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Dataset results
15 results for “Viticulture”
Data for "Crop Diversification in Viticulture with Aromatic Plants: Effects of Intercropping on Grapevine Productivity in a Steep-Slope Vineyard in the Mosel Area, Germany"
<p>This dataset is corresponding to an open-access article named "Crop Diversification in Viticulture with Aromatic Plants: Effects of Intercropping on Grapevine Productivity in a Steep-Slope Vineyard in the Mosel Area, Germany" published in Agriculture (https://www.mdpi.com/2077-0472/11/2/95; <a href="https://doi.org/10.3390/agriculture11020095">https://doi.org/10.3390/agriculture11020095</a>), funded by the European Commission Horizon 2020 project Diverfarming [grant agreement 728003]. </p>
Precision viticulture dataset for detailed vineyard mapping composed of geotagged smartphone ground images, phytosanitary status, UAV orthomosaics, 3D point clouds, and RTK GNSS data - Northern Spain, July 2022
<p>This dataset offers a rich multimodal collection of data from vineyards, designed to enhance agricultural research with a focus on vineyard management and disease monitoring. It includes geotagged smartphone ground images in ".7z" format for detailed plant-level analysis, a ".csv" file detailing plants' phytosanitary status for health assessment, UAV-derived 3D Point Clouds and orthomosaics in ".las" and ".tiff" formats for aerial landscape views, and RTK GNSS data in ".shp" format for precise plant geolocations.</p> <p>This dataset can be combined with other datasets to enable a comprehensive view of the vineyards and improve its value:</p> <div> <ul> <li>Ariza-Sentís, Mar, Sergio Vélez, and João Valente. ‘Dataset on UAV RGB Videos Acquired over a Vineyard Including Bunch Labels for Object Detection and Tracking’. <em>Data in Brief</em> 46 (February 2023): 108848. <a href="https://doi.org/10.1016/j.dib.2022.108848">https://doi.org/10.1016/j.dib.2022.108848</a>.</li> <li>Vélez, Sergio, Mar Ariza-Sentís, and João Valente. ‘VineLiDAR: High-Resolution UAV-LiDAR Vineyard Dataset Acquired over Two Years in Northern Spain.’ <em>Data in Brief</em>, October 2023, 109686. <a href="https://doi.org/10.1016/j.dib.2023.109686">https://doi.org/10.1016/j.dib.2023.109686</a>.</li> <li> <div> <div>Vélez, Sergio, Mar Ariza-Sentís, and João Valente. ‘Dataset on Unmanned Aerial Vehicle Multispectral Images Acquired over a Vineyard Affected by Botrytis Cinerea in Northern Spain’. <em>Data in Brief</em> 46 (February 2023): 108876. <a href="https://doi.org/10.1016/j.dib.2022.108876">https://doi.org/10.1016/j.dib.2022.108876</a>.</div> <div> </div> </div> </li> </ul> </div>
Bioclimatic Indeces for Viticultural Zoning in Marchfeld (AU)
<p>This dataset includes 6 Bioclimatic indeces for Marchfeld area (AU), used as part of basic data to compute a viticultural zoning in GIS environment. The spatialized indeces provided as raster layers, have been calculated starting from ERA5-LAND reanalysis dataset with horizontal resolution of 9 km and daily temporal resolution. The dataset temporal extention starts from 1981 up to 3 months before the present. The indeces have been calculated considering 10 years of daily data from 2010 to 2020 to obtain an average year. The meteorological variables used are: 2m temperature (°C) (min., mean, max.) and total precipitation (mm). </p> <p> The potential solar radiation (whm<sup>-2</sup>) has been calculated with GIS software by processing a Digital Elevation Model with 10m spatial resolution.</p>
Bioclimatic Indeces for Viticultural zoning in Campania region (IT)
<p>This dataset includes 6 Bioclimatic indeces for Campania region, used as part of basic data to compute the regional viticultural zoning in GIS environment. The spatialized indeces provided as raster layers, have been calculated starting from ERA5-LAND reanalysis dataset with horizontal resolution of 9 km and daily temporal resolution. The dataset temporal extention starts from 1981 up to 3 months before the present. The indeces have been calculated considering 10 years of daily data from 2010 to 2020 to obtain an average year. The meteorological variables used are: 2m temperature (°C) (min., mean, max.) and total precipitation (mm). </p> <p> The potential solar radiation (whm<sup>-2</sup>) has been calculated with GIS software by processing a Digital Elevation Model with 5m spatial resolution.</p> <p> </p>
Figure 1 in Positioning entomopathogenic nematodes for the future viticulture: exploring their use against biotic threats and as bioindicators of soil health
Figure 1. Example of the progression of authorized phytosanitary product usage in Spain against the most important diseases and pests of vineyards during the last decade. The size of each circle is proportional to the total number of phytosanitary authorized against each biotic threat.1
FIGURE 3 in Diversity Of Mites (Acari) In Vineyard Agroecosystems (Vitis Vinifera) In Two Viticultural Regions Of Rio Grande Do Sul State, Brazil
FIGURE 3: Bray-Curtis clustering analysis dendrograms of mite communities observed on grapevine (A) and on non-cultivated plants (B), in four plots planted with Cabernet Sauvignon (CS) or Pinot Noir (PN), in Bento Gonçalves (BG) and Candiota (CA) regions, Rio Grande do Sul.
FIGURE 2 in Diversity Of Mites (Acari) In Vineyard Agroecosystems (Vitis Vinifera) In Two Viticultural Regions Of Rio Grande Do Sul State, Brazil
FIGURE 2: Bray-Curtis clustering analysis dendrograms of mite communities observed in four plots (agroecosystems) planted with Cabernet Sauvignon (CS) or Pinot Noir (PN) in the two vine-producing regions Bento Gonçalves (BG) and Candiota (CA), Rio Grande do Sul: A – All mite families; B – Phytoseiidae; C – Stigmaeidae; D – Eriophyidae.
FIGURE 1 in Diversity Of Mites (Acari) In Vineyard Agroecosystems (Vitis Vinifera) In Two Viticultural Regions Of Rio Grande Do Sul State, Brazil
FIGURE 1: Abundance of main mite species found on grapevine in Bento Gonçalves (A - Cabernet Sauvignon; B - Pinot Noir) and Candiota (C - Cabernet Sauvignon; D - Pinot Noir) municipalities, Rio Grande do Sul, Brazil.
Supplementary material 1 from: Biniari K, Daskalakis I, Bouza D, Stavrakaki M (2019) Comparative study of qualitative and quantitative characters of grape cultivar 'Mavrodafni' (Vitis vinifera L.) and 'Renio' grown in different regions of the Protected Designation of Origin Mavrodafni Patras. Viticulture Data Journal 1: e37852. https://doi.org/10.3897/vdj.1.e37852
<p>This is the raw dataset of the measurements performed on the samples collected from the two varieties from the different locations. There are three repetitions per measurement and no statistical analysis has been performed.</p>
Supplementary material 1 from: Verarou V, Stavrakaki M, Daskalakis I, Bouza D, Biniari K (2020) Effect of the plot variability on the qualitative and quantitative characteristics of the berry's skins and seeds of grape cultivar Agiorgitiko (Vitis vinifera L.). Viticulture Data Journal 2: e46873. https://doi.org/10.3897/vdj.2.e46873
Agiorgitiko quality characteristics measurements
Figure 4 in Positioning entomopathogenic nematodes for the future viticulture: exploring their use against biotic threats and as bioindicators of soil health
Figure 4. Evaluation of the impact of cover crops (CC) in the entomopathogenic nematode (EPN) soil food web in a Spanish vineyard. A. Impact in the presence and activity of native EPNs. B. Presence of natural enemies (nematophagous fungi and ectoparasitic bacteria) and competitors for the resource (Free-living nematodes) (Data from Blanco-Pérez et al., 2020, modified for this figure).
Figure 3. Preventive inhibition growth effect against Botrytis cinerea over grapevine leaves three days after the infection. A in Positioning entomopathogenic nematodes for the future viticulture: exploring their use against biotic threats and as bioindicators of soil health
Figure 3. Preventive inhibition growth effect against Botrytis cinerea over grapevine leaves three days after the infection. A. Destilled water (control treatment). B. Xenorhabdus nematophilus natural products treatment.
Supplementary material 1 from: Ruland KT, Montague T, Helwi P (2023) Impact of hail-netting on Vitis vinifera L. canopy microclimate, leaf gas exchange, fruit quality, and yield in a semi-arid environment. Viticulture Data Journal 555: e108805. https://doi.org/10.3897/vdj.555.e108805
Hail-netting on vines
Supplementary material 3 from: Ruland KT, Montague T, Helwi P (2023) Impact of hail-netting on Vitis vinifera L. canopy microclimate, leaf gas exchange, fruit quality, and yield in a semi-arid environment. Viticulture Data Journal 555: e108805. https://doi.org/10.3897/vdj.555.e108805
Compact canopy under hail-netting
Supplementary material 2 from: Ruland KT, Montague T, Helwi P (2023) Impact of hail-netting on Vitis vinifera L. canopy microclimate, leaf gas exchange, fruit quality, and yield in a semi-arid environment. Viticulture Data Journal 555: e108805. https://doi.org/10.3897/vdj.555.e108805
Li-Cor-6400 machines below hail-netting
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