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.
1,342
datasets available to search
ShareScore release 0.7.1
Dataset results
1,342 results for “pest”
F I G U R E 3 in Current and future potential geographical distribution of Bactericera cockerelli: an invasive pest of increasing global importance
F I G U R E 3 Predicted climatic suitability for tomato potato psyllid (TPP; Bactericera cockerelli) under current climatic conditions in Australia current climatic conditions. The known global distributions are denoted by green colour dots.
F I G U R E 7 in Current and future potential geographical distribution of Bactericera cockerelli: an invasive pest of increasing global importance
F I G U R E 7 Predicted future climatic suitability for tomato potato psyllid (TPP; Bactericera cockerelli) in New Zealand under a future climate change scenario predicted to the year 2090 in CLIMEX using the general circular model (GCM) CSIRO Mark 3.0, run with the A1B emissions scenario. The known global distributions denoted by green colour dots.
Figure 2 in Susceptibility of the sweet pepper (Capsicum annuum L.) to the infestation of Tetranychus urticae (Acari: Tetranychidae) and the different insect pests under greenhouse conditions in Ismailia, Egypt
Figure 2. The interaction effects of seasons and cultivars on the Chl., Car., total protein and phenol contents (A) and the activity of the antioxidant enzymes (B) of the two sweet pepper cultivars during the two growing seasons 2021–22.
Figure 1 in Susceptibility of the sweet pepper (Capsicum annuum L.) to the infestation of Tetranychus urticae (Acari: Tetranychidae) and the different insect pests under greenhouse conditions in Ismailia, Egypt
Figure 1. Monthly abundance of total TSSM (A), associated insect pest (B), and predator (C) numbers on the two sweet pepper cultivars during the two growing seasons 2021–22.
Figure 7 in The structure of the compound eyes and phototaxis in two phenotypes of the bean pest Callosobruchus maculatus (Coleoptera: Bruchinae)
Figure 7. Results of behavioral experiments and ERG measurements. A. Behavioral experimental equipment (DA—Dark area; SA— Standing area; LA—Light area). B. Daily activities of normal form Callosobruchus maculatus. C. Quantification of ERG voltage responses of the flight and normal form insects exposed to different light stimuli. Different letters indicate significant differences between ERG responses. D. The phototaxis responses of the flight (above) and normal (down) forms were classified into 'positive phototaxis', 'negative phototaxis', and 'no selection'. E. Comparison of the phototaxis responses of the normal form and flight form Callosobruchus maculatus in response to different colors of light. Data are presented as mean ± standard error of the mean, **p <0.01, ***p <0.001 (t tests).
Figure 4 in The structure of the compound eyes and phototaxis in two phenotypes of the bean pest Callosobruchus maculatus (Coleoptera: Bruchinae)
Figure 4. Three-dimensional reconstruction of the compound eye of the flight form Callosobruchus maculatus. A, D. Frontal view of the head. B, C. Lateral view of the head. E. Posterior view of the head. F. Anterior view of the head. Scale bars = 100 μm.
Figure 1 in The structure of the compound eyes and phototaxis in two phenotypes of the bean pest Callosobruchus maculatus (Coleoptera: Bruchinae)
Figure 1. External appearance of compound eyes of Callosobruchus maculatus obtained via SEM. A–D. Laterial view of head. E–H. Vertical view of head. A, E. Flight form female (FF). B, F. Flight form male (FM). C, G. Normal form female (NF). D, H. Normal form male (NM). Abbreviations: AS—antennal socket; CE—compound eye. Scale bars = 100 μm.
Figure 6 in The structure of the compound eyes and phototaxis in two phenotypes of the bean pest Callosobruchus maculatus (Coleoptera: Bruchinae)
Figure 6. Ultrastructure of compound eye of Callosobruchus maculatus. A, D. Longitudinal section of the cornea. B, E. Cross-section of the distal end of the rhabdom. C, F. Cross section of proximal end of the rhabdom. G, H. Longitudinal section of compound eye. I. Semischematic drawing of one ommatidium of Callosobruchus maculatus. A, B, C, G. Normal form male. D, E, F, H. Flight form male. Abbreviations: Co—cornea; CC—crystalline cone; PPC—primary pigment cell; SPC—secondary pigment cell; Rh—rhabdom; R1–R8—retinular cells; Rh7, Rh8—rhabdomere; PG—pigment granule; CCN—nuclei of cone cells; PCN—nuclei of primary pigment cells; RCN—nuclei of retinular cells. Scale bars: A–B, D–E = 5 μm; C, F = 0.5 μm; G–H = 10 μm.
Figure S3 in The structure of the compound eyes and phototaxis in two phenotypes of the bean pest Callosobruchus maculatus (Coleoptera: Bruchinae)
Figure S3. Electrophysiological waveforms of compound eyes of two types of Callosobruchus maculatus. A. White. B. Green (520–530 nm). C. Blue (460–470 nm). D. Ultraviolet (365 nm). E. Red (620–630 nm).
Figure 5 in The structure of the compound eyes and phototaxis in two phenotypes of the bean pest Callosobruchus maculatus (Coleoptera: Bruchinae)
Figure 5. Three-dimensional reconstruction of the compound eye of the normal form Callosobruchus maculatus. A, D. Frontal view of the head. B, C. Lateral view of the head. E. Posterior view of the head. F. Anterior view of the head. Scale bars = 100 μm.
Figure S2 in The structure of the compound eyes and phototaxis in two phenotypes of the bean pest Callosobruchus maculatus (Coleoptera: Bruchinae)
Figure S2. The projection of microCT of Callosobruchus maculatus. A. Flight form. B. Normal form. Abbreviations: S—baseline length of a segment; H—height.
Figure 3 in The structure of the compound eyes and phototaxis in two phenotypes of the bean pest Callosobruchus maculatus (Coleoptera: Bruchinae)
Figure 3. Differences in the areas and numbers of ommatidia observed in two types of Callosobruchus maculatus. A. The ommatidia areas of the flight and normal forms. B. The number of ommatidia compared between two types of Callosobruchus maculatus. *p <0.05; **p <0.01; n.s., indicates no significant difference (t tests).
Figure 2 in The structure of the compound eyes and phototaxis in two phenotypes of the bean pest Callosobruchus maculatus (Coleoptera: Bruchinae)
Figure 2. Partially external appearance of compound eyes of Callosobruchus maculatus obtained via SEM. A–D. Hexagonal ommatidia of compound eye (H). E–H. Pentagonal and irregular ommatidia of compound eye (P). I–L. The arrows point to the interfacetal hairs between the hexagonal ommatidia. M–P. The arrows point to the interfacetal hairs between the pentagonal and irregular ommatidia. A, E, I, M. Flight-form female (FF). B, F, J, N. Flight form male (FM). C, G, K, O. Normal form female (NF). D, H, L, P. Normal form male (NM). Scale bars = 10 μm.
Figure 1 in Identification of planthoppers (Hemiptera: Delphacidae) intercepted on aquarium plants in Florida and elucidation of a potential pathway for exotic aquatic and semiaquatic pests
Figure 1. Opiconsiva anacharsis (Fennah). A) Opiconsiva anacharsis on Echinodorus sp. plant as sold in stores. Photograph by Melanie Cain, DPI. B) Adult female dorsal habitus. Photograph by Jade S. Allen, DPI. C) Male genital capsule, lateral view. Photograph by Jade S. Allen, DPI. D) Male genital capsule, posterior view. Photograph by Susan E. Halbert, DPI.
Development of thrips barcode database and multiplex real-time PCR assay for quarantine and agriculture pest species
<p>Thrips (Order Thysanoptera) species are agriculturally important as plant sap sucking pests and vectors of several plant diseases. They are very small insects and commonly associated with imported commodities at New Zealand border in all life stages. Morphological identification of thrips is mainly performed on adults, but the available identification keys for immature stages do not include many species and are inadequate, thus DNA barcode was regularly used for thrips identification, here, we have generated DNA barcode data for over 29 thrips species from over 100 individuals. At New Zealand border,<em> Frankliniella occidentalis </em>is the dominant species intercepted, followed by <em>F. panamensis</em>, <em>Thrips palmi</em> and <em>T. tabaci </em>and several other thrips species. Hence, we have also developed a multiplex real time PCR assay, targeting the four thrips species to facilitate the identification of quarantine interceptions with more accurate and faster diagnostic method for any developmental stages. The DNA barcode database further assists in thrip identification. The assay showed high specificity for all the four target species and could detect 10 copies/ µL of the target DNA. Linear responses and high correlation coefficients between the amount of DNA and <em>C</em><sub>q</sub> values for each species were also achieved. The method was tested on single egg, larva and adult and proved to be applicable for all life stages of the four species. This study has demonstrated the assay is a useful biosecurity tool for rapid and reliable identification of the target thrips species. </p>
Assessing the Impact of Pest Monitoring Traps on Bombus griseocollis (Hymenoptera: Apidae) Colony Growth and Development
<p>Insect traps use visual and olfactory cues to attract target pests; however, they vary in their specificity and often unintentionally capture non-target beneficial insects (bycatch), including <em>Bombus</em>. Concerns have been expressed that bycatch may contribute to <em>Bombus</em> mortality and the consequential loss of pollination services. Here, we quantified the impact of trap captures on <em>Bombus griseocollis</em> colony growth and development by evaluating the following four treatments: colonies paired with traps, colonies paired with traps and pheromone lures, traps and pheromone lures (but no colonies), and colonies with no trap and no lure. Trap contents were collected biweekly to determine <em>B. griseocollis </em>capture rates. Colony growth and development data were collected weekly by weighing colonies and recording foraging activity. Based on microsatellite polymerase chain reaction (PCR) amplification, three <em>B. griseocollis </em>were collected from released colonies, while the remaining five were residents within the environment. Given the low number of <em>B. griseocollis </em>workers collected, any differences in colony weight change and active foraging were likely not a result of pest monitoring trap captures. However, trap captures could have a greater impact by interfering with functional diversity, colony establishment, and pollination services, emphasizing the need for additional research. Building on this research will provide a more comprehensive view of the impact of pest monitoring traps on <em>Bombus </em>populations, which could minimize risk to pollinator populations and pollination services.</p>
Fig. 3. Spiraea japonica L in The Spider Mite Schizotetranychus Spireafolia (Acari, Tetranychidae), Specific Pest Of Spiraea In The A. V. Fomin Botanical Garden
Fig. 3. Spiraea japonica L. infested with Sch. spireafolia mites: a — upper surface of leaf, b — lower surface of leaf.
Fig. 2 in The Spider Mite Schizotetranychus Spireafolia (Acari, Tetranychidae), Specific Pest Of Spiraea In The A. V. Fomin Botanical Garden
Fig. 2. Morphological characteristics of Sch. spireafolia from A. V. Fomin Botanical Garden, Kyiv, Ukraine: a — female x10; b — male x10; c — dorsal setae x100; d — palp tarsus of female x100; e — palp tarsus of male x100; f — empodium of tarsus I of female x100; g —
Fig. 5 in The Carpomyini Fruit Flies Diptera: Tephritidae Of Europe Caucasus And Middle East: New Records Of Pests With Improved Keys
Fig. 5. Rhagoletis spp. mesonotums (1–8), dorsal view, and head (2), lateral view: 1 — R. completa; 2 — R. bagheera; 3 — R. berberidis; 4 — R. cerasi; 5 — R. flavicincta; 6 — R. flavigenualis; 7 — R. obsoleta, Myhiia; 8 — R. sp. near obsoleta, Mt. Hermon.
Fig. 2 in The Carpomyini Fruit Flies Diptera: Tephritidae Of Europe Caucasus And Middle East: New Records Of Pests With Improved Keys
Fig. 2. Carpomya spp. heads, left lateral view: 1 — C. (Goniglossum) liat; 2 — C. (Myiopardalis) pardalina; 3 — C. (s. str.) incompleta; 4 — C. (s. str.) schineri.
ScienceDex guides
Understand access before you commit
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.