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552 results for “Honey”
Trophallaxis interactions of three honey bee colonies
<p>This dataset consists of the trophallaxis interactions analyzed in [TODO]. Please see its README.txt file for a detailed description of the data, and the paper for information about how the data was generated. </p> <p>Academic papers should cite the aforementioned publication. Otherwise, please cite this Zenodo record. </p>
Strength-mass scaling law governs mass distribution inside honey bee swarms
<p>To survive during colony reproduction, bees create dense clusters of thousands of suspended individuals. How does this swarm, which is orders of magnitude larger than the size of an individual, maintain mechanical stability? We hypothesize that the internal structure in the bulk of the swarm, about which there is little prior information, plays a key role in mechanical stability. Here, we provide the first-ever 3D reconstructions of the positions of the bees in the bulk of the swarm using x-ray computed tomography. We find that the mass of bees in a layer decreases with distance from the attachment surface. By quantifying the distribution of bees within swarms varying in size (made up of 4000–10,000 bees), we find that the same power law governs the smallest and largest swarms, with the weight supported by each layer scaling with the mass of each layer to the ≈1.5 power. This arrangement ensures that each layer exerts the same fraction of its total strength, and on average a bee supports a lower weight than its maximum grip strength. This illustrates the extension of the scaling law relating weight to strength of single organisms to the weight distribution within a superorganism made up of thousands of individuals.</p>
Economics Analysis of Small and Large Farm Size Honey Bee Sub-Sector in Chitwan District, Nepal
<p>This is an SPSS file that can be used for calculating various descriptive statistics and performing statistical tests such as t-tests and chi-square tests. Ranking of scale can also be carried out from these datasets.</p>
Collection of wing images for conservation of honey bees (Apis mellifera) biodiversity in Europe
<p>Identification of honey bee (<em>Apis mellifera</em>) from various parts of the world is essential for protection of their biodiversity. The identification can be based on wing measurements which is inexpensive and easy available. In order to develop such identification there are required reference samples from various parts or the world.</p> <p>We provide collection of 26481 honey bee fore wing images from 13 countries in Europe: Austria (AT), Croatia (HR), Greece (GR), Moldova (MD), Montenegro (ME), Poland (PL), Portugal (PT), Romania (RO), Serbia (RS), Slovenia (SI), Spain (ES), Turkey (TR). For each country there are three files starting with the two letter country code (indicated earlier in the parentheses): XX-wing-images.zip, XX-raw-coordinates.csv and XX-data.csv, which contain wing images, raw landmark coordinates and geographic coordinates, respectively. Files with prefix EU contain combined data from all countries.</p> <p>The resolution of the wing images was provided in pixels per meter. If the resolution was not provided it is not known. In those cases only wing shape and not wing size can be analyzed. </p> <p>For analysis of the dataset see:</p> <p>Oleksa, A., Căuia, E., Siceanu, A., Puškadija, Z., Kovačić, M., Pinto, M. A., Rodrigues, P. J., Hatjina, F., Charistos, L., Bouga, M., Prešern, J., Kandemir, İ., Rašić, S., Kusza, S., Tofilski, A. (2023). Honey bee (<em>Apis mellifera</em>) wing images: a tool for identification and conservation. GigaScience, 12, giad019. <a href="https://doi.org/10.1093/gigascience/giad019">https://doi.org/10.1093/gigascience/giad019</a></p> <p>Oleksa, A., Căuia, E., Siceanu, A., Puškadija, Z., Kovačić, M., Pinto, M. A., Rodrigues, P. J., Hatjina, F., Charistos, L., Bouga, M., Prešern, J., Kandemir, I., Rašić, S., Kusza, S., Tofilski, A. (2023). Apis-wings-EU. WorkflowHub. <a href="https://doi.org/10.48546/WORKFLOWHUB.WORKFLOW.422.1">https://doi.org/10.48546/WORKFLOWHUB.WORKFLOW.422.1</a></p>
Pigment-Dispersing Factor expressing neurons provide an infrastructure for conveying circadian information in the honey bee brain
<p>A movie of a 360° view of the 3D-reconstructed PDF (Pigment Dispersing Factor) network in the honey bee brain. (avi file to be opened with for example Fiji ImageJ)</p>
Biting behavior against Varroa mites in honey bees is associated with changes in mandibles
<p>raw data of the mite biting behavior, and parameters of mandibles for our manuscript "<span>Biting behavior against Varroa mites in honey bees is associated with changes in mandibles, with tracking by a new mobile application for mite damage identification</span>"</p>
Identification data for discrimination between honey bee (Apis mellifera) lineages
<p><span>The data in dw.xml file can be used for discriminate between 4 lineages of honey bee </span><em>Apis mellifera</em><span>: A, C, M, O. </span></p> <p>The discrimination is based on 19 landmarks of a forewing. The data were obtained from:</p> <p>Nawrocka, A., Kandemir, İ., Fuchs, S., & Tofilski, A. (2018). Computer software for identification of honey bee subspecies and evolutionary lineages. Apidologie, 49(2), 172-184. <a href="https://doi.org/10.1007/s13592-017-0538-y" rel="noopener">https://doi.org/10.1007/s13592-017-0538-y</a></p> <p>The dw.xml file can be used in <a href="http://drawwing.org/identifly" target="_blank" rel="noopener">IdentiFly</a> software or in R package <a href="https://github.com/DrawWing/IdentiFlyR" target="_blank" rel="noopener">IdentiFlyR</a> https://github.com/DrawWing/IdentiFlyR. </p> <p><span> </span></p>
Identification data for discrimination between regions in lineage C of honey bee (Apis mellifera)
<p>The data in dw.xml file can be used for discriminate between 5 regions in lineage C of honey bee <em>Apis mellifera</em>: Greece, Croatia and Slovenia, Italy, Romania and Moldova and European part of Turkey. </p> <p>The discrimination is based on 19 landmarks of a forewing. The data were obtained from:</p> <p>Oleksa, A., Căuia, E., Siceanu, A., Puškadija, Z., Kovačić, M., Pinto, M. A., Rodrigues, P. J., Hatjina, F., Charistos, L., Bouga, M., Prešern, J., Kandemir, İ., Rašić, S., Kusza, S., Tofilski, A. (2023). Honey bee (<em>Apis mellifera</em>) wing images: a tool for identification and conservation. GigaScience, 12, giad019. <a href="https://doi.org/10.1093/gigascience/giad019" target="_blank" rel="noopener">https://doi.org/10.1093/gigascience/giad019</a></p> <p>The dw.xml file can be used in <a href="http://drawwing.org/identifly" target="_blank" rel="noopener">IdentiFly</a> or in R package <a href="https://github.com/DrawWing/IdentiFlyR" target="_blank" rel="noopener">IdentiFlyR</a>. </p>
Data from: Evaluating the strength of western honey bees (Apis mellifera L.) colonies fed pollen subsitutes over winter
<p>We fed managed honey bee colonies one of two commercially available pollen substitutes (MegaBee, AP23) or no diet over late fall and winter in Florida, U.S.A. We measured the change in mass of adult bees, brood, and full colonies after nine weeks of feeding. We also measured the average mass per pupa, amount of pollen substitute patty consumed, the average total mass of natural pollen collected, and the proportion of pollen foragers.</p>
Colony fitness increases in the honey bee at queen mating frequencies higher than genetic diversity asymptote
Abstract Across the eusocial Hymenoptera, a queen's mating frequency is positively associated with her workers' genetic diversity and colony's fitness. Over 90% of a colony's diversity potential is achieved by its mother's tenth effective mating (me); however, many females mate at levels of me > 10, a zone we here call hyperpolyandry. We compared honey bee colony fitness at mating levels near and above this genetic diversity asymptote. We were interested in how hyperpolyandry affects colony phenotypes arising from both common tasks (brood care) and rare specialized tasks (parasite resistance). We used an unselected wild line of bees and a Varroa Sensitive Hygiene (VSH) line selected to resist the parasite Varroa destructor. Virgin queens were instrumentally inseminated to replicate the following queen/colony conditions: (1) VSH semen/low polyandry (observed mating number = mo = 9), (2) VSH semen/high polyandry (mo = 54), (3) wild type semen/low polyandry, or (4) wild semen/high polyandry. There was a positive effect of polyandry on brood survival, an outcome of common tasks, with highest values at mo = 54. There was an interaction between polyandry and genetics such that differences between genetic lines expressed only at mo = 54, with fewer mites in VSH colonies. These results are consistent with two hypotheses for the evolution of mating levels in excess of the genetic diversity asymptote: hyperpolyandry improves colony fitness by (1) optimizing genotype compositions for common tasks and (2) by capturing rare specialist allele combinations, resisting cliff-edge ecological catastrophes. Significance statement Polyandry is a female's practice of mating with several males, storing their sperm, and using it to produce one or more clutches of genetically diverse offspring. In the social Hymenoptera, polyandry increases the genetic diversity and task efficiency of workers, leading to improved colony fitness. Over 90% of the increase in a colony's diversity potential is achieved by its mother's tenth mating; however, many females practice hyperpolyandry, a term we reserve here for mating levels above this genetic diversity asymptote. We show that a token of colony fitness arising from common tasks, brood survival, improves universally as one moves from sub- to hyperpolyandrous mating levels. However, a colony phenotype arising from a rare parasite resistance task is only expressed in the presence of the controlling alleles and under conditions of hyperpolyandry. These results suggest adaptive mechanisms by which hyperpolyandry could evolve.
Misinformation, internet honey trading, and beekeepers drive a plant invasion
<p>Biological invasions are a major human induced global change that is threatening global biodiversity by homogenizing the world's fauna and flora. Species spread because humans have moved species across geographic boundaries and have changed ecological factors that structure ecosystems, such as nitrogen deposition, disturbance, etc. Many biological invasions are caused accidentally, as a byproduct of human travel and commerce driven product shipping. However, humans also have spread many species intentionally because of perceived benefits. Of interest is the role of the recent exponential growth in information exchange via internet social media in driving biological invasions. To date, this has not been examined. Here we show that for one such invasive species, goldenrod, social networks spread misleading and incomplete information that is enhancing the spread of goldenrod invasions into new environments. We show that the notion of goldenrod honey as a "superfood" with unsupported healing properties is driving a demand that leads beekeepers to produce goldenrod honey. Social networks provide a forum for such information exchange and this is leading to further spread of goldenrod in many countries where goldenrod is not native, such as Poland. However, this informal social information exchange ignores laws that focus on preventing the further spread of invasive species and the strong negative effects that goldenrod has on native ecosystems, including floral resources that negatively impact honeybee performance. Thus, scientifically unsupported information on "superfoods" such as goldenrod honey that is disseminated through social internet networks has real world consequences such as increased goldenrod invasions into novel geographical regions which decreases native biodiversity.</p>
Playbacks of Asian honey bee stop signals demonstrate referential inhibitory communication
<p>Referential communication provides a sophisticated way in which animals can communicate information about their environment. Previously, research demonstrated that honey bee stop signals encode predator danger in their fundamental frequency and danger context in their duration. Here, we show that these signals also encode danger in their vibrational amplitude. Stop signals elicited by the more dangerous predator, the large hornet (<em>Vespa</em><em>mandarinia</em>) had significantly 1.5-fold higher vibrational amplitudes than those elicited by the small hornet predator (<em>Vespa</em><em>velutina</em>). We measured the freezing vibrational response thresholds, and show that these natural signals exceed response thresholds. Finally, with artificial playbacks of the vibratory stop signal, we demonstrate that these signals referentially encode the danger that foragers experience at food source. Stop signals elicited by the larger and significantly more dangerous predator (<em>V.</em><em>mandarinia</em>) were significantly 1.4-fold more inhibitory than stop signals elicited by the smaller and less dangerous predator (<em>V.</em><em>velutina</em>). This dataset contains all of the data used for the statistical analyses reported in this paper and to generate the figures.</p>
Data from: Agroecological measures in meadows promote honey bee colony development and winter survival
<p><span>The homogenization of agricultural landscapes has led to a decrease in pollinator diversity and abundance. In response to this decline, farmers have implemented agroecological measures, which, in meadows, aim at providing more floral resources. These measures are the availability of unmown floral strips, delayed mowing, and discouraging the use of the conditioner, a device known to harm insects. The aim of our study was to investigate the cascade of effects of these agroecological measures on honey bee colony development and winter survival. We (i) determined the effect of these measures on colony size during the nectar and pollen collecting season in spring and summer, (ii) evaluated the effect of spring and summer colony sizes on autumn size, and (iii) described the effect of colony size in autumn on winter mortality. In this study, 300 honey bee colonies were monitored over three years </span><span>in three cantons of Switzerland. Colony size was defined by the number of brood cells and adult workers, Honey bee colony size in summer and autumn were improved by agroecological measures on meadows and likely contributed to the increased overwintering success.</span> <span>This study is a first step towards the targeted identification of viable agroecological measures on temporary meadows that can be implemented to promote honey bee colonies' health in the agricultural landscape.</span></p>
Multisite imaging of neural activity using a genetically encoded calcium sensor in the honey bee
<p><span>Understanding of the neural bases for complex behaviors in Hymenoptera insect species has been limited by a lack of tools that allow measuring neuronal activity simultaneously in different brain regions. </span><span>Here, we developed the first pan-neuronal genetic driver in a Hymenopteran model organism, the honey bee, and expressed the calcium indicator GCaMP6f under the control of the honey bee <em>synapsin</em> promoter. We show that GCaMP6f is widely expressed in the honey bee brain, allowing it to record neural activity from multiple brain regions. </span><span>To assess the power of this tool, we focused on the olfactory system, recording simultaneous responses from the antennal lobe, and from the more poorly investigated lateral horn and mushroom body calyces. Neural responses to 16 distinct odorants demonstrate that odorant quality (chemical structure) and quantity are faithfully encoded in the honey bee antennal lobe. In contrast, odor coding in the lateral horn departs from this simple physico-chemical coding, supporting the role of this structure in coding the biological value of odorants. We further demonstrate robust neural responses to several bee pheromone odorants, key drivers of social behavior, in the lateral horn. Combined, these brain recordings represent the first use of a neurogenetic tool for recording large-scale neural activity in a eusocial insect, and will be of utility in assessing the neural underpinnings of olfactory and other sensory modalities and of social behaviors and cognitive abilities.</span></p>
EFSA Opinion on Grayanotoxins in certain honey - Plant list of Ericaceae species
<p>Plant list of Ericaceae species that have been investigated for grayanane content or that have been listed for ethnopharmacological use</p>
Data for: Breeding honey bees (Apis mellifera L.) for low and high Varroa destructor population growth: gene expression of bees performing grooming behavior
<p class="MsoNormal"><strong><span>Background</span></strong></p> <p class="MsoNormal">Social organisms, including honey bees (<em>Apis mellifera</em> L.), have defense mechanisms to control the multiplication and transmission of parasites and pathogens within their colonies. Self-grooming, a mechanism of behavioral immunity, seems to contribute to restraining the population growth of the ectoparasitic mite <em>Varroa destructor</em> in honey bee colonies. Because <em>V. destructor</em> is the most damaging parasite of honey bees, breeding them for resistance against the mite is a high priority of the beekeeping industry. We conducted a bidirectional breeding program to select honey bee colonies with low and high varroa<em> </em>population growth (LVG and HVG, respectively). Having high and low lines of bees allowed the study of genetic mechanisms underlying self-grooming behavior between the extreme genotypes. Worker bees were classified into two categories: 'light groomers' and 'intense groomers'. The brains of bees from the different categories (LVG-intense, LVG-light, HVG-intense, and HVG-light) were used for gene expression and viral quantification analyses.</p> <p class="MsoNormal"><strong><span>Results</span></strong></p> <p class="MsoNormal">Differentially expressed genes (DEGs) associated with the LVG and HVG lines were identified, including four odorant-binding proteins and a gustatory receptor. A functional enrichment analysis showed 19 enriched pathways from a list of 219 down-regulated DEGs in HVG bees, including the Kyoto Encyclopedia of Genes and Genomes (KEGG) term of oxidative phosphorylation. Additionally, bees from the HVG line showed higher levels of <em>Apis rhabdovirus</em> <em>1</em> and <em>2</em>, <em>Varroa destructor virus -1</em> (VDV-1), and <em>Deformed wing virus-A</em> (DWV-A) compared to bees of the LVG line.</p> <p class="MsoNormal"><strong><span>Conclusions</span></strong></p> <p class="MsoNormal">The difference in expression of odorant-binding protein genes and a gustatory receptor between bee lines suggests a possible link between them and the perception of irritants to trigger rapid self-grooming instances that require the activation of energy metabolic pathways. Therefore, our results provide new insights into the molecular mechanisms involved in honey bee grooming behavior. Differences in viral levels in the brains of LVG and HVG bees showed the importance of investigating the pathogenicity and potential impacts of neurotropic viruses on behavioral immunity. The results of this study advance the understanding of a trait used for selective breeding, self-grooming, and the potential of using genomic-assisted selection to improve breeding programs.</p>
Honey Particle Detection Dataset
<p>A synthetically generated dataset of honey samples observed by a digital microscope. The goal of this dataset is to train machine learning models to detect the pollen found in the images. This dataset contains 500 images with three different classes of particles commonly found in honey.</p> <p>The annotations are provided in YOLO format in a different directory. Each annotation is associated with the image by an unique ID. The images follow the naming convention "image_{ID}.png" and the annotations follow the convention "image_{ID}.txt".</p> <p>This dataset has been created by Sonicat Systems and is published under Creative Commons Attribution Non-Commercial Share Alike license.</p> <p> </p>
Data for: Negative but antagonistic effects of neonicotinoid insecticides and ectoparasitic mites Varroa destructor on Apis mellifera honey bee food glands
<p>Collaborative brood care by workers is essential for the functionality of eusocial honey bee, <em>Apis</em> <em>mellifera</em>, colonies. The hypopharyngeal food glands of workers play a crucial role in this context. Even though there is consensus that ubiquitous ectoparasitic mites <em>Varroa</em> <em>destructor</em> and widespread insecticides, such as neonicotinoids, are major stressors for honey bee health, their impact alone and in combination on the feeding glands of workers is poorly understood. Here, we show that both <em>V. destructor</em> and neonicotinoids reduce hypopharyngeal gland size, thereby potentially compromising collaborative brood care in colonies. In a fully-crossed laboratory experiment, the impact of mites and the neonicotinoids thiamethoxam and clothianidin alone and in combination on workers were evaluated. While the neonicotinoids did not impact survival and emergence body mass, the data confirm that <em>V. destructor</em> reduces both. Even though the interactions between both stressors were antagonistic and neutral, the clear detrimental effects of both stressors alone and in combination on worker longevity and food glands are remarkable. Besides reduced worker longevity, impaired brood care provided by workers exposed to <em>V. destructor</em> and neonicotinoids could be detrimental for honey bee colony functionality. Our findings highlight a mechanism to explain honey bee colonies losses globally.</p>
Does pre-sorting by colour using visible and high-energy violet light improve the detection of plant species in honey bee pollen baskets?
<div class="article-section__content en main"> Premise <p>Pollen collected by honey bees from different plant species often differs in color, and this has been used as a basis for plant identification. The objective of this study was to develop a new, low-cost protocol to sort pollen pellets by color using high-energy violet light and visible light to determine whether pollen pellet color is associated with variations in plant species identity.</p> Methods and Results <p>We identified 35 distinct colors and found that 52% of pollen subsamples (<em>n</em> = 200) were dominated by a single taxon. Among these near-pure pellets, only one color consistently represented a single pollen taxon (Asteraceae: Cichorioideae). Across the spectrum of colors spanning yellows, oranges, and browns, similarly colored pollen pellets contained pollen from multiple plant families ranging from two to 13 families per color.</p> Conclusions <p>Sorting pollen pellets illuminated under high-energy violet light lit from four directions within a custom-made light box aided in distinguishing pellet composition, especially in pellets within the same color.</p> </div>
Sensitivity of different grass functional groups to honey mesquite
<p>Quantifying the relationship of different grass functional groups to increasing woody plant cover is necessary to better understand the effects of woody plant encroachment on grasslands. This study explored biomass production responses of three perennial grass groups based on photosynthetic pathway and potential canopy height (C<sub>4</sub> short-grasses, C<sub>3</sub> mid-grasses and C<sub>4</sub> mid-grasses) to different percent canopy covers of the surrounding deciduous woody legume, honey mesquite (<em>Prosopis</em> <em>glandulosa</em>). Two methods were used to determine mesquite canopy cover, line-intercept and geospatial analysis of aerial images, and both were used to predict production of the 3 grass groups. Five years of grass production data were included in the mesquite cover/grass production regressions. Two years had extreme grass production responses, one due to drought and the other to high rainfall. Of the 3 remaining years, best-fit curves were negative linear for C<sub>4</sub> short-grasses and C<sub>3</sub> mid-grasses, and negative sigmoidal for C<sub>4</sub> mid-grasses using both cover determination methods, although slopes of the curves differed between cover determination methods. C<sub>4</sub> mid-grasses were more sensitive than the other grass groups to increasing mesquite cover. Loss of production potential when mesquite cover increased from 0–35% was 75.5, 28.7 and 23.2% for C<sub>4</sub> mid-grasses, C<sub>3</sub> mid-grasses and C<sub>4</sub> short-grasses, respectively. Moreover, production potential of C<sub>4</sub> mid-grasses under no mesquite cover was 3 and 6 times greater than C<sub>3</sub> mid-grasses or C<sub>4</sub> short-grasses, respectively. Spatial settings of the different grass groups in relation to mesquite tree size and size of intercanopy areas provided indirect evidence that the process of mesquite encroachment in the last 50 to 100 years may have negatively impacted C<sub>4</sub> mid-grasses more than the other grass groups. Results suggest that gains in grass production following mesquite treatment would be limited if the system has degraded to where only C<sub>3</sub> mid-grasses and C<sub>4</sub> short-grasses dominate.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.