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1,425 results for “Agriculture”
Eliciting plant defenses by exposition to HIPV’s: a new sustainable approach to manage agricultural pests
GEO Series GSE150659. Solanum lycopersicum. 12 samples. Type: Expression profiling by high throughput sequencing.
Implications of the use of organic fertilizers for Antibiotic Resistant Gene dissemination in agricultural soils and fresh food products. A plot-scale study
GEO Series GSE179685. soil metagenome; feces metagenome; sludge metagenome; solid waste metagenome. 71 samples. Type: Other.
A large-scale high-resolution cropland non-agriculturalization (Hi-CNA) dataset
<p><span>The Hi-CNA is a high-resolution remote sensing dataset dedicated to the cropland non-agriculturalization (CNA) tasks, featuring high-quality semantic and change annotations for cropland. The study area covers parts of Hebei, Shanxi, Shandong, Hubei provinces in China, with a total area exceeding 1100 km<sup>2</sup>. These regions exhibit significant variations in crop planting, ensuring the diversity of cropland morphologies. The first temporal phase spans from 2015 to 2017, while the second phase ranges from 2020 to 2022, covering multiple phenological periods of crops. These characteristics provide a rich variety of samples for CNA tasks.</span></p> <p><span><span>The dataset is sourced from multispectral GF-2 fusion images with a spatial resolution of 0.8m, encompassing four bands including visible light and near-infrared. All images are cropped to 512*512, resulting in a total of 6797 pairs of dual-temporal images with corresponding annotations. Figure 1 illustrates different forms of cropland and some types of changes.</span></span></p>
Agricultural Crop Disease Image Dataset from Tanzania
<p>A comprehensive Crop Disease Image Dataset meticulously curated to aid in the study and advancement of agricultural research and plant pathology within Tanzania. This dataset encompasses a diverse array of classes, each representing distinct diseases and health states affecting a variety of crops commonly cultivated in Tanzanian agriculture. Classes include American Poppy, Bean Angular Leaf Spot, Bean Healthy, Bean Leaf Miner, Bean Light Yellow, Bean Rust, Bell Pepper Early Bright, Bell Pepper Fusarium Wilt, Bell Pepper Healthy, Black Nightshade Healthy, Black Nightshade Leaf Miner, Cabbage CP Deficiency, Cabbage Healthy, Chinese Botanical Leaf Spot, Chinese Healthy, Maize Faw, Maize Health, Maize Leaf Aphid, Maize Streak Virus, Okra Health, Okra Leaf Miner, Okra Powderly, Onions Healthy, Onions Powderly, Spinach Anthracnose, Spinach Health, Tomato Health, and Tomato Leaf Miner. Each class represents a distinct disease or health state commonly observed in crops grown throughout Tanzania, providing a valuable resource for researchers, agronomists, and machine learning practitioners alike. With a diverse range of classes meticulously labeled and organized, this dataset facilitates the development and evaluation of algorithms for disease detection, classification, and mitigation strategies specific to Tanzanian agricultural contexts.</p>
Assessment of the adverse effects of pollution on farmland bird diversity in contemporary agricultural landscapes: Species Richness and Abundance Data
Open the record for dataset details and reuse information.
Input data and R code for "Larger male Yellow Warbler ( Setophaga petechia ) occupy smaller home ranges over winter in natural and agricultural sites in western Mexico"
<p>Data used for modeling Yellow Warbler home ranges in western Mexico from 2012 to 2014.</p> <p> </p> <p> </p>
Characterization of Antibiotic Resistance and Metal Homeostasis Genes in Midwest USA Agricultural Sediments
GEO Series GSE125810. uncultured soil bacterium; uncultured soil microorganism. 9 samples. Type: Other.
Agricultural sterol biosynthesis inhibitor fungicides
GEO Series GSE2412. Saccharomyces cerevisiae. 22 samples. Type: Expression profiling by array.
Model output data for Fujimori et al., Impacts of GHG emissions abatement measures on agricultural market and food security
<p>Model output data for "Fujimori et al., Impacts of GHG emissions abatement measures on agricultural market and food security" submitted to Nature Food</p>
SELECTED PHYSICAL AND CHEMICAL PROPERTIES OF SOIL UNDER DIFFERENT AGRICULTURAL LAND-USE TYPES IN ILE-IFE, NIGERIA
<p>The study examined changes in soil properties under different agricultural land-use types. This is with the view to extending knowledge on the nature of soil properties under long-term land-use practices. Six land-use types were considered; paddock, continuously cropped, secondary forest, teak, oil palm and cacao plantations. Soil strength and saturated hydraulic conductivity were determined at two soil depths (0-15 and 15-30 cm) in-situ. Soil samples were collected to determine particle size distribution, bulk density, aggregate stability, pH, organic carbon, cation exchange capacity, total nitrogen and available phosphorus.</p>
Dataset for McClelland et al. 2022. Infrequent compost applications increased plant productivity and soil organic carbon in irrigated pasture but not degraded rangeland. Agriculture, Ecosystems, and Environment.
<p>Raw data files accompanying the published article "Infrequent compost applications increased plant productivity and soil organic carbon in irrigated pasture but not degraded rangeland" in <em>Agriculture, Ecosystems, and Environment</em>. <a href="https://authors.elsevier.com/a/1etJPcA-Ik6yb">https://authors.elsevier.com/a/1etJPcA-Ik6yb</a></p> <p>Units for response variables in .csv files are as follows. Please reach out to scm229@cornell.edu with any questions about using the files or the data within.</p> <p>--</p> <p>Aboveground biomass: total (Mg ha-1), carbon (Mg C ha-1), nitrogen (kg N ha-1)</p> <p>Bulk density: g cm-3</p> <p>Respiration (Rs): micro mol m-2 s-1</p> <p>Roots: Mg C ha-1</p> <p>Soil C and N: organic and inorganic carbon (Mg C ha-1), nitrogen (Mg N ha-1)</p> <p> </p>
Post-Typhoon Mawar UAV Orthomosaic: UOG Yigo Agricultural Research and Education Center
<p>This orthomosaic was created from 815 images taken on 02 June 2023. Images were collected at 400 ft AGL, with a DJI Zenmuse H20 mounted on a DJI Matrice 30T UAV. The mission was planned using the DJI Pilot application and post-processed using DroneDeploy. The resolution of the orthomosaic is .82in/px.</p> <p>The following aerial imagery is intended solely for the purpose of assessing damages to the natural and built environment associated with Typhoon Mawar. Typhoon Mawar's closest approach to Guam was 24 May 2023. It is strictly prohibited to distribute this imagery to any unauthorized individuals or third-party entities without prior authorization.</p> <p>The University of Guam Drone Corps (funded by NASA Guam Space Grant and NASA Guam EPSCoR) and the Western Pacific Tropical Research Center retain all rights to the aerial imagery, including but not limited to copyrights and intellectual property rights. Any unauthorized modification, reproduction, or distribution of the imagery is strictly prohibited.</p> <p>By using this data, you acknowledge and agree to abide by the terms and conditions set forth in this disclaimer.</p> <p>Privacy Disclaimer: The aerial imagery captured for damage assessment may inadvertently include images of private property and individuals. While every effort has been made to respect privacy, it is possible that identifiable information or sensitive locations may be visible in the imagery. University of Guam Drone Corps and the Western Pacific Tropical Research Center disclaim any responsibility for the unintentional collection or dissemination of such information. The recipient(s) of this imagery are urged to handle it with due care and take necessary precautions to protect the privacy rights of individuals and comply with applicable privacy laws and regulations.</p>
Post-Typhoon Mawar UAV Orthomosaic: UOG Ija Agricultural Research Station
<p>This orthomosaic was created from 644 images taken on 13 June 2023. Images were collected at 400 ft AGL, with a DJI Zenmuse H20 mounted on a DJI Matrice 30T UAV. The mission was planned using the DJI Pilot application and post-processed using DroneDeploy. The resolution of the orthomosaic is 1.4in/px.</p> <p>The following aerial imagery is intended solely for the purpose of assessing damages to the natural and built environment associated with Typhoon Mawar. Typhoon Mawar's closest approach to Guam was 24 May 2023. It is strictly prohibited to distribute this imagery to any unauthorized individuals or third-party entities without prior authorization.</p> <p>The University of Guam Drone Corps (funded by NASA Guam Space Grant and NASA Guam EPSCoR) and the Western Pacific Tropical Research Center retain all rights to the aerial imagery, including but not limited to copyrights and intellectual property rights. Any unauthorized modification, reproduction, or distribution of the imagery is strictly prohibited.</p> <p>By using this data, you acknowledge and agree to abide by the terms and conditions set forth in this disclaimer.</p> <p>Privacy Disclaimer: The aerial imagery captured for damage assessment may inadvertently include images of private property and individuals. While every effort has been made to respect privacy, it is possible that identifiable information or sensitive locations may be visible in the imagery. University of Guam Drone Corps and the Western Pacific Tropical Research Center disclaim any responsibility for the unintentional collection or dissemination of such information. The recipient(s) of this imagery are urged to handle it with due care and take necessary precautions to protect the privacy rights of individuals and comply with applicable privacy laws and regulations.</p>
Post-Typhoon Mawar UAV Orthomosaic: UOG Inarajan Agricultural Research Station
<p>This orthomosaic was created from 132 images taken on 13 June 2023. Images were collected at 400 ft AGL, with a DJI Zenmuse H20 mounted on a DJI Matrice 30T UAV. The mission was planned using the DJI Pilot application and post-processed using DroneDeploy. The resolution of the orthomosaic is .82in/px.</p> <p>The following aerial imagery is intended solely for the purpose of assessing damages to the natural and built environment associated with Typhoon Mawar. Typhoon Mawar's closest approach to Guam was 24 May 2023. It is strictly prohibited to distribute this imagery to any unauthorized individuals or third-party entities without prior authorization.</p> <p>The University of Guam Drone Corps (funded by NASA Guam Space Grant and NASA Guam EPSCoR) and the Western Pacific Tropical Research Center retain all rights to the aerial imagery, including but not limited to copyrights and intellectual property rights. Any unauthorized modification, reproduction, or distribution of the imagery is strictly prohibited.</p> <p>By using this data, you acknowledge and agree to abide by the terms and conditions set forth in this disclaimer.</p> <p>Privacy Disclaimer: The aerial imagery captured for damage assessment may inadvertently include images of private property and individuals. While every effort has been made to respect privacy, it is possible that identifiable information or sensitive locations may be visible in the imagery. University of Guam Drone Corps and the Western Pacific Tropical Research Center disclaim any responsibility for the unintentional collection or dissemination of such information. The recipient(s) of this imagery are urged to handle it with due care and take necessary precautions to protect the privacy rights of individuals and comply with applicable privacy laws and regulations.</p> <p> </p> <p> </p>
USGS Group on Earth Observations (GEO) Global Agricultural Monitoring (GLAM) Algeria
The objective of GEO is to fulfil a vision of a world where decisions and actions are informed by coordinated, comprehensive and sustained Earth Observation (EO). This is being pursued mainly through the added value of co-ordinating existing institutions, organised communities, space agencies, in-situ monitoring agencies, scientific institutions, research centres, universities, modelling centres, technology developers and other groups that deal with one or more aspects of EO. To reach this overarching goal, GEO focuses on capacity development in three dimensions: infrastructure, individuals and institutions. In the field of agriculture, the general goal is to promote the utilization of Earth observations for advancing sustainable agriculture, aquaculture and fisheries. Key issues include early warning, risk assessment, food security, market efficiency and combating desertification. (Source: http://www.research-europe.com/index.php/2011/08/joao-soares-secretariat-expert-for-agriculture-group-on-earth-observations/)
USGS Group on Earth Observations (GEO) Global Agricultural Monitoring (GLAM) Russia
The objective of GEO is to fulfil a vision of a world where decisions and actions are informed by coordinated, comprehensive and sustained Earth Observation (EO). This is being pursued mainly through the added value of co-ordinating existing institutions, organized communities, space agencies, in-situ monitoring agencies, scientific institutions, research centres, universities, modelling centres, technology developers and other groups that deal with one or more aspects of EO. To reach this over arching goal, GEO focuses on capacity development in three dimensions: infrastructure, individuals and institutions. In the field of agriculture, the general goal is to promote the utilisation of Earth observations for advancing sustainable agriculture, aquaculture and fisheries. Key issues include early warning, risk assessment, food security, market efficiency and combating desertification. (Source: http://www.research-europe.com/index.php/2011/08/joao-soares-secretariat-expert-for-agriculture-group-on-earth-observations/)
USGS Group on Earth Observations (GEO) Global Agricultural Monitoring (GLAM) Ethiopia
The objective of GEO is to fulfil a vision of a world where decisions and actions are informed by coordinated, comprehensive and sustained Earth Observation (EO). This is being pursued mainly through the added value of co-ordinating existing institutions, organised communities, space agencies, in-situ monitoring agencies, scientific institutions, research centres, universities, modelling centres, technology developers and other groups that deal with one or more aspects of EO. To reach this overarching goal, GEO focuses on capacity development in three dimensions: infrastructure, individuals and institutions. In the field of agriculture, the general goal is to promote the utilization of Earth observations for advancing sustainable agriculture, aquaculture and fisheries. Key issues include early warning, risk assessment, food security, market efficiency and combating desertification. (Source: http://www.research-europe.com/index.php/2011/08/joao-soares-secretariat-expert-for-agriculture-group-on-earth-observations/)
USGS Group on Earth Observations (GEO) Global Agricultural Monitoring (GLAM) Uganda
The objective of GEO is to fulfil a vision of a world where decisions and actions are informed by coordinated, comprehensive and sustained Earth Observation (EO). This is being pursued mainly through the added value of co-ordinating existing institutions, organised communities, space agencies, in-situ monitoring agencies, scientific institutions, research centres, universities, modelling centres, technology developers and other groups that deal with one or more aspects of EO. To reach this over arching goal, GEO focuses on capacity development in three dimensions: infrastructure, individuals and institutions. In the field of agriculture, the general goal is to promote the utilisation of Earth observations for advancing sustainable agriculture, aquaculture and fisheries. Key issues include early warning, risk assessment, food security, market efficiency and combating desertification. (Source: http://www.research-europe.com/index.php/2011/08/joao-soares-secretariat-expert-for-agriculture-group-on-earth-observations/)
USGS Group on Earth Observations (GEO) Global Agricultural Monitoring (GLAM) Argentina
The objective of GEO is to fulfil a vision of a world where decisions and actions are informed by coordinated, comprehensive and sustained Earth Observation (EO). This is being pursued mainly through the added value of co-ordinating existing institutions, organised communities, space agencies, in-situ monitoring agencies, scientific institutions, research centres, universities, modelling centres, technology developers and other groups that deal with one or more aspects of EO. To reach this overarching goal, GEO focuses on capacity development in three dimensions: infrastructure, individuals and institutions. In the field of agriculture, the general goal is to promote the utilization of Earth observations for advancing sustainable agriculture, aquaculture and fisheries. Key issues include early warning, risk assessment, food security, market efficiency and combating desertification. (Source: http://www.research-europe.com/index.php/2011/08/joao-soares-secretariat-expert-for-agriculture-group-on-earth-observations/)
USGS Group on Earth Observations (GEO) Global Agricultural Monitoring (GLAM) Ukraine
The objective of GEO is to fulfill a vision of a world where decisions and actions are informed by coordinated, comprehensive and sustained Earth Observation (EO). This is being pursued mainly through the added value of coordinating existing institutions, organized communities, space agencies, insitu monitoring agencies, scientific institutions, research centres, universities, modelling centres, technology developers and other groups that deal with one or more aspects of EO. To reach this overarching goal, GEO focuses on capacity development in three dimensions: infrastructure, individuals and institutions. In the field of agriculture, the general goal is to promote the utilization of Earth observations for advancing sustainable agriculture, aquaculture and fisheries. Key issues include early warning, risk assessment, food security, market efficiency and combating desertification. (Source: http://www.research-europe.com/index.php/2011/08/joao-soares-secretariat-expert-for-agriculture-group-on-earth-observations/)
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.