In addition, pathogen occurrence rates across the geographic locations are described.
Here, scientists from 19 European countries, most of them collaborating in Working Group 4: "Diversity and Vitality" of COST Action FA 0803 "Prevention of honey bee COlony LOSSes" (COLOSS), review ...the methodology applied in each country for discriminating between honey bee populations. Morphometric analyses (classical and geometric) and different molecular markers have been applied. Even if the approach has been similar, however, different methodologies regarding measurements, landmarks or molecular markers may have been used, as well as different statistical procedures. There is therefore the necessity to establish common methods in all countries in order to have results that can be directly compared. This is one of the goals of WG4 of the COLOSS project.
Honey bee workers were sampled across the Serbian territory during 2009-2010 from mostly non-migratory apiaries to determine the population structure of these bees using morphometric, genetic, and ...spatial information. A total of 134 bees were sampled, of which 77 were analysed using classical wing morphometrics and 122 bees were successfully analysed using 24 DNA microsatellite markers. A combination of methods including multivariate statistics and assignment tests (frequency-based and Bayesian) revealed the honey bees of this region to resemble the subspecies Apis mellifera macedonica, Apis mellifera carnica or hybrids of these two subspecies. Based on Bayesian assignment ('Structure') and spatial PCA, honey bees within the Serbian territory were composed of 56%-58% A. m. carnica and 42%-44% A. m. macedonica. Spatial analysis showed the existence of a north-west to south-east cline in genetic differentiation. The bees in the north-west resemble A. m. carnica,while the bees in the south-east of the country are more similar to A. m. macedonica. Thus, the extent of A. m. macedonica within Serbia was greater than previously estimated. We define a line of hybridisation between A. m. carnica and A. m. macedonica within our study area. The cline of differentiation was still evident using a combination of genetic and spatial information, in spite of beekeeping activities including transhumance and breeding efforts.
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