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1,648 results for “farm”
Fig. 2 in Prevalence and gross pathology of liver fluke in macropods cohabiting livestock farms in north eastern NSW, Australia, and diagnosis using cELISA
Fig. 2. Liver fluke prevalence in Macropods (infected/total sampled) cohabiting farms in the Northern Tablelands region of NSW, Australia. Number of farms by risk site: low – 2 farms, medium – 3 farms, high – 2 farms.
Fig. 1 in Common occurrence of Enterocytozoon bieneusi genotypes SHR1 and PL2 in farmed masked palm civet (Paguma larvata) in China
Fig. 1. Phylogenetic relationships of the E. bieneusi genotypes. The relationships were inferred using NJ analysis of the ITS rRNA gene and the values generated greater than 70% are shown beside the nodes. Genotypes with hollow circles and filled circles are known and novel genotypes identified in this study, respectively.
Fig. 1 in Molecular detection and genotypes of Enterocytozoon bieneusi in farmed mink (Neovison vison), blue foxes (Alopex lagopus), and raccoon dogs (Nyctereutes procyonoides) in Xinjiang, China
Fig. 1. Phylogenetic relationships of the E. bieneusi genotypes. The relationships were inferred using NJ analysis of the ITS rRNA gene and the values generated greater than 50% are shown beside the nodes. Genotypes with hollow circles and filled circles are known and novel genotypes identified in this study, respectively.
CWRU Farm SDR CHU 3.330 MHz from April 1, 2024
<p>Collected at Squire Valleevue Farm.</p> <table> <tbody> <tr> <td>41.49308889</td> <td>-81.42378287</td> </tr> </tbody> </table>
CWRU Farm SDR CHU 14.770 MHz from April 8, 2024 Solar Eclipse
<p>Collected at Squire Valleevue Farm.</p> <table> <tbody> <tr> <td>41.49308889</td> <td>-81.42378287</td> </tr> </tbody> </table>
CWRU Farm CHU 7.850 MHz from April 8, 2024 Solar Eclipse
<p>Collected at Squire Valleevue Farm.</p> <table> <tbody> <tr> <td>41.49308889</td> <td>-81.42378287</td> </tr> </tbody> </table>
CWRU Farm (ET) CHU 3.330 MHz from April 8, 2024 Solar Eclipse
<p>Collected at Squire Valleevue Farm.</p> <table> <tbody> <tr> <td>41.49308889</td> <td>-81.42378287</td> </tr> </tbody> </table>
FIGURE 5 in Structure and composition of ichthyofauna associated with cage fish farming and compared to a control area after severe drought in a Neotropical reservoir
FIGURE 5 | Redundancy analysis (RDA). Relation of ichthyofauna to the significant environmental variable (quota) in the drought and wet seasons in an area without the influence of fish farming (Control) at the Ilha Solteira reservoir, Upper Paraná River, São Paulo, Brazil. Ala = Acestrorhynchus lacustris, Acr = Astronotus crassipinnis, Cke = Cichla kelberi, Cpi = Cichla piquiti, Cbr = Cyphocharax gillii, Cgi = Crenicichla britskii, Gsv = Geophagus sveni, Hma = Hoplias aff. malabaricus, Mac = Megalancistrus parananus, Mli = Metynnis lippincottianus, Oni = Oreochromis niloticus, Ppl = Pimelodus platicirris, Ppi = Pinirampus pirinampu, Psq = Plagioscion squamosissimus, Pam = Pterygoplichthys ambrosettii, Rvu = Rhaphiodon vulpinus, Rde = Roeboides descalvadensis, Spa = Satanoperca pappaterra, Sin = Steindachnerina insculpta, Sit = Schizodon intermedius, Sna = Schizodon nasutus, Sma = Serrasalmus maculatus, Smg = Serrasalmus marginatus, Hbu = Heterotilapia buttikoferi, and Tne = Triportheus nematurus.
FIGURE 4 in Structure and composition of ichthyofauna associated with cage fish farming and compared to a control area after severe drought in a Neotropical reservoir
FIGURE 4 | Beta diversity (PERMDISP) in the drought and wet seasons in the control and fish farm areas at the Ilha Solteira reservoir, Upper Paraná River, São Paulo, Brazil. Average distances of centroids with presence/absence of data. Asterisks indicates significant upper value between seasons within each area.
FIGURE 3 in Structure and composition of ichthyofauna associated with cage fish farming and compared to a control area after severe drought in a Neotropical reservoir
FIGURE 3 | Box plots (minimum and maximum value = vertical line ends, standard error = box, and mean = horizontal line) of the ichthyofauna attributes in the control area and fish farm area, in the drought and wet seasons at the Ilha Solteira reservoir, Upper Paraná River, SP, Brazil. A. Total abundance; B. Species richness; C. Shannon index; D. Pielou evenness. Asterisks indicates significant upper value between seasons within each area. Hash indicates significant upper value between areas within each season.
FIGURE 2 in Structure and composition of ichthyofauna associated with cage fish farming and compared to a control area after severe drought in a Neotropical reservoir
FIGURE 2 | Historical series of the variation in quota (m) between 1999 and 2019 in the Ilha Solteira reservoir, Upper Paraná River, São Paulo, Brazil. The dots indicate the sampling period.
FIGURE 1 in Structure and composition of ichthyofauna associated with cage fish farming and compared to a control area after severe drought in a Neotropical reservoir
FIGURE 1 | Map of South America showing the Ilha Solteira reservoir, with an indication of the sample areas (black circles). Adapted from Kliemann et al. (2018).
Soil biota (earthworm, nematode and soil surface fauna) data of organic, permaculture and conventional horticultural farms of Central Hungary
<p>This dataset has been produced from the PhD research of Alfréd Szilágyi supervised by Csaba Centeri and Eszter Kovács Tormáné. The study compared permaculture, organic and conventional farming systems regarding their ecosystem-service provision potential and sustainability. Multiple ecological indicators were measured in the field during the field study in 2020, and the basic datasets (soil test results; photo gallery of the studied farms with soil core sample; soil resistance and moisture; decomposition; earthworms; nematodes; soil surface fauna; pollinators; agrobiodiversity and habitat types) are uploaded in Zenodo separately to provide scientific data on permaculture systems. In this way, we hope to contribute to international efforts to evaluate the performance of agroecological agriculture alternatives. These publications also serve as supplements to the PhD thesis. For the sake of further usability of the datasets short description of the used methods is described. For further information please contact the authors.</p>
Predation activity data in organic, permaculture and conventional horticultural farms of Central Hungary
<p>This dataset has been produced from the PhD research of Alfréd Szilágyi supervised by Csaba Centeri and Eszter Kovács Tormáné. The study compared permaculture, organic and conventional farming systems regarding their ecosystem-service provision potential and sustainability. Multiple ecological indicators were measured in the field during the field study in 2020, and the basic datasets (soil test results; photo gallery of the studied farms with soil core sample; soil resistance and moisture; decomposition; earthworms; nematodes; soil surface fauna; pollinators; agrobiodiversity and habitat types) are uploaded in Zenodo separately to provide scientific data on permaculture systems. In this way, we hope to contribute to international efforts to evaluate the performance of agroecological agriculture alternatives. These publications also serve as supplements to the PhD thesis. For the sake of further usability of the datasets short description of the used methods is described. For further information please contact the authors.</p>
SUPER-G Benchmarking performance on commercial farms (task 3.1)
<p><span>The SUPER-<em>G </em>project aimed to co-develop sustainable Permanent Grassland (PG) systems and policies with farmers and policy makers to effectively optimise productivity whist supporting biodiversity and delivering other Ecosystem Services (ES). This was achieved through the completion of a series of Work Packages (WP). Work Package 3 aimed </span><span>to benchmark performance in terms of profitability and sustainability and the delivery of ES. This was achieved in part through </span><span>deliverable (D) D3.2, where an “</span><span>Overview of data, key gaps, and trends in PG management in the different biogeographic regions” was compiled. This overview included a survey of 352 farms across six biogeographic regions conducted in 2019, which explored on-farm management and differences between regions. A second, subsequent, survey was undertaken in 2023, which included 203 of the original farms from five biogeographic areas. Deliverable report 3.3. </span>describes the distribution of key indicators from farms surveyed in the first survey and describes any changes which were captured in the second survey. <span>A</span><span>gri-environment indicators and key sustainability indicators were identified in WP2 and include forage efficiency, grass utilisation (the proportion of grass dry matter grown that is consumed by livestock) and grass/clover dry matter (DM) productivity. Due to the limitations of how many questions can be asked in a survey and the time required to perform a survey, it was not possible to calculate all these metrics. This report examines the sustainability indicators of stocking density, grass production and output per hectare and environmental indicators of areas reserved for nature and biodiversity.</span></p> <p> </p> <p><span>The data files include the survey questions, responses from 2021 survey, responses from 2023 survey and a blank survey form. </span></p>
LAND RESOURCES OF YAKUTIA'S AGRICULTURE IN THE LAST DECADE OF SOCIALISM: PECULIARITIES OF LAND ACCOUNTING OF STATE FARMS IN THE ARCTIC AND NORTHERN REGIONS
<p><span>The article shows the peculiarities of land resources utilization in the traditional economy of the indigenous population of Yakutia in the last decade of the Soviet period with a separate delineation of the state of the land balance and lands used in agriculture in 1990-1991. Including on the basis of archival data on land resources of state farms of the studied 15 arctic and northern regions, peculiarities of their accounting, preliminary results of statistical analysis of land resources of these large farms are obtained. The author introduces into scientific turnover new factual materials on land resources of separate state farms for the last Soviet 1991, in particular on their agricultural lands, reindeer and horse pastures.</span></p>
Supplementary material to the publication entitled "Digital transformation at what cost? A case study from Germany estimating the adoption potential of precision farming technologies under different scenarios" in Smart Agricultural Technology, https://doi.org/10.1016/j.atech.2024.100585
<p>The file '<em>PAT_Descriptions_Assumptions_Supplementary Material.pdf</em>' contains descriptions of the selected Precision Agricultural Technologies (PATs) and detailed explanations of the assumptions made in the calculation model.</p> <p> </p> <p>The file '<em>Calculation Model_NUTS3_BW.xlsx</em>' includes the calculation model created for the publication.</p>
Linked collectors and determiners for: Wild Bee Specimens from Blueberry and Raspberry Farms in the Champlain Valley, Vermont, USA.
Natural history specimen data linked to collectors and determiners held within, "Wild Bee Specimens from Blueberry and Raspberry Farms in the Champlain Valley, Vermont, USA". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/26c7440a-f4e4-4564-9901-9aac6e116536">https://bionomia.net/dataset/26c7440a-f4e4-4564-9901-9aac6e116536</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/26c7440a-f4e4-4564-9901-9aac6e116536">https://gbif.org/dataset/26c7440a-f4e4-4564-9901-9aac6e116536</a>. Formatted as a Frictionless Data package.
ET0001 - CWRU Farm - CHU 14.670 MHz from April 8, 2024 Solar Eclipse
<p>See <a href="https://doi.org/10.5281/zenodo.13293306">10.5281/zenodo.13293306</a> for system documentation. <br>See <a href="https://doi.org/10.5281/zenodo.14004715">10.5281/zenodo.14004715</a> for python code to parse these files. </p> <p>Location: Chagrin Falls, OH. </p> <p>Lat/lon: </p> <table> <tbody> <tr> <td>41.49308889</td> <td>-81.42378287</td> </tr> </tbody> </table>
Agriculture and food system scenarios with particular focus on organic and agro-ecological farming practices in the EU
<p>This is a comprehensive dataset of the agriculture and food system scenarios co-developed with stakeholders with the agricultural land use model BioBaM-GHG 2.0 and presented in Deliverable 4.2 of the H2020 project UNISECO. It includes sub-national (NUTS1/2-level) data on agricultural production and consumption, land use, greenhouse gas emissions from livestock and agricultural activities, etc. for the base year 2012 and the scenario years 2030 and 2050. The scenarios include a Business as usual case and four scenarios with focus on organic and agro-ecological farming practices in the EU, based on different storylines. Further information is available from the above-mentioned deliverable.</p> <p>A detailed model description is provided in the paper "Exploring the option space for land system futures at regional to global scales: The diagnostic agro-food, land use and greenhouse gas emission model BioBaM-GHG 2.0", in which these scenarios are also presented as an exemplary application of the model BioBaM-GHG 2.0.</p> <p>This work was funded by the ERA-NET SusAn project 101243 AnimalFuture, as well as by the European Union’s Horizon 2020 research and innovation programme and its funding of the H2020 UNISECO project under grant agreement N°773901.</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)
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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.