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189 results for “Vineyards”
Figure 2 in Oribatid mites of conventional and organic vineyards in the Valencian Community, Spain
Figure 2 Mean temperature (°C) and sum of precipitation (mm) in all months of years 2014 and 2015 in El Poble Nou de Benitatxell (data
VINEyard Piacenza Image Collections - VINEPICs
<p><strong>For a detailed description of this dataset</strong>, based on the <em>Datasheets for Datasets</em> (Gebru, Timnit, et al. "Datasheets for datasets." <em>Communications of the ACM</em> 64.12 (2021): 86-92.), check the <strong>VINEPICs_datasheet.md</strong> file.</p> <p><strong>For what purpose was the dataset created?</strong><br> VINEPICs was developed specifically for the purpose of detecting grape bunches in RGB images and facilitating tasks such as object detection, semantic segmentation, and instance segmentation. The detection of grape bunches serves as the initial phase in an analysis pipeline designed for vine plant phenotyping. The dataset encompasses a wide range of lighting conditions, camera orientations, plant defoliation levels, species variations, and cultivation methods. Consequently, this dataset presents an opportunity to explore the influence of each source of variability on grape bunch detection<strong>.</strong></p> <p><strong>What do the instances that comprise the dataset represent?</strong><br> The dataset consists of RGB images showcasing various species of vine plants. Specifically, the images represent three different Vitis vinifera varieties:<br> - Red Globe, a type of table grape<br> - Cabernet Sauvignon, a red wine grape<br> - Ortrugo, a white wine grape</p> <p>These images have been collected over different years and dates at the vineyard facility of Università Cattolica del Sacro Cuore in Piacenza, Italy. You can find the images stored in the "data/images" directory, organized into subdirectories based on the starting time of data collection, indicating the day (and, if available, the approximate time in minutes). Images collected in 2022 are named using timestamps with nanosecond precision.</p> <p><strong>Is there a label or target associated with each instance?</strong><br> Each image has undergone manual annotation using the Computer Vision Annotation Tool (CVAT) (https://github.com/opencv/cvat). Grape bunches have been meticulously outlined with polygon annotations. These annotations belong to a single class, "bunch," and have been saved in a JSON file using the COCO Object Detection format, including segmentation masks (https://cocodataset.org/#format-data).</p> <p><strong>What mechanisms or procedures were used to collect the data?</strong><br> The data was collected using a D435 Intel Realsense camera, which was mounted on a four-wheeled skid-steering robot. The robot was teleoperated during the data collection process. The data was recorded by streaming the camera's feed into rosbag format. Specifically, the camera was connected via a USB 3.0 interface to a PC running Ubuntu 18.04 and ROS Melodic.</p>
UAV Canyelles Vineyard Dataset 2023-06-09
<p>The dataset encompasses the following data:</p> <ol> <li> <p>Orthomosaic Images:</p> <ul> <li>ortho_230609.jpg: A detailed RGB orthomosaic of the entire vineyard. This orthomosaic was meticulously generated using Agisoft Metashape, employing images from the RGB.zip folder. The creation process involved medium accuracy settings.</li> <li>ortho_230609_ndvi.jpg: An orthomosaic captured in Near-Infrared (NIR) spectrum, portraying the entirety of the vineyard. This NIR orthomosaic was crafted through Agisoft Metashape, utilizing both NIR images and the Red channel of the RGB images from the NIR.zip and RGB.zip folders. The generation process employed medium accuracy settings.</li> </ul> </li> <li> <p>Drone-Captured Image Folders:</p> <ul> <li>RGB.zip: A collection of RGB images obtained using a DJI MAVIC 3M drone. These images were gathered during a flight at an altitude of 10 meters, ensuring 80% frontal and side overlap between each image.</li> <li>NIR.zip: A compilation of Near-Infrared (NIR) images collected through the same manual drone flight process.</li> </ul> </li> </ol> <p>The data collection procedure involved flying the DJI MAVIC 3M drone over the vineyard in Canyelles in Catalonia, Spain. The flight took place under sunny weather conditions with an average temperature of 26 degrees Celsius. </p>
Climatic records and within field data on yield and harvest quality over a whole vineyard estate.
<p>The data were obtained on a 30 ha vineyard located in a peri-urban area near a city of 10,000 inhabitants (Villeneuve-lès-Maguelone, France; 43.532300° N, 3.864230° E). The data includes 3 types of data:</p> <ul> <li> <p><strong>Block(s) data</strong>: the data describes each vineyard block. The description parameters of the blocks are the identity, the year of plantation, the variety of the grapes, the area, the inter-row distance and vine-distance. The data is provided as vector data (.shp and associated files) using the WGS84 global coordinate reference system for latitude and longitude. The data is composed of 68 features.</p> </li> <li> <p><strong>Agronomic data</strong>: The data describes production parameters for each “harvest sector” for the 2022 harvest season. A harvest sector is the area covered by the harvester to fill a harvest trailer before its departure to a cellar. The mean area of these harvest sectors over the vineyard is equal to 0.3 ha. The data is provided as vector data (.shp and associated files) using the WGS84 global coordinate reference system for latitude and longitude. The data is composed of 87 features associated with 87 harvest sectors. Each harvest sector is characterized by the harvest date, the block(s) id(s) that it belongs to, the percentage of unproductive plants(Uplants) and yield parameters (Mass, Yield and Yield PP). For 50 of them, harvest quality parameters are available (Sugar, Alcohol, Total acidity, pH, Yeast Assimilable Nitrogen and Organic Nitrogen).</p> </li> <li> <p><strong>Weather data</strong>: the data consists of meteorological data for the 2020, 2021 and 2022 years recorded by a weather station located in the center of the vineyard. The recorded parameters are the followings: date, hour, relative humidity, rain gauge and air temperature. The acquisition time step is 15 minutes. The data are provided in Comma Separated Values (CSV) format. It is composed of 97988 lines. Each line describes meteorological data recorded at a given time.</p> </li> </ul>
Linking intercontinental biogeographic events to decipher how European vineyards escaped Pierce's disease
Open the record for dataset details and reuse information.
Unexpected effects of local management and landscape composition on predatory mites and their food resources in vineyards
<p>This research was funded by the project SECBIVIT.</p> <p>Dataset of the results in the Articel: Unexpected effects of local management and landscape composition on predatory mites and their food resources in vineyards.</p> <p>For further information also see: </p> <ul> <li>Sampled grape varieties: http://doi.org/10.5281/zenodo.4562219 </li> <li>https://www.secbivit.boku.ac.at/</li> </ul>
UAV Spraying Parameters-Coverage in Vineyards
<p>A set of UAV spraying data collected using WSPs, across different parameter configurations. All tests were conducted in an experimental vineyard, under field conditions. All WSP samples were analysed using the DepositScan software developed by USDA (doi: 10.1016/j.compag.2011.01.003), and all coverage and VMD values are estimated by this software.</p>
Seismic and Hydrostratigraphic Characterization of the Onshore-Offshore Freshwater Systems of Martha's Vineyard and Nantucket, Massachusetts, USA: Field Survey Report
<p>This data archive includes three files: field project report, seisimic data (shot gathers) from Martha's Vineyard, and seismic data (shot gathers) from Nantucket. This work was supported by the National Science Foundation (NSF Award 2052794). Technical support was provided by Geophysical Technology, Inc. (<a href="https://geophysicaltechnology.com/">https://geophysicaltechnology.com/</a>), Exploration Instruments (<a href="https://www.exiusa.com/">https://www.exiusa.com/</a>) , and Seismic Source (<a href="https://seismicsource.com/">https://seismicsource.com/</a>). Field work in Manuel F. Correllus State Forest was conducted with the approval of the Massachusetts Department of Conservation and Recreation under Research Access Permit #R-209. Daniel Wright and Conor Laffey of the Massachusetts Department of Conservation and Recreation provided local logistical support on Martha’s Vineyard. Field work on Nantucket was conducted with the approval of Wannacommet Water Company. Mark Willett of Wannacommet water company provided local logistical support on Nantucket.</p>
Typical swiss vineyard shed or "Capite"
Typical swiss vineyard shed or "Capite" captured using DJI Mavic3 drone and processed in RealityCapture Photogrammetry software This is the simplified version of the model (from 10.7M tri to 3.2M tri) These Capite can be found everywhere in the Swiss vineyards, especially in Lavaux vineyard and are used to store equipment and sometimes as a resting place Source: Objaverse 1.0 / Sketchfab
Dataset for the SFmodel, applied in Evapotranspiration dynamics and partitioning in a grassed vineyard: ecophysiological and computational modelling approaches
<p>Dataset used for the SFmodel, applied in the work "Evapotranspiration dynamics and partitioning in a grassed vineyard: ecophysiological and computational modelling approaches".</p> <p>For units and nomenclature of the variables refer to Units_and_Nomenclature_for_SFmodel_in_Evapotranspiration_dynamics_and_partitioning_in_a_grassed_vineyard.pdf. </p>
Landscape heterogeneity increases bird functional diversity within Neotropical vineyards
<p>Conversion of lands to agroecosystems has resulted in a decline in bird biodiversity. Analyzing functional diversity is a central tool for detecting changes in the ecological functions performed by birds in these landscapes. This paper aims to investigate the responses of bird taxonomic and functional diversity to landscape heterogeneity and native forest cover in Neotropical vineyards. We sampled 19 vineyard landscapes in southeastern Brazil. These landscapes covered a gradient of forest cover and heterogeneity resulting from various land uses. To assess bird diversity, we considered both taxonomic diversity and functional diversity (i.e., functional richness, evenness, and divergence). To examine the potential interactions between landscapes and bird assemblages, we employed generalized linear models (GLM). Taxonomic diversity showed no correlation with any landscape metrics. On the other hand, variation in the three metrics of functional diversity was related to landscape heterogeneity. However, in heterogeneous landscapes, these communities can be structured by limiting similarity processes. We highlight the impact of landscape homogenization on the ecological functions performed by birds in vineyards while finding no significant effect on species diversity. These findings can provide valuable support for the formulation of public policies aimed at striking a balance between agricultural production and biodiversity conservation.</p>
Dataset for Evapotranspiration dynamics and partitioning in a grassed vineyard: ecophysiological and computational modelling approaches
<p>Data sets of the work "Evapotranspiration dynamics and partitioning in a grassed vineyard: ecophysiological and computational modelling approaches".</p> <p>You will find all data files needed for this work, organised by the figures of the paper. For the codes, refer to Flavio Bastos Campos. (2024). flaviobastoscampos/ET_dynamics_and_partitioning_vineyard: v2024.1 (v2024.1). Zenodo. <a href="https://doi.org/10.5281/zenodo.10864169" target="_blank" rel="nofollow noopener">https://doi.org/10.5281/zenodo.10864169</a>. </p>
Data from: Effects of pesticides on soil bacterial, fungal and protist communities, soil functions and crop quality in vineyards
<p>Pesticides can have unintentional effects on non-target organisms and change biotic communities. Such changes might be particularly important in soil microbial communities which drive many ecosystem functions and may affect crop quality. Here, we investigated, in a 3-year study, how vegetation control (by herbicide application) and soil copper content (from long-term copper-based fungicide application), affect biodiversity and the community structure of soil bacteria, fungi and protists and associated soil functions (respiration, decomposition) in Swiss vineyards. Furthermore, we determined the effects of these two management practices on grape quality as the most direct ecosystem service to farmers. Across all study years, the community composition of microorganisms was affected by herbicide application, however, a significant loss of operational taxonomic units (OTUs) was only observed in fungi and protists. Soil copper content reduced OTU richness of bacteria and protists in some years but had no significant effect on fungal richness. Copper changed the community composition in all three groups of soil microorganisms. While we found no effect of copper on soil functions, herbicide application reduced microbial respiration and biomass by about 39% and 45% respectively. However, decomposition rates remained virtually unchanged by any pesticide. Yeast assimilable nitrogen (YAN) levels in grape must were below the critical threshold of 140 mg/L in 40% of the vineyards without herbicide application and the variety Chasselas , whereas in vineyards with herbicide application it was only 20%. Synthesis and applications: Application of pesticides led to changes in richness and composition of soil microbial communities and directly reduced some soil functions (microbial biomass and respiration), but not all (decomposition). Some grape quality parameters can be indirectly enhanced by pesticide application, highlighting the trade-off between the interests of nature conservation and the interests of the farmer. Balancing these two diverging interests requires the establishment of alternative vineyard management allowing reduced pesticide application.</p>
Vector Field Histogram (VFH) video results for vineyard navigation and collision avoidance
<p><strong>Video Results for PhD Thesis</strong>: This video demonstrates the implementation of Vector Field Histogram (VFH) navigation for collision avoidance within crop rows. The simulation is conducted in Gazebo, utilizing a Husky robot to showcase efficient path planning and obstacle avoidance in an agricultural setting.</p>
UAV Canyelles Vineyard Dataset 2023-04-21
<p>The dataset includes the following components:</p> <ul> <li><strong>RGB</strong>: contains 342 RGB images captured using a DJI Mavic 3 Classic UAV. The images are stored in JPG format, with metadata that includes location information, camera settings and capture dates.</li> <li><strong>SHAPE</strong>: contains the shape file used in Metashape Agisoft to crop the point cloud, orthomosaics and DEM, ensuring a clear visualization of the vineyard rows.</li> <li><strong>POINTCLOUDS</strong>: includes both the raw and cropped point clouds, processed using Metashape Agisoft, and stored in XYZ format (.txt).</li> <li><strong>ORTHOMOSAICS</strong>: includes the original and cropped orthomosaic images, generated with Metashape Agisoft, in TIF format.</li> <li><strong>DEM</strong>: contains the original and cropped DEM images, also processed using Metashape Agisoft, and stored in TIF format.</li> </ul> <p>This data is aligned with the rest of <strong>UAV Canyelles Vineyard Datasets</strong> uploaded by Noumena (UC1), so different orthomosaics / pointclouds / DEM of different dates can be analyzed jointly for cropped and uncropped files. </p> <p>Data collection took place on April 21, 2023, in Canyelles, Catalonia, Spain. The UAV was manually flown at an altitude of 10 meters, ensuring sufficient frontal and side overlap between images. The weather was cloudy, with an average temperature of 18°C.</p>
UAV Canyelles Vineyard Dataset 2023-06-09
<p>The dataset includes the following components:</p> <ul> <li><strong>RGB(1-3)</strong>: contains 1454 RGB images captured using a DJI Mavic 3M UAV. The images are stored in JPG format, with metadata that includes location information, camera settings and capture dates.</li> <li><strong>SHAPE</strong>: contains the shape file used in Metashape Agisoft to crop the pointcloud, orthomosaics and DEM, ensuring a clear visualization of the vineyard rows.</li> <li><strong>POINTCLOUDS</strong>: includes both the raw and cropped pointclouds in RGB, NIR, G, RE and NDVI. All of them were processed using Metashape Agisoft and stored in XYZ format (.txt).</li> <li><strong>ORTHOMOSAICS</strong>: includes the original and cropped orthomosaics in RGB, NIR, G, RE and NDVI. All of them were generated using Metashape Agisoft and are in TIF format.</li> <li><strong>DEM</strong>: contains the original and cropped DEM images, also processed using Metashape Agisoft, and stored in TIF format.</li> </ul> <p>This data is aligned with the rest of <strong>UAV Canyelles Vineyard Datasets</strong> uploaded by Noumena (UC1), so different orthomosaics / pointclouds / DEM of different dates can be analyzed jointly for cropped and uncropped files. </p> <p>Data collection took place on June 9th, 2023, in Canyelles, Catalonia, Spain. The UAV was manually flown at an altitude of 12 meters, ensuring sufficient frontal and side overlap between images.</p>
Dataset: Efficiency of organic fungicides against the formation of Erysiphe necator chasmothecia in vineyards
<p>Data repository of the raw data for the data analysis of the article: "Efficiency of organic fungicides against the formation of <em>Erysiphe necator</em> chasmothecia in vineyards", published in Pest Management Science: https://onlinelibrary.wiley.com/doi/10.1002/ps.7487</p>
Figure 98. Four localities where Saratus hesperus has been found. 1, Fence near Canberra. 2, Vineyard near Canberra. 3 in Five new peacock spiders from eastern Australia (Araneae: Salticidae: Euophryini: Maratus Karsch 1878 and Saratus, new genus)
Figure 98. Four localities where Saratus hesperus has been found. 1, Fence near Canberra. 2, Vineyard near Canberra. 3, Enfield, NSW. 4, Girraween National Park, QLD. Photos 1-2 by Stuart Harris, 3-4 by Michael Doe.
Effect size data for the meta-analysis article ""Effects of vegetation management intensity on biodiversity and ecosystem services in vineyards: a meta-analysis"
<p>This Exel file includes the effect size dataset used for the statistical analysis for the paper "Effect of vegetation management intensity on biodiversity and ecosystem services in vineyards: a meta-analysis", which will be published in the Journal of Applied Ecology in 2018.</p> <p>This meta-analysis was conducted in the course of the project VineDivers (<a href="http://www.vinedivers.eu/">www.vinedivers.eu</a>) funded through the 2013-2014 BiodivERsA/FACCE-JPI joint call for research proposals, with the national funders: Austrian Science Fund (FWF), Spanish Ministry for Economy and Competitiveness (MINECO), French National Research Agency (ANR), Romanian Executive Agency for Higher Education, Research, Development and Innovation Funding (UEFISCDI) and Federal Ministry of Education and Research (BMBF/Germany). P. Batáry was supported by the German Research Foundation (DFG BA4438/2-1) and by the Economic Development and Innovation Operational Programme of Hungary (GINOP–2.3.2–15–2016–00019).</p> <p> </p>
Distributed temperature sensing and associated data - Martha's Vineyard Coastal Observatory 2014
<p>Distributed temperature sensing (DTS) and associated calibration data from deployment on the Martha's Vineyard inner shelf during summer 2014.</p> <p>Each zip file contains a readme.txt file describing the contents in detail. Further information on the study is detailed in:</p> <ul> <li>Connolly, T. P. and A. R. Kirincich (2019) High-resolution observations of subsurface fronts and alongshore bottom temperature variability over the inner shelf, Journal of Geophysical Research. doi:<a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2018JC014454">10.1029/2018jc014454</a></li> </ul> <p><strong>DTS_MVCO_xml.zip</strong> - original XML files created by the DTS instrument, one file per trace (~50 GB uncompressed)</p> <p><strong>DTS_MVCO_cal.zip</strong> - original text files containing temperature data used for calibrating the DTS instrument, as well as information on positions and timing from the DTS deployment</p> <p><strong>DTS_MVCO_nc.zip</strong> - processed DTS data and associated calibration data in NetCDF format</p>
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OpenNeuro
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