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552 results for “Honey”
Data and supplementary information: Effects of lithium on locomotor activity and circadian rhythm of honey bees
<p>Data and supplementary files for publication:</p><p>Erdem, B., Arslan, O.C., Sevin, S. Gozen, A. G., Agosto-Rivera, J. L., Tugrul, G., & Alemdar, H. (2023). Effects of lithium on locomotor activity and circadian rhythm of honey bees. <i>Scientific Reports</i>, <i>13,</i> 19861. https://doi.org/10.1038/s41598-023-46777-7</p><p> </p><p>AcuteExp_Dark_ActivityData.xlsx - Total LMA counts of acute experiment in dark condition.</p><p>AcuteExp_Light_ActivityData.xlsx - Total LMA counts of acute experiment in light condition.</p><p>ChronicExp_ActivityData.xlsx - Total LMA counts of the chronic experiment.</p><p>ChronicExp_MortalityData.xlsx - Mortality data of the chronic experiment.</p><p>ChronicExp_PeriodRhytmData.xlsx - Defines rhythmic and arrhythmic individuals and the circadian periods (h) of the rhythmic individuals in chronic experiment.</p><p>LD_doubleplots.pdf - Double-plotted actograms of the individuals in the chronic experiment in the 12 h light / 12 h dark condition.</p><p>DD_doubleplots.pdf - Double-plotted actograms of the individuals in the chronic experiment in the constant dark condition.</p><p>LL_doubleplots.pdf - Double-plotted actograms of the individuals in the chronic experiment in the constant light condition.<br>In the double-plotted actograms, NR indicates "non-rhythmic" individuals.</p>
Data for: Patch fidelity and patch preference of honey bees and bumble bees
<p>Animals commonly exhibit a tendency to return to previously visited locations. Such tendency is manifested at different scales, for example fidelity to a site, or fidelity to a specific patch within a site. Although patch fidelity has important implications for the pollinators and the plants they visit, our understanding of patch fidelity, and the extent to which it varies among bee species, remains limited. Here, we used a mark-reobservation approach to compare patch fidelity and patch size preference between one bumble bee and one honey bee species foraging on patches of <em>Medicago sativa</em> L. Honey bees exhibited greater patch fidelity (76%) than bumble bees (47%); they were more likely to return to the patch where they were marked. Patch size affected the level of patch fidelity for bumble bees but not for honey bees. Bumble bees were more likely to return to larger relative to smaller patches. In addition to patch fidelity, we detected preference of bees for the larger patches. Bees visited the larger patches more often than the smaller patches. These results add patch fidelity to the already known repertoire of differences in foraging strategies between a bumble bee and a honey bee species. It also indicates how the simultaneous study of distinct species in a similar environment can reveal important previously undetected information about their behavioral ecology. Observed differences in patch fidelity and patch size preferences may have important implications for crop pollination and conservation habitat design.</p>
Data for: Honey bees (Apis mellifera) modify plant-pollinator network structure, but do not alter wild species' interactions
<p>Honey bees (<em>Apis mellifera</em>) are widely used for honey production and crop pollination, raising concern for wild pollinators, as honey bees may compete with wild pollinators for floral resources. The first sign of competition, before changes appear in wild pollinator abundance or diversity, may be changes to wild pollinator interactions with plants. Such changes for a community can be measured by looking at changes to metrics of resource use overlap in plant-pollinator interaction networks. Studies of honey bee effects on plant-pollinator networks have usually not distinguished whether honey bees alter wild pollinator interactions, or if they merely alter total network structure by adding their own interactions. To test this question, we experimentally introduced honey bees to a Canadian grassland and measured plant-pollinator interactions at varying distances from the introduced hives. We found that honey bees increased the network metrics of pollinator and plant functional complementarity and decreased interaction evenness. However, in networks constructed from just wild pollinator interactions, honey bee abundance did not affect any of the metrics calculated. Thus, all network structural changes to the full network (including honey bee interactions) were due only to honey bee-plant interactions, and not to honey bees causing changes in wild pollinator-plant interactions. Given widespread and increasing use of honey bees, it is important to establish whether they affect wild pollinator communities. Our results suggest that honey bees did not alter wild pollinator foraging patterns in this system, even in a year that was drier than the 20-year average.</p>
Fore wings of honey bees (Apis mellifera) from Jammu and Kashmir, India
<p>The dataset consists of 350 honey bee (<i>Apis mellifera</i>) fore wing images, which represent 175 workers and 10 locations in Jammu and Kashmir, India. The wing images are compressed in IN-wing-images.zip. Raw coordinates of 19 landmarks marked on the wings are in file IN-raw-coordinates.csv. Additional data, including geographic coordinates and resolution, is saved in the file IN-data.csv.</p>
Data for: Russian honey bee genotype identification through enhanced marker panel set
<p>Russian honey bees (RHB) are a breeding population developed by USDA-ARS as an effort to provide Varroa-resistant honey bees to beekeepers. The selection strategy for this breeding population was the first in honey bees to incorporate genetic stock identification (GSI). The original GSI approach has been in use for over a decade, and though effective, novel technologies and analytical approaches recently developed provide an opportunity for improvement. Here we outline a novel genotyping assay that capitalizes on the markers used in the GSI as well as novel loci recently identified in a whole genome pooled study of commercial honey bee stocks. Our approach utilizes a microfluidic platform and machine learning analyses to arrive at an accurate, high throughput assay. This novel approach provides an improved tool that can be readily incorporated into breeding decisions towards healthier more productive bees.</p>
Annotated dataset of microscope images of pollen grains in honey from 17 beekeeping taxa
<p><strong>Annotated dataset of microscope images of pollen grains in honey from 17 beekeeping taxa</strong></p><p>Melissopalynology is a method based on the separation of pollen grains present in honey and the identification of the plant species to which they belong. It is used to determine the botanical, but also the geographical origin of the honey, as well as its commercial value. For this reason, a database including microscope images and characteristics of pollen grains of 17 beekeeping taxa, usually present in honey samples, was created. </p><p>For the honey preparations the methodology of Louveaux et al. (1978) and Von Der Ohe et al. (2004) was followed. Specifically, 5.0 g of honey were weighed and dissolved in 10 ml of distilled water. The solution was centrifuged for 10 min at 2300 r/min. The supernatant solution was discarded and the precipitate was transferred with a disposable plastic Pasteur pipette onto a slide, where it was spread with the addition of fuchsin on a 22 x 22 mm surface. Staining with fuchsin helps to see in greater detail the morphological characteristics of the pollen grains. The preparation was dried by gentle heating to 40°C, on a heating plate and covered with a coverslip on which a small amount of Entellan adhesive (Merck) has been placed. The pollen grains were photographed on an optical microscope (Olympus SZX12), with lens 40× (Olympus DF PLAPO 1X DF) and a digital analysis camera (Olympus SC30), while a morphometry software (Image Pro Plus Software, V1.1.19) was used for their determination. For the microscopic identification of the pollen types, the collection of reference slides from the Laboratory of Apiculture of the Aristotle University of Thessaloniki, which is accredited to ISO 17025:2017, was used. </p><p>The dataset contains 1404 training captured microscope images of pollen grains from 17 major beekeeping taxa (class list can be found below) and 85 testing captured images. Polygon annotations were created using LabelMe software and saved in COCO Annotation format (train.json and val.json files). </p><p>Further information about the related project (SmartBeeKeep) can be found in the following article and presentation (please site if you use these data):</p><ul><li>Vasilios Liolios, Dimitrios Kanelis, Maria-Anna Rodopoulou, Chrysoula Tananaki (2023). A Comparative Study of Methods Recording Beekeeping Flora. Forests, 14(8), 1677; <a href="https://doi.org/10.3390/f14081677">https://doi.org/10.3390/f14081677</a> </li><li>Nikos Grammalidis, Andreas Stergioulas, Aggelos Avramidis, Konstantinos Karystinakis, Athanasios Partozis, Athanasios Topaloudis, Georgia Kalantzi, Chrisoula Tananaki, Dimitrios Kanelis, Vasilis Liolios, and Madesis Panagiotis "A smart beekeeping platform based on remote sensing and artificial intelligence", Proc. SPIE 12786, Ninth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2023), 127860C (21 September 2023); <a href="https://doi.org/10.1117/12.2681866%20">https://doi.org/10.1117/12.2681866</a> Event: Ninth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2023), 2023, Ayia Napa, Cyprus <a href="https://smartbeekeep.eu/files/rscyp23_sbk_paper.pdf">Author preprint available</a></li></ul><p><strong>Annotation - Latin name</strong></p><p>Myrtus - Myrtus communis</p><p>Brassicaceae - Brassicaceae</p><p>Cercis - Cercis siliquastrum</p><p>Helianthus annuus - Helianthus annuus</p><p>Lavandula - Lavandula angustifolia</p><p>Robinia pseudacacia - Robinia pseudoacacia</p><p>Olea - Olea europaea</p><p>Citrus - Citrus sp.</p><p>Paliurus - Paliurus spina-christi</p><p>Eucalyptus - Eucalyptus sp.</p><p>Polygonum - Polygonum aviculare</p><p>Carduus - Silybum marianum</p><p>Cistus - Cistus sp.</p><p>thymus - Thymus sp.</p><p>Castanea - Castanea sativa</p><p>erica - Erica manipuliflora</p><p>Gossypium - Gossypium hirsutum</p><p> </p>
Apothecary vessel for diluted rose honey
ID no.: KGZ 5922 Museum: The Museum of Pharmacy at the Jagiellonian University Medical College in Kraków https://muzea.malopolska.pl/en/objects-list/2708 Digitalisation: RDW MIC, Virtual Małopolska project Source: Objaverse 1.0 / Sketchfab
Interest in the Use of Dressings With Honey for Wound Healing After Excision of Pilonidal Cyst
ClinicalTrials.gov study NCT02485860. IPD Sharing: Not stated. Countries: 1. Publications: 1.
The Use of Medical Grade Honey in the Prevention of Bone Anchored Hearing Aid Associated Skin Breakdown
ClinicalTrials.gov study NCT03929224. IPD Sharing: Not stated. Countries: 1. Publications: 6.
Evidence of exploitative competition between honey bees and native bees in two California landscapes
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Survey questionnaire and data of health management strategies of resilient honey bee stock throughout Southern California
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Data from: Pathogen shifts in a honey bee predator following arrival of the Varroa mite
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Data from: Honey bees (Apis mellifera) modify plant-pollinator network structure, but do not alter wild species’ interactions
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Data from: Drivers of viral prevalence in landscape-scale pollinator networks across Europe: Honey bee viral density, niche overlap with this reservoir host and network architecture
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The trisaccharide melezitose impacts honey bees and their intestinal microbiota
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Insecticide exposure alters flight-dependent gene-expression in honey bees, Apis mellifera
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Data for: Breeding honey bees (Apis mellifera L.) for low and high Varroa destructor population growth: gene expression of bees performing grooming behavior
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Negative effects of excessive heat on colony thermoregulation and population dynamics in honey bees
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Data from: Reduced density and visually complex apiaries reduce parasite load and promote honey production and overwintering survival in honey bees
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The weakest link: Haploid honey bees are more susceptible to neonicotinoid insecticides
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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.