Skip to main content
Powered by ShareScore

Find research datasets worth reusing

Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.

28

datasets available to search

ShareScore release 0.9.0

Reset

Dataset results

28 results for “sticky traps”

Learn how ShareScore rates datasets ↗
edi48/100

Luquillo Understory invertebrates Sticky Trap Samples

Sticky traps, designed to resemble resin globules that eventually could become amber, were coated with adhesive and placed on lower tree boles or on logs at one non-gap site at the LEF for 5 days during June 2004, January and July 2005, July 2006 and July 2007 (total 35 samples). Samples were dominated by Diptera (89% of specimens), with phorids representing 60%, mycetophilids 16%, dolichopodids 4%, sarcophagids 2%, cecidomyiids and chironomids 1% each, and other Diptera 5%. Other collected taxa included Hymenoptera (6% of specimens), with chalcidoid wasps 4%, little fire ant (Wasmania auropunctata) 1% and other Hymenoptera 1%; Coleoptera (2% of specimens), with curculionids 1% and other Coleoptera 1%; and a variety of other insects, spiders and mites representing 3%. Two small Anolis lizards and a small Eleutherodactylus frog also were captured. Arthropod composition in sticky traps from the LEF and in Dominican amber were similar. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.

openCC (other)May 2023View details →
zenodo44/100

Pest Sticky Traps: a dataset for Whitefly Pest Population Density Estimation in Chromotropic Sticky Traps

<p><strong>The dataset<br></strong></p> <p>The Pest Sticky Traps (PST) dataset is a collection of yellow chromotropic sticky trap pictures specifically designed for training/testing deep learning models to automatically count insects and estimate pest populations.</p> <p>Images were manually annotated by some experts of the Department of Agriculture, Food and Environment of the University of Pisa (Italy) by putting a dot over the centroids of each identified insect. Specifically, we labeled insects as belonging to the category &ldquo;whitefly&rdquo; considering two different species, i.e., the sweet potato whitefly (<em>Bemisia tabaci</em>) (Gennadius) and the greenhouse whitefly (<em>Trialeurodes vaporariorum</em>) (Westwood).</p> <p>The dataset comprises two subsets:<br>- a subset we suggest using for the training/validation phases (contained in the `train/` folder)<br>- a subset we suggest using for the test phase (contained in the `test/` folder)</p> <p>Annotations of the two subsets are contained in `train/annotations.csv` and `test/annotations.csv`, respectively. They have the following columns:<br>- *imageName* - filename of the image containing the whiteflies,<br>- *X,Y* - 2D coordinates of the whitefly in the image space,<br>- *class* - class index of the insect (always 0 in this dataset).</p> <p>&nbsp;</p> <p><strong>Citing our work</strong></p> <p>If you found this dataset useful, please cite the following paper</p> <blockquote> <pre>@inproceedings{CIAMPI2023102384,<br> title = {A deep learning-based pipeline for whitefly pest abundance estimation on chromotropic sticky traps},<br> &nbsp; &nbsp;journal = {Ecological Informatics},<br> volume = {78},<br> pages = {102384},<br> year = {2023},<br> issn = {1574-9541}, &nbsp; &nbsp; doi = {10.1016/j.ecoinf.2023.102384}, &nbsp; url = {https://www.sciencedirect.com/science/article/pii/S1574954123004132}, &nbsp; year = 2023, &nbsp; &nbsp; author = {Luca Ciampi and Valeria Zeni and Luca Incrocci and Angelo Canale and Giovanni Benelli and Fabrizio Falchi and Giuseppe Amato and Stefano Chessa}, } </pre> </blockquote> <p>and this Zenodo Dataset</p> <blockquote> <pre>@dataset{ciampi_2023_7801239, &nbsp; &nbsp; author = {Luca Ciampi and Valeria Zeni and Luca Incrocci and Angelo Canale and Giovanni Benelli and Fabrizio Falchi and Giuseppe Amato and Stefano Chessa}, &nbsp; &nbsp; title = {Pest Sticky Traps: a dataset for Whitefly Pest Population Density Estimation in Chromotropic Sticky Traps}}, &nbsp; month = apr, &nbsp; year = 2023, &nbsp; publisher = {Zenodo}, &nbsp; version = {1.0.0}, &nbsp; doi = {10.5281/zenodo.7801239}, &nbsp; url = {<a href="https://doi.org/10.5281/zenodo.7801239">https://doi.org/10.5281/zenodo.6560823</a>} } </pre> </blockquote> <p>&nbsp;</p> <p><strong>Contact Information</strong></p> <p>If you would like further information about the dataset or if you experience any issues downloading files, please contact us at <a href="mailto:mobdrone@isti.cnr.it">luca.ciampi@isti.cnr.it</a></p> <p>&nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Apr 2023View details →
zenodo40/100

Fig. 1. Sticky trap applied for catching Elaeidobius kamerunicus, pollinating weevils. The trap was 21.7 in Pollination activity of Elaeidobius kamerunicus (Coleoptera: Curculionoidea) on oil palm on Hainan island

Fig. 1. Sticky trap applied for catching Elaeidobius kamerunicus, pollinating weevils. The trap was 21.7 cm in diameter and 26.3 cm in height. It was folded into a cylinder surrounding an Elaeis guineensis inflorescence with the sticky gel–coated surface on the outside.

opencc-by-4.0Jun 2015View details →
zenodo40/100

Fig. 1 in Comparison of parasitoid retention on yellow sticky card traps

Fig. 1. Percentage of parasitoid escape afer 72 h on Alpha Scents folding yellow card traps and Pherocon AM no-bait traps.

opencc-by-4.0Jun 2022View details →
zenodo40/100

Fig. 2 in Comparison of parasitoid retention on yellow sticky card traps

Fig. 2. Yellow sticky card containing pushpins marking the location of captured parasitoid wasps. Pushpins were placed approximately 2 to 3 mm from each captured wasp and their movement on the sticky card can be observed with the wasp's varying distance from pushpins.

opencc-by-4.0Jun 2022View details →
zenodo40/100

Fig. 1 in Attraction of thrips (Thysanoptera) to colored sticky traps in a Florida olive grove

Fig. 1. Diagrammatic representation of the olive grove with sampling plots and locations of trap series within each plot. Location of individual traps is represented by an X.

opencc-by-4.0Mar 2018View details →
zenodo40/100

Fig. 6 in Attraction of thrips (Thysanoptera) to colored sticky traps in a Florida olive grove

Fig. 6. Total thrips collected from sticky cards at each sampling station during olive bloom. For analysis, sampling positions within the dotted line were considered to be interior, whereas those on the outside were considered to be outer sites.

opencc-by-4.0Mar 2018View details →
zenodo40/100

Fig. 4 in Attraction of thrips (Thysanoptera) to colored sticky traps in a Florida olive grove

Fig. 4. Comparison of mean numbers of thrips (± SE) collected by sticky traps, tap samples, or brush samples between pre-bloom, bloom, and post-bloom sampling periods. Bars with different letters indicate significantly different means (P &lt;0.05).

opencc-by-4.0Mar 2018View details →
zenodo40/100

Fig. 3 in Attraction of thrips (Thysanoptera) to colored sticky traps in a Florida olive grove

Fig. 3. Differences in mean numbers of thrips (± SE) collected by tap and brush samples between plots. Bars with different letters indicate significantly different means (P &lt;0.05).

opencc-by-4.0Mar 2018View details →
zenodo40/100

Fig. 5 in Attraction of thrips (Thysanoptera) to colored sticky traps in a Florida olive grove

Fig. 5. Collection of mean numbers of thrips (± SE) (all species and stages combined) from differently colored sticky traps with combined data from all collection dates, or collections from bloom period alone. Bars with different letters indicate significantly different means (P &lt;0.05).

opencc-by-4.0Mar 2018View details →
zenodo40/100

Fig. 2 in Attraction of thrips (Thysanoptera) to colored sticky traps in a Florida olive grove

Fig. 2. Spectral reflectance of sticky card traps (white, blue, yellow, and clear), and abaxial and adaxial surfaces of olive leaves.

opencc-by-4.0Mar 2018View details →
zenodo40/100

Fig. 1 in Survey of Thysanoptera using colored sticky card traps in Florida, USA, olive groves

Fig. 1. Map of olive groves surveyed in North Central Florida. Stars represent locations of groves. "S" is a grove in Suwannee County, "G" is a grove in Gilchrist County, "M" is a grove in Marion County, and "V" is a grove in Volusia County. Map created using spatial data from USGS (2016).

opencc-by-4.0Jul 2020View details →
zenodo40/100

Fig. 2 in Survey of Thysanoptera using colored sticky card traps in Florida, USA, olive groves

Fig. 2. Diagram of a Florida olive grove indicating sampling locations (A) and spatial identifiers (B) used for sampling design and analysis. The large rectangle represents a 4 ha area surveyed; each of the 4 white boxes represents a 1 ha subplot. Each letter represents a sampling location where yellow and blue sticky traps were placed during each sampling visit. Spatial identifiers for sampling sites included: "COR" = corner site, "CEN" = center site, "ER" = edge of the grove site and bordered by olive trees on 3 sides of the tree, "END" = site located at the end of a row, but not a corner. Image from Google Maps.

opencc-by-4.0Jul 2020View details →
zenodo40/100

Fig. 4 in Survey of Thysanoptera using colored sticky card traps in Florida, USA, olive groves

Fig. 4. Mean thrips abundance per mo in 2017 and 2018 and in both yr combined found on yellow and blue sticky card traps in 4 north central Florida olive groves.

opencc-by-4.0Jul 2020View details →
zenodo40/100

Fig. 3 in Survey of Thysanoptera using colored sticky card traps in Florida, USA, olive groves

Fig. 3. Timeline of observed fruiting and flowering events of North Central Florida olive trees in both 2017 and 2018. The 2017 flowering and fruiting are represented by white symbols. The gap in 2017 fruiting visible in Sep is when Hurricane Irma prevented sampling efforts. The 2018 flowering and fruiting symbols are represented by black symbols. Triangles represent flowering events. Circles represent fruiting events. The black arrow represents the Florida harvest period. Specific flowering and fruiting events are listed on the y-axis, mo of observation are on the x-axis.

opencc-by-4.0Jul 2020View details →
zenodo36/100

2-class Grapevine Pest Dataset of Scaphoideus titanus and Orientus ishidae on yellow Sticky traps for Insect Detection

<p>This dataset consists of 615 images of <em>Scaphoideus titanus</em> (ST) and <em>Orientus ishidae</em> (OI) from yellow sticky traps (YST). Among these, 150 photos, which lack target insects, have been repurposed as background images. Insect annotations comprise 1329 ST and 1506 for OI, ensuring an almost class-balanced dataset. The images were acquired through four distinct methods:</p> <ul> <li>Photos from the field;</li> <li>Images of stored YST (T = 5&plusmn;1&deg;C) and reared insects within a controlled greenhouse environment;</li> <li>Digital scans of YST collected during regular monitoring activities in the fields;</li> <li>Photos from a smart trap prototype installed in our experimental vineyard.</li> </ul> Structure of the dataset, showing the number of images from each data source and the corresponding class annotations. <table><tbody> <tr> <td>Image source</td> <td>Number of images</td> <td>ST annotations</td> <td>OI annotations</td> <td>Number of background images</td> </tr> <tr> <td> <p>Field</p> </td> <td>18</td> <td>3</td> <td>101</td> <td>8</td> </tr> <tr> <td>Laboratory</td> <td>157</td> <td>473</td> <td>863</td> <td>8</td> </tr> <tr> <td>scanned</td> <td>390</td> <td>853</td> <td>542</td> <td>84</td> </tr> <tr> <td>smart-trap</td> <td>50</td> <td>0</td> <td>0</td> <td>50</td> </tr> </tbody> </table> <p>We provide the yellow sticky trap images already cropped in the pre-processing stage, the corresponding enhanced datasets focusing on&nbsp;<em>brightness &amp; contrast</em>, <em>sharpness</em>, and a combination of both. Finally the annotations exported in YOLO format.</p> <h3>Dataset structure</h3> <ol> <li><em>crop/</em></li> <li><em>bright/</em></li> <li><em>sharp/</em></li> <li><em>bright_and_sharp/</em>&nbsp;</li> <li><em>labels/</em></li> </ol> <p>At the time of publication, this dataset is the largest publicly available resource in the control of FD vectors. Detailed documentation, along with model benchmarking and performance results is given in an accompanying journal paper: (paper under submission).</p> <h3>Deployment</h3> <p>You can use this dataset as starting point to train your own insect detection models. Open source Python scripts to deploy the trained models can be found in our <a href="https://github.com/checolag/insect-detection-scripts/tree/main">Github</a> repository.</p>

opencc-by-4.0Jun 2024View details →
dryad36/100

Sticky trap pattern size for thrips spatial vision

Open the record for dataset details and reuse information.

publicApr 2025View details →
dryad32/100

Data from: Sticky traps as an early detection tool for crawlers of Adelges tsugae (Hemiptera: Adelgidae)

We developed an approach using sticky trap arrays as an early detection tool for populations of first instar nymphs of the hemlock woolly adelgid, Adelges tsugae (Annand), a pest of hemlocks, Tsuga spp., in North America. We considered the detection rate of at least one nymph from trapping arrays consisting of one to six sticky panels, where we varied both the surface area of each trap that we assessed and the length of the trapping duration. We also estimated the time needed to set up, service and assess groups of traps and attempted to relate capture of nymphs on traps to incidence and abundance of A. tsugae in the canopy above the traps. Arrays consisting of two traps provided a detection rate of 75% when 87.5% of the surface area of each trap was assessed, a process that required 38 min per array. The probability of detecting nymphs on traps left in the field for 5 or 6 days was similar to that for traps left for 12 days. The number of nymphs trapped in an array predicted the probability of finding A. tsugae in the canopy but only when all six traps were fully assessed. To reliably detect incipient A. tsugae infestations, we recommend placing arrays of traps at 1 km intervals along the perimeter of a stand during peak activity of first instar sistentes nymphs and servicing these arrays every 5 to 7 days.

opencc-zeroAug 2020View details →
zenodo32/100

Figure 2 in Living on a sticky trap: natural history and morphology of Bactrodes assassin bugs (Insecta: Hemiptera: Reduviidae: Bactrodinae)

Figure 2. Bactrodes femoratus in the field. (a) Female with egg batch, Colombia. (b) Female with ant prey; antennae in touch with egg batch, Colombia. (c) Female with egg batch, Trinidad and Tobago. (d) Egg batch with developing Bactrodes embryos, French Guiana. (e) Female with egg batch and hatching first instar immature, Peru. (f) Early instar with prey, French Guiana. (g) Pretarsus grasping plant trichome, Colombia. (h) Close up of pretarsus grasping plant trichome, Colombia. (i) Female on dorsal leaf surface of Clidemia cf. urceolata, Trinidad and Tobago. (j) Insect carrion trapped on sticky trichomes of Clidemia cf. urceolata.

opennotspecifiedJun 2021View details →
zenodo32/100

Figure 7 in Living on a sticky trap: natural history and morphology of Bactrodes assassin bugs (Insecta: Hemiptera: Reduviidae: Bactrodinae)

Figure 7. Egg batches of B. femoratus and egg parasitoids. (a) Egg batch with Bactrodes embryos and hatched eggs, Trinidad and Tobago. (b) Egg batch hatched eggs and eggs parasitised by Telenomus sp. (Scelionidae), Peru. (c) Two Bactrodes eggs parasitised by Telenomus sp. (d) Two Bactrodes eggs parasitised by Trichogramma sp. (Trichogrammatidae). (e) Telenomus sp. (right) and Trichogramma sp. (left) reared from B. femoratus eggs.

opennotspecifiedJun 2021View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record