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22,710 results for “Plants for planting”
Figures 40–45 in Revision of the Australian species of Pleistodontes (Hymenoptera: Agaonidae) fig-pollinating wasps and their host-plant associations
Figures 40–45. Head (females). (40) P. schizodontus; (41) P. rigisamos; (42) P. schizodontus sp. nov. clypeus; (43) P. rigisamos clypeus; (44) P. schizodontus sp. nov. mandibles; (45) P. rigisamos mandibles. Scale bar = 100 Mm.
Figures 14–22 in Revision of the Australian species of Pleistodontes (Hymenoptera: Agaonidae) fig-pollinating wasps and their host-plant associations
Figures 14–22. (14) P. regalis pronotum anterior part; (15) P. nitens metasoma; (16) P. addicotti head; (17) P. nitens head; (18) P. nigriventris head; (19) P. addicotti mandibular appendages; (20) P. nitens mandibular appendages; (21) P. nitens mandibles (22) P. nigriventris mandibular appendages. Scale bar = 200 Mm, except 14 & 22 = 100 Mm.
Figures 77–82 in Revision of the Australian species of Pleistodontes (Hymenoptera: Agaonidae) fig-pollinating wasps and their host-plant associations
Figures 77–82. Head and mesosoma (females). (77) P. macrocainus sp. nov. vertex; (78) P. cuneatus pollen pocket; (79) P. astrabocheilus sp. nov. pollen pocket; (80) P. macrocainus sp. nov. pollen pocket; (81) P. greenwoodi pollen pocket; (82) P. xanthocephalus sp. nov. pollen pocket. Scale bar = 100 Mm.
Figures 88–91 in Revision of the Australian species of Pleistodontes (Hymenoptera: Agaonidae) fig-pollinating wasps and their host-plant associations
Figures 88–91. (88) P. macrocainus sp. nov. (ex F. brachypoda) mandible; (89) P. greenwoodi mandible; (90) P. greenwoodi fore leg; (91) P. xanthocephalus sp. nov. fore leg. Scale bar = 50 Mm.
Figures 1–8 in Revision of the Australian species of Pleistodontes (Hymenoptera: Agaonidae) fig-pollinating wasps and their host-plant associations
Figures 1–8. Head (females). (1) P. froggatti dorsal view; (2) P. froggatti mandibles; (3) P. deuterus sp. nov. dorsal view; (4) P. regalis dorsal view; (5) P. froggatti clypeus; (6) P. deuterus sp. nov. clypeus; (7) P. regalis clypeus; (8) P. regalis mandibles. Scale bar = 200 Mm (head) and 50 Mm (clypeus and mandibles).
Public resources about PHYVV and TMV detection in Jalapeño pepper plants using CNNs
<p>This repository contains a dataset of Jalapeño pepper leaves which where divided into three classes labeles as "healthy", "PHYVV-infected" and "TMV-infected. In addition, the folder labeled as model contains all the information of the artificial intelligence model that was utilized to classify between the aforementioned classes.</p>
Grapevine Dataset for plant organ segmentation
<p><br>This is a dataset for Grapevine segmentation for the purposes of winter pruning, created in a joint work between Istituto Italiano di Tecnologia and Università Cattolica del Sacro Cuore, as part of the Vinum project. The work was also cofounded by Italian Ministry of University and Research PRIN 20172HHNK5 Project, under the supervision of Matteo Gatti, Claudio Semini and Darwin Caldwell.</p> <p>The images were captured in the simulated grapevine garden in Università Cattolica, located in Piacenza, Italy, and it is split in two parts, following agronomic trials being run on the university. The first part is a group of seven specimen that is the Control group, and the second group of eight specimens is being performed shoot thinning.</p> <p>Each plant has around 5 spurs, and the photos are taken from both sides of the grapevine specimen, meaning that there is one picture where the plant grows from left to right, and the other side where the plant grows from right to left. The resolution of the images is 4608x3456, and we have a total of 149 images. </p> <p> </p> <p>It is annotated using the COCO Segmentation format, and some of the statistics of the dataset such as the number of annotations and number of images can be seen next.</p> <p><strong>Control Complex</strong></p> <ul> <li>Total <ul> <li>Images: 69</li> <li>Annotated Images: 69</li> <li>Annotations: 1838</li> <li>Categories: 5</li> </ul> </li> <li>Annotations Per Category <ul> <li>Main Cordon: 79</li> <li>Cane: 440</li> <li>Node: 1100</li> <li>Arm: 103</li> <li>Spur: 116</li> </ul> </li> <li>Annotated Images Per Category <ul> <li>Main Cordon: 69</li> <li>Cane: 69</li> <li>Node: 69</li> <li>Arm: 62</li> <li>Spur: 68</li> </ul> </li> </ul> <p><strong>Shoot Thining Simple</strong></p> <ul> <li>Total <ul> <li>Images: 79</li> <li>Annotated Images: 79</li> <li>Annotations: 1635</li> <li>Categories: 5</li> </ul> </li> <li>Annotations Per Category <ul> <li>Main Cordon: 84</li> <li>Cane: 341</li> <li>Node: 912</li> <li>Arm: 154</li> <li>Spur: 144</li> </ul> </li> <li>Annotated Images Per Category <ul> <li>Main Cordon: 79</li> <li>Cane: 79</li> <li>Node: 79</li> <li>Arm: 79</li> <li>Spur: 77</li> </ul> </li> </ul> <p> </p>
Data from: Effects of artificial light at night on the leaf functional traits of freshwater plants
<p>Leaf traits measured on three species of submerged aquatic plants (<em>Myriophyllum verticillatum </em>L., <em>Potamogeton coloratus</em> Hornem., and <em>Vallisneria spiralis</em> L.) grown under light pollution at night or in the dark. Details about the protocols and the data collection can be found in the article published in <em>Freshwater Biology</em>.</p>
Data from: Floral scents of a deceptive plant are hyperdiverse and under population-specific phenotypic selection
<p>Floral scent is a key mediator in plant–pollinator interactions; however, little is known to what extent intraspecific scent variation is shaped by phenotypic selection, with no information yet in deceptive plants. We recorded 289 scent compounds in deceptive moth fly-pollinated <i>Arum maculatum </i>from various populations north vs. south of the Alps, the highest number so far reported in a single plant species. Scent and fruit set differed between regions, and some, but not all differences in scent could be explained by differential phenotypic selection in northern vs. southern populations. Our study is the first to provide evidence that phenotypic selection is involved in shaping geographic patterns of floral scent in deceptive plants. The hyperdiverse scent of <i>A. maculatum</i> might result from the plant's imitation of various brood substrates of its pollinators.</p>
Data - Co-feeding of VGO and pine-wood derived hydrogenated pyrolysis oils in an Fluid Catalytic Cracking pilot plant to generate olefins and gasoline
<p>Dataset to the corresponding research article with the same title. Research article is submitted to the open research europe platform.</p>
Pollination success increases with plant diversity in high Andean communities
<p>Pollinator-mediated plant-plant interactions have traditionally been viewed within the competition paradigm. However, facilitation via pollinator sharing might be the rule rather than the exception in harsh environments. Moreover, plant diversity could be playing a key role in fostering pollinator-mediated facilitation. We examined a total of 9,371 stigmas of 88 species from nine high-Andean communities in NW Patagonia, and we explored the prevalent sign of the relation between conspecific pollen receipt and heterospecific pollen diversity, and assessed whether the incidence of different outcomes varies with altitude and whether pollen receipt relates to plant diversity.</p>
Datasets from An Atlas of Plant Transposable Elements
<p>In this repository, we deposited support data for the article "An Atlas of Plant Transposable Elements", available at <a href="http://apte.cp.utfpr.edu.br/">http://apte.cp.utfpr.edu.br/</a>.</p> <p>Here, we included:</p> <p><strong>1.) Supplementary material data:</strong><br> A) SuppMat_1.xlsx: The genome assembly reference access from Ensembl Plants species used.<br> B) SuppMat_2.docx: A brief transposable elements annotation steps used in this work.</p> <p><strong>2.) Code and software: </strong>all script code create, third part software, how we used it, are detailed using Arabidopsis thaliana genome as an example in the GitHub: <a href="https://github.com/daniellonghi/te_pipeline">https://github.com/daniellonghi/te_pipeline</a> under the MIT license (please see details in licence.txt file). For third part-software, consult their terms.</p> <p>To report bugs, to ask for help, and to give any feedback, please contact Alexandre R. Paschoal (paschoal@utfpr.edu.br) or Douglas S. Domingues (douglas.domingues@unesp.br).</p>
Code & Data from: Development of a low cost open-source ultrasonic device for plant height measurements
<p>We here provide code and data for the study "Development of a low cost open-source ultrasonic device for plant height measurements"</p> <p>Code:<br> - Arduino code (management of the electronic circuit): "Arduino_ultrasonic_sensor.ino"<br> - OpenSCAD code (3D-printing): "3DShells_ultrasonic_sensor.scad"<br> - R code (statistical analysis of field test): "Statistical_analysis.R"</p> <p>Data:<br> - "manual_vs_sensor_controlled.csv": this file contains the comparison between the ultrasonic device and the ruler in standardized laboratory conditions. It has three columns: "manual_value", the height value measured manually; "sensor_value", the height value obtained from the ultrasonic device; "height_range", the interval to which the height value belongs (we worked with 25 cm intervals).<br> - "manual_vs_ruler_field.csv": this file contains the comparison between the ultrasonic device and the ruler in field conditions. Plant height measurements were performed on 26 sorghum genotypes. The file has four columns: "Genotype", the id of the measured genotype; "rep" the replicate (3 plants were measured for each genotype); "manual_value", the height value measured manually; "sensor_value", the height value obtained from the ultrasonic device. When using the ruler, the operator spent 15 min and 23 s to complete all measurements in the field, and 3 min and 27 s to enter all data manually in a digital file. When using the sensor, the operator spent 10 min and 52 s to complete all measurements in the field, and manual transcription was not needed since all measurements are instantaneously saved on an SD card.</p> <p>More details on the experimental data can be found in the article "Development of a low cost open-source ultrasonic device for plant height measurements".</p> <p>We also provide a tutorial to explain how to build the ultrasonic-sensor ("tutorial.docx")</p>
Plasma NMR metabolomic of rainbow trout fed diets with different levels of marine and plant ingredients.
<p>The NMR and biochemical datasets used in the manuscript draft entiteld "Intestinal microbiota in rainbow trout, <em>Oncorhynchus mykiss</em>, fed diets with different levels of marine and plant ingredients: A correlative approach with some plasma metabolites."</p> <p>François-Joël Gatesoupe1*, Benoît Fauconneau1, Catherine Deborde2,3**, Blandine Madji Hounoum1,2, Daniel Jacob2,3,Annick Moing2,3, Geneviève Corraze1, Françoise Médale1. 1 UMR 1419 NuMeA, INRA, Université de Pau et des Pays de l’Adour, Saint Pée sur Nivelle, France 2 Bordeaux Metabolome Facility, CGFB, MetaboHUB, Centre INRA Nouvelle -Aquitaine-Bordeaux, Villenave d'Ornon, France 3 UMR1332 Biologie du Fruit et Pathologie, Centre INRA Nouvelle -Aquitaine-Bordeaux, Villenave d'Ornon, France<br> *Corresponding author Joel.Gatesoupe@partenaire-exterieur.ifremer.fr</p> <p>**NMR dataset Corresponding author catherine.deborde@inra.fr</p> <p> </p> <p> </p> <p> </p>
Dataset for the paper "Data for Distribution of Vascular Plants (Tracheophytes) of urban forests and floodplains in the Tyumen city (Western Siberia)"
<p>Dataset associated with the manuscript “Data for Distribution of Vascular Plants (Tracheophytes) of urban forests and floodplains in the Tyumen city (Western Siberia)” submitted to the journal Data.</p>
Data from: Which traits optimize plant benefits? Meta-analysis on the effect of partner traits on the outcome of an ant-plant protective mutualism
<p><span>1. Theoretical models on mutualism dynamics predict that partner traits may influence the outcome of mutualistic interactions. However, most empirical data on this issue is restricted to case studies, limiting our ability to reach a more widespread comprehension of the role of partner traits on the dynamic of mutualisms. </span></p> <p><span>2. We investigated how the outcome of protective mutualisms between ants and plants bearing extrafloral nectaries (EFNs) is influenced by the traits of EFNs and ants feeding on EFNs. We used a meta-analytical approach based on 35 studies investigating the effect of ant attendance on the herbivores and reproductive performance of EFN-bearing plants. We evaluated how variation in the EFN vascularization and location on plants and the ant aggressiveness can modulate the effect of ant attendance on the plants. </span></p> <p><span>3. Both plant and ant traits investigated here drove the outcome of the protective mutualism for EFN-bearing plants. Plants exclusively bearing EFNs near reproductive organs benefited more from ant attendance than plants bearing EFNs on vegetative or vegetative and reproductive organs. Ants had a higher positive impact on the reproductive performance of plants bearing non-vascularized EFNs than plants bearing vascularized EFNs, although their effects on herbivores had been similar in both plant types. Regarding the ant behavior, plants often attended by more aggressive ant species had a higher reproductive performance than plants often attended by less aggressive ones. </span></p> <p><span>4. Synthesis</span><span>: Our results highlight that the selective pressures and evolutionary routes in ant-plant protective mutualisms may depend on the pool of traits exhibited by partner species. Although some studies have already reported some impact of species traits on the outcome of ant-plant mutualisms, this is the first time that a generalization about the role of species traits on the net balance of ant attendance was proposed. Due to this generalization, it was possible to advance our knowledge about the evolution of facultative mutualisms by showing that the role of species traits on the mutualistic outcome can vary in intricate ways due to a particular trait combination found among partners in communities where the interactions are embedded in.</span></p>
Object-based image analysis for monitoring plant invasions, can we use an open-source solution?
<p><strong>Introduction</strong></p> <p>This is a practical exercise testing possibilities of open-source solutions (FOSS) for object-based image analysis (OBIA) to monitor plant invasion using unoccupied aerial system (UAS, drone).</p> <p>The material is accompanying a chapter <strong><em>Müllerová, J. et al. (2023). Vegetation mapping and monitoring by unoccupied aerial systems – current state and perspectives. In: Manfreda, S. et Eyal B.D. (eds). Unmanned Aerial Systems for Monitoring Soil, Vegetation, and Riverine Environments. Elsevier.</em></strong></p> <p>The material is meant for readers to run the workflow and detect invasion of giant hogweed on the UAS data themselves testing different FOSS solutions.</p> <p> </p> <p><strong>Data</strong></p> <p>• a subset of UAS-borne data (consumer camera) collected in Czech Republic during the flowering of a noxious invasive plant species giant hogweed (<em>Heracleum mantegazzianum</em>)</p> <p>• training dataset</p> <p>• eCognition rulebase (proprietary OBIA software)</p> <p>• a script for SegOptim package implemented in R</p> <p> </p> <p><strong>Description</strong></p> <p>The use case represents a simple application of OBIA approach based on the SegOptim package implemented in R.</p> <p>Four bands (RGBN) UAS image subset are available, capturing the central area of a heavily invaded location (CZ) by giant hogweed (Heracleum mantegazzianum). Thanks to the proper image timing, the invasive species is clearly observable as white objects (in RGB) representing the various stage of the blossom. Considering the complex shape of the flower heads, detection based on image segmentation outperforms pixel-based classification (Müllerová et al., 2017). Simple segmentation of input imagery is performed (for simplicity only the spectral bands are considered both for segmentation and feature space definition, however additional features such as vegetation indices or textural measures may be included), followed by supervised classification using training data. Finally, a visual comparison of result detection both from proprietary (eCognition) and open-source (SegOptim) implementation is provided, confirming comparable results.</p> <p>Based on #github("joaofgoncalves/SegOptim")</p> <p> </p> <p><strong>References</strong></p> <p>Gonçalves, J., Pôças, I., Marcos, B., Mücher, C. A., & Honrado, J. P. (2019). SegOptim—A new R package for optimizing object-based image analyses of high-spatial resolution remotely-sensed data. <em>International Journal of Applied Earth Observation and Geoinformation</em>, <em>76</em>, 218-230.</p> <p>Müllerová, J., Brůna, J., Bartaloš, T., Dvořák, P., Vítková, M. & Pyšek, P. (2017b). Timing Is Important: Unmanned Aircraft vs. Satellite Imagery in Plant Invasion Monitoring. Frontiers in Plant Science 8:1–13.</p> <p>Accompanying material for</p> <p>Müllerová, J. et al. (2023). Vegetation mapping and monitoring by unoccupied aerial systems – current state and perspectives. In: Manfreda, S. et Eyal B.D. (eds). Unmanned Aerial Systems for Monitoring Soil, Vegetation, and Riverine Environments. Elsevier</p>
Data from: Fertiliser application modulates the impact of interannual climate fluctuations and plant-to-plant interactions on the dynamics of annual species in a Mediterranean grassland
<p><span><strong><span>Background:</span></strong><span> Climate and land-use changes, which include the application of various types of organic and inorganic fertilisers, have been reducing the species diversity of Mediterranean grasslands and threatening their conservation. Annual plants are one of the most diverse functional groups of species in these grasslands, despite suffering competitive pressure from perennial herbaceous and woody species, and they are essential for ecosystem functioning and stability. </span></span></p> <p><span><strong><span>Aims:</span></strong><span> To quantify how fertilisation modulates the impact of plant-to-plant interactions and climate fluctuations on the dynamics of annuals in Mediterranean grasslands. We hypothesised that the application of sewage sludge would increase competition between functional groups, reducing the abundance of annuals in the long-term, but would buffer the negative impacts of drought on the year-to-year fluctuation of the diversity of annuals.</span></span></p> <p><span><strong><span>Methods:</span></strong><span> In a semi-natural species-rich Mediterranean grassland in northern Spain, we analysed the changes in the taxonomical and functional composition and diversity of annuals over 14 years in response to variations in the abundance of perennial herbaceous and woody species, climate fluctuations, and fertilisation with sewage sludge. We quantified separately the patterns of year-to-year fluctuations and long-term trends. </span></span></p> <p><span><strong><span>Results:</span></strong><span> The frequency and diversity of annuals decreased with a higher abundance of perennial herbaceous species, drought in June, and cold winters. The addition of sewage sludge decreased the abundance of annuals in the long-term, seemed to promote competition between annuals and other functional groups at an interannual scale, and mitigated the negative effects of drought and cold.</span></span></p> <p><span><span><strong>Conclusions:</strong> Fertilisation influences differently the temporal response of annuals to climate fluctuations and plant-to-plant interactions.</span></span></p>
Figures 10–18 in Whiteflies (Hemiptera: Aleyrodidae) intercepted on plant product imported to South Korea from 2013-2021
Figures 10–18. Eight species of whiteflies. 10) Aleuroclava jasmini (Takahashi), puparium. 11) Aleuroclava neolitseae (Takahashi), puparium. 12) Aleuroclava similis (Takahashi), puparium. 13) Aleurodicus dispersus Russell, puparium. 14) Aleurolobus marlatti (Quaintance), puparium. 15) Aleuroplatus alcocki (Peal), puparium. 16–17) Aleuroplatus bossi Takahashi, puparium and vasiform orifice. 18) Aleurotrachelus dryandrae Solomon, puparium.
Figures 19–27 in Whiteflies (Hemiptera: Aleyrodidae) intercepted on plant product imported to South Korea from 2013-2021
Figures 19–27. Eight species of whiteflies. 19–20) Aleurotrachelus sp., puparium and abdomen detail of the vasiform orifice. 21) Bemisia tabaci (Gennadius), puparium. 22) Cockerelliella psidii (Corbett), puparium. 23) Crenidorsum aroidephagus Martin and Aguiar, puparium. 24) Dialeurodes citri (Ashmead), puparium. 25) Dialeurodes kirkaldyi (Kotinsky), puparium. 26) Dialeuropora decempuncta (Quaintance and Baker), puparium. 27) Massilieurodes sp., puparium.
ScienceDex guides
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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.