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1,425 results for “Agriculture”
MULTIPLIERS_WP5_Science learning project on Biodiversity and agriculture_UBO_Public data_20241014_v1
<p><span>This dataset contains the following data related to</span><span> the science learning project on <em>Biodiversity and agriculture</em></span><span>:</span></p> <ul> <li><span>S</span><span>ummary of transcripts from interviews with teachers, and OSC members (</span><span>Pseudo-/Anonymised)</span></li> </ul>
The role of nitrogen and iron biogeochemical cycles in the production and export of dissolved organic matter in agricultural headwater catchments
<p>Data on soil solutions collected in the riparian area at 15 cm depth in an agricultural catchment in Brittany (France) during one hydrological cycle. Zero-tension lysimeters were collected at a fortnightly frequency from October 2022 to June 2023. Measurements inlcude dissolved organic matter concentration and composition (3D flurorescence), nitrates, iron, and phosphorus.</p> <p>Data are published in Lambert et al., 2014, The role of nitrogen and iron biogeochemical cycles in the production and export of dissolved organic matter in agricultural headwater catchments, doi.org/10.5194/egusphere-2024-1212 (preprint).</p>
THE IMPACT OF LOCAL PRODUCT BRANDING ON THE ECONOMIC PERFORMANCE OF AGRICULTURAL AND LIVESTOCK AGRO-PROCESSING INDUSTRIES IN VLORA
<p>This study aims to examine the impact of local product branding on the economic performance of the agricultural and livestock agro-processing industries in the region of Vlora. Based on the data collected from local agro-processing and agro-tourism industries, the purpose of this research is to analyze how branding strategies contribute to increasing the level of sales, the level of income, creating a strong identity, and improving the performance of businesses and the territory where these businesses are concentrated. The study includes in the analysis the influence of the local brand in the creation of the identity, in the level of sales, in the income, the profit margins, and the improvement of the economic performance of the agricultural and livestock agro-processing industries. For this reason, the research was conducted with the inclusion of over 100 industries/agritourism, and the analysis of the questionnaire data was conducted with the STATA program. From the results of the research, it is clear that investment in the branding of products with local indicators is necessary to stimulate economic development and to strengthen the market positioning of businesses in the agricultural and livestock sectors. Also, this research provides important recommendations for improving branding practices as a strategic tool for the development and consolidation of agro-processing industries in the region.</p>
Linked collectors and determiners for: Connecticut Agricultural Experiment Station Arthropod Collection.
Natural history specimen data linked to collectors and determiners held within, "Connecticut Agricultural Experiment Station Arthropod Collection". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/a42d07b3-e34d-4a65-b7e3-6aafa9f8f27b">https://bionomia.net/dataset/a42d07b3-e34d-4a65-b7e3-6aafa9f8f27b</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/a42d07b3-e34d-4a65-b7e3-6aafa9f8f27b">https://gbif.org/dataset/a42d07b3-e34d-4a65-b7e3-6aafa9f8f27b</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: CDA - California Department of Food and Agriculture.
Natural history specimen data linked to collectors and determiners held within, "CDA - California Department of Food and Agriculture". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/b0515413-6d32-490a-83a0-f8c08f002c70">https://bionomia.net/dataset/b0515413-6d32-490a-83a0-f8c08f002c70</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/b0515413-6d32-490a-83a0-f8c08f002c70">https://gbif.org/dataset/b0515413-6d32-490a-83a0-f8c08f002c70</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Estonian University of Life Sciences Institute of Agricultural and Environmental Sciences Mycological Herbarium.
Natural history specimen data linked to collectors and determiners held within, "Estonian University of Life Sciences Institute of Agricultural and Environmental Sciences Mycological Herbarium". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/1f917113-dd55-4000-9f80-6266fab1af03">https://bionomia.net/dataset/1f917113-dd55-4000-9f80-6266fab1af03</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/1f917113-dd55-4000-9f80-6266fab1af03">https://gbif.org/dataset/1f917113-dd55-4000-9f80-6266fab1af03</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Estonian University of Life Sciences Institute of Agricultural and Environmental Sciences Entomological Collection.
Natural history specimen data linked to collectors and determiners held within, "Estonian University of Life Sciences Institute of Agricultural and Environmental Sciences Entomological Collection". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/1af83152-24f7-4df7-afbc-b213b62175bb">https://bionomia.net/dataset/1af83152-24f7-4df7-afbc-b213b62175bb</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/1af83152-24f7-4df7-afbc-b213b62175bb">https://gbif.org/dataset/1af83152-24f7-4df7-afbc-b213b62175bb</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Estonian University of Life Sciences Institute of Agricultural and Environmental Sciences Department of Plant Protection.
Natural history specimen data linked to collectors and determiners held within, "Estonian University of Life Sciences Institute of Agricultural and Environmental Sciences Department of Plant Protection". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/91afc73f-a11a-4e8b-9313-ed056697cf05">https://bionomia.net/dataset/91afc73f-a11a-4e8b-9313-ed056697cf05</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/91afc73f-a11a-4e8b-9313-ed056697cf05">https://gbif.org/dataset/91afc73f-a11a-4e8b-9313-ed056697cf05</a>. Formatted as a Frictionless Data package.
DIGITAL TOOLS FOR MONITORING AND MANAGEMENT IN AGRICULTURAL PRODUCTION
<p>The digitalization of agricultural production has led to the widespread use of mobile technologies for monitoring and managing agricultural processes. Applications and devices such as drones and satellites allow you to receive real-time data on soil conditions, humidity, plant growth, and pest threats. This data helps farmers to make quick decisions on irrigation, fertilization, and crop forecasting. Modern mobile solutions such as AgroMonitor integrate with various data sources and provide accurate information, which increases the efficiency of resource management and reduces production risks. The introduction of these technologies not only helps to increase yields but also ensures the sustainable development of agricultural operations, minimizing the impact of external factors. Thus, digital tools are becoming an important element of the modernization of the agro-industrial sector, contributing to its competitiveness at the global level.</p>
Analysis of the survival of agricultural exporting firms in Peru, 2009-2019
<p><strong><span>Background</span></strong><strong><span>: </span></strong><span>At the international level, the survival of exporting companies represents a critical issue in a context of heightened uncertainty and intensified competition within the framework of the country's commercial opening. This is a context in which different companies are born and die as a result of the interaction between the market and other factors. The objective of this research was to analysis of the survival of exporting agricultural companies in Peru, 2009-2019 . To this end, data from the Commission for the Promotion of Peru for Exports and Tourism (Promperu) was utilised.</span></p> <p><strong><span>Methods: </span></strong><span>The methodological contribution of the research is based on the quantitative approach, of basic type with a descriptive elk; being the population that involves a total of data of the agricultural exporting companies of Peru in the period 2009-2019 and the sample is census and the non-parametric statistical technique used was the Kaplan Meier estimate for the estimation of the survival rate. </span></p> <p><strong><span>Results: </span></strong><span>Exports of Peru's non-traditional agricultural sector in FOB value have had an average annual growth of 12% in terms of FOB value and 9% in terms of volume exported</span><strong><span>; </span></strong><span>the entry rate of new agro-exporting agricultural companies reached an average growth of 2.3% and the exit rate reached an average of 2.2% in the period 2009-2019.</span></p> <p><strong><span>Conclusions: </span></strong><span>The survival of exporting companies in the non-traditional agricultural sector is critical, where 89% of them survive only one year, while in the second year only 75% survive and in the sixth year only 33% survive.</span></p> <p><strong><span>Keywords: </span></strong><span>Agricultural exporting firms, Export resilience, Economic sustainability, Peru's agricultural exports, Business survival analysis</span></p>
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>
Epigenome-wide DNA Methylation and Pesticide Use in the Agricultural Lung Health Study
<p>An epigenome-wide association study of blood DNA methylation and pesticide use was conducted in adults in the Agricultural Lung Health Study. Sixteen specific pesticides were analyzed: dicamba, picloram, mesotrione, acetochlor, metolachlor, glyphosate, 2,4-Dichlorophenoxyacetic acid (2,4-D), atrazine, malathion, aldrin, chlordane, DDT, dieldrin, heptachlor, lindane, and toxaphene. 162 differentially methylated CpGs across 9 specific pesticides (acetochlor, atrazine, dicamba, glyphosate, malathion, metolachlor, mesotrione, picloram, and heptachlor.</p>
Abb. 3 in Tribu des brevipennes. Famille des aleochariens. Septieme branche: Myrmedoniaires. Annales de la Societe d'Agriculture Histoire Naturelle et Arts Utiles de Lyon (ser.
Abb. 3: Nadelwald mit Rhododendron-Unterwuchs bei Dagcanglhamo in der Umgebung des Typenfundortes von Trigonurus ruzickai. Foto: J. RĤžiþka.
Abb. 2a-g in Tribu des brevipennes. Famille des aleochariens. Septieme branche: Myrmedoniaires. Annales de la Societe d'Agriculture Histoire Naturelle et Arts Utiles de Lyon (ser.
Abb. 2a-g: Trigonurus ruzickai: -Sternit VIII (a); -Tergit VIII (b); -Sternit IX (c); Aedoeagus, lateral (d); Aedoeagus, dorsal (e); Aedoeagus, ventral (f); Distal-Gonocoxit, Stylus und Hinterrand von -Tergit X (g). -Paratypus (a-f); -Paratypus (g).
Abb. 1a-k in Tribu des brevipennes. Famille des aleochariens. Septieme branche: Myrmedoniaires. Annales de la Societe d'Agriculture Histoire Naturelle et Arts Utiles de Lyon (ser.
Abb. 1a-k: Trigonurus ruzickai: Habitus (a); Kopf (b); Kopf, Unterseite (c); Pronotum (d); Elytre (e); Prosternum (f); Mitte von Sternit III (g); Mikroskulptur auf Scutellum (h); Elytren (i) und Abdomen (k). -Holotypus (a, b, d, e, h-k), -Paratypus (c, f, g).
Dataset with Agricultural Parcels Markup on Satellite Images
<p>The dataset was created for the development and testing of the algorithm proposed in the paper "Segmentation of agricultural parcel in satellite images based on historical vegetation index data". However, this markup can be used to test other algorithms and compare their quality.</p> <p>This work employs data from the remote sensing programs Sentinel-2A, Sentinel-2B.</p> <p>The dataset contains the agricultural parcel markup for four regions within Russia and Ukraine, where agriculture is well developed. The areas were chosen so that each of them had other types of terrain in addition to fields: urban area, water surface, swamps, and forests.</p> <p> </p>
Scottish hill farming score by agricultural parishes
<p>Dataset to accompany work on the impact of hill farming in Scotland commissioned by RESAS (Scottish Government). Data resolution is agricultural parishes, spatial data defining these can be downloaded from <https://data.gov.uk/dataset/939fdd5e-7322-4ab7-9dc9-bbfc538c4477/agricultural-parishes>.</p> <p>Data used to define the hill farming score is derived from the following datasets: Ordnance Survey Terrain 50; Scottish Natural Heritage, landscape character assessment, carbon and peatland map; James Hutton Institute land capability for agriculture; RESAS agricultural census common and rough grazing areas.</p> <p>Licence statements for input data are:</p> <p>Derived from or contains: Scottish Government and SNH information licensed under the Open Government Licence v3.0; James Hutton Institute materials licensed under the Open Government Licence v.2.0; and Ordnance Survey data Crown copyright and database right 2018.</p> <p>Generation code can be found here: https://doi.org/10.5281/zenodo.1887477</p>
Agricultural grasslands buffer density effects in red deer populations
<p>Data for</p> <p>Agricultural grasslands buffer density effects in red deer populations</p> <p>Initially accepted in Journal of Wildlife Management</p>
Datset of the paper entitled "FAIR degree assessment in agriculture datasets using the F-UJI tool".
<p>This is a dataset of our research realised recently, which contains tested results (json files) by F-UJI tool and FAIR assesment reports of tested repositories.</p>
Data supplement to "Aromatics and agriculture: A spatial approach to long-distance trade and the local economy of the Nabataeans"
<p>Data used to analyze the role of long-distance trade in the local agricultural economy of the Nabataeans, as described in Weaverdyck, E. J. S. forthcoming. "Aromatics and agriculture: A spatial approach to long-distance trade and the local economy of the Nabataeans." In S. von Reden (ed.). <em>Handbook of Ancient Afro-Eurasian Economies</em>, vol. 3. Oldenbourg: De Gruyter.</p> <p>Data sources are provided in the chapter.</p> <p>With the exception of runoff, environmental variables are rasters created using the focal statistics tool to sum the number of cells within a radius around each cell. They are named according to the following convention: f{radius}_{factor abbreviation}_{variable}.tif</p> <p>Factor abbreviations:</p> <table> <tbody> <tr> <td>A</td> <td>Aspect</td> </tr> <tr> <td>D</td> <td>DEV geomorphological land form</td> </tr> <tr> <td>H</td> <td>Hydrology</td> </tr> <tr> <td>S</td> <td>Slope</td> </tr> <tr> <td>T</td> <td>TPI geomorphological land form</td> </tr> </tbody> </table> <p>Of these environmental variables, the following were used as background variables in the MaxEnt models:</p> <table> <thead> <tr> <th scope="col">ASKP-LA</th> <th scope="col">WHS</th> </tr> </thead> <tbody> <tr> <td>f500_H_prec_soak</td> <td>f500_H_Runoff</td> </tr> <tr> <td>f500_T_Valley</td> <td>f5k_D_Ridge</td> </tr> <tr> <td>f5k_T_Ridge</td> <td>f5k_H_Runoff</td> </tr> <tr> <td>f5k_H_Runoff</td> <td>f500_D_UpperSlope_or_low_rise</td> </tr> <tr> <td>f5k_A_Northeast</td> <td>f5k_A_Southwest</td> </tr> <tr> <td>f500_D_UpperSlope_or_low_rise</td> <td>f500_D_Valley</td> </tr> <tr> <td>f5k_H_springs</td> <td> </td> </tr> <tr> <td>f5k_D_Ridge</td> <td> </td> </tr> <tr> <td>f5k_A_South</td> <td> </td> </tr> <tr> <td>f5k_A_Southwest</td> <td> </td> </tr> <tr> <td>f5k_A_Northwest</td> <td> </td> </tr> <tr> <td>f500_T_UpperSlope_or_low_rise</td> <td> </td> </tr> <tr> <td>f500_D_Lower_slope_or_shallow_valley</td> <td> </td> </tr> <tr> <td>f5k_A_North</td> <td> </td> </tr> </tbody> </table> <p> </p>
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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.
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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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.