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108 results for “Vitis vinifera”
InnoVine WP3: 105 phenolic compound quantification of 2014 and 2015 mature grape berries from a core-collection of 279 irrigated and non-irrigated Vitis vinifera cultivars
<p>FP7/311775 InnoVine (Innovation in vineyard): Combining innovation in vineyard management and genetic diversity for a sustainable European viticulture</p> <p>WP3: Exploiting the genetic diversity in grapevine</p> <p>105 phenolic or related compounds, from 2014 and 2015 mature grape berries from a core-collection of 279 irrigated and non-irrigated <em>Vitis vinifera</em> cultivars, were quantified by UPLC-TQ-MRM Mass Spectrometry (Lambert M<em> et al., Molecules</em> <strong>2015</strong>, <em>20</em>(5), 7890-7914; doi:10.3390/molecules20057890 & Pinasseau L <em>et al.</em>, <em>Molecules</em> <strong>2016</strong>, <em>21</em>(10), 1409; doi:10.3390/molecules21101409).</p> <p>3 parameters were added:<br> - water/drought status (delta C13)<br> - sugar content (refractive index, brix degree)<br> - weight of 100 grape berries</p> <p>All plant material was collected at the Vassal repository: French National Grapevine Germplasm Collection, INRA Domaine de Vassal, 34340 Marseillan-Plage, France (Centre de Ressources Biologiques de la Vigne (CRB-Vigne) de Vassal-Montpellier).</p>
Effects of crown gall disease on natural microbiota of Vitis vinifera - genome annotations
<p>Young grapevines (Vitis vinifera) frequently die due to the crown gall (CG) disease induced by the plant pathogen Allorhizobium vitis (Rhizobiaceae). Virulent members of A. vitis harbour a tumor-inducing (Ti) plasmid and cause formation of CGs due to genes encoded on the T-DNA. Expression of the oncogenes by transformed host cells induce cell proliferation, metabolic and physiological changes. The CG produces opines uncommon to plants, which provide an important nutrient source for A. vitis harbouring opine catabolism enzymes. CGs host a defined bacterial community and the mechanisms establishing a CG-specific bacterial community are currently unknown. Thus, we were interested in whether genes homologous to those of the Ti-plasmid coexist in the genomes of the microbial species coexisting in CGs. We isolated eight bacterial strains from grapevine CGs, sequenced their genomes and tested their virulence and opine utilization ability in bioassays. In addition, the eight genome sequences were aligned to the sequences of a Ti-plasmid and seven published bacterial genomes, including closely related plant associated bacteria but not from CGs. Homologous genes for virulence and opine anabolism were only present in the virulent Rhizobiaceae. By contrast, homologs of the opine catabolism genes were present in all strains including the non-virulent members of the Rhizobiaceae and non-Rhizobiaceae, indicating horizontal gene transfer of the opine degradation cluster from virulent to non-virulent strains. These results along with those of the opine utilization assay support the important role of opine utilization for co-colonization of virulent and non-virulent bacteria in CGs, thereby shaping the CG community.</p> <p>This dataset contains the prokka annotations of the genomes as used in "Opportunistic bacteria of grapevine crown galls are equipped with the genomic repertoire for opine utilization"</p>
The complete reference genome for grapevine (Vitis vinifera L.) genetics and breeding
<div>PN40024, a highly homozygous inbred line originating from ‘Helfensteiner’, was used for T2T genome assembly. In total, 21 Gb (21 024 461 524 bp, ∼42× coverage) HiFi reads were generated by the PacBio platform. For the preliminary assembly, hifiasm was used to assemble the HiFi reads. We then used MUMmer and the 12X.v0 genome version (V. vinifera genome assembly 12X.v0 to order the 38 contigs into 19 chromosomes.</div> <p> The PN_T2T genome size was finally generated (494.87 Mb), being 69 Mb longer than 12X.v0 using the same statistical method. The k-mer metric was used to evaluate genomic homozygosity, estimated at 99.8%. The BUSCO for this genome is up to 98.5%.</p> <p>The PN40024.T2T genome assembly: PN.fa</p> <p>The PN40024.T2T gene annotation: PN_T2T.v5.1.gff3</p> <p>The PN40024.T2T TE annotation: PN_T2T_TE.gff</p> <p>The PN40024.T2T centromere annotation: PN.trf.gff3</p> <p>The PN40024.T2T protein sequence: PN_protein.fa</p> <p>The PN40024.T2T cds sequence: PN40024.cds.fa</p> <p>Comparison of gene annotation among PN_T2T and PN_T2T.v5.1, 12X.v0, 12X.v2, PN40024.v4, PN40024.v4.1: correlation.list.txt</p> <p>Mitochondrial assembly sequence of PN40024: PN_T2T_mit.fa</p> <p>Annotation of mitochondrial assembly for PN40024:PN_T2T_mit.gff3</p> <p>Chloroplast assembly sequence of PN40024: PN_T2T_chl.fa</p> <p>Annotation of chloroplast assembly for PN40024: PN_T2T_chl.gff3</p> <p>Citation: </p> <p>Please cite this paper when using the data of PN_T2T for your publications.</p> <p>Xiaoya Shi, Shuo Cao, Xu Wang, Siyang Huang, Yue Wang, Zhongjie Liu, Wenwen Liu, Xiangpeng Leng, Yanling Peng, Nan Wang, Yiwen Wang, Zhiyao Ma, Xiaodong Xu, Fan Zhang, Hui Xue, Haixia Zhong, Yi Wang, Kekun Zhang, Amandine Velt, Komlan Avia, Daniela Holtgräwe, Jérôme Grimplet, José Tomás Matus, Doreen Ware, Xinyu Wu, Haibo Wang, Chonghuai Liu, Yuling Fang, Camille Rustenholz, Zongming Cheng, Hua Xiao, Yongfeng Zhou, The complete reference genome for grapevine (<em>Vitis vinifera</em> L.) genetics and breeding, <em>Horticulture Research</em>, Volume 10, Issue 5, May 2023, uhad061, <a href="https://doi.org/10.1093/hr/uhad061">https://doi.org/10.1093/hr/uhad061</a></p>
Herbarium specimen image of Vitis vinifera L., part of the collection of Meise Botanic Garden
Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published.<br><br>Content of this deposition:<br><br>- A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values.<br>- A JPEG image file of the scanned herbarium sheet.<br>- A lossless TIFF image from which the JPEG image has been derived.
Forcing vine regrowth in vitis vinifera cv. touriga nacional at Douro region (datasets)
<p>Datasets related to the trials performed during 2018 and 2019 in Douro Superior sub-region on 'Touriga Nacional’ grape, at Quinta do Ataide on Tou, in the course of the VISCA project. This data was used to the prepare the article with the DOI 10.5281/zenodo.3568194 (Forcing vine regrowth in vitis vinifera cv. touriga nacional at Douro region). For each year (2018 and 2019), it includes data on : fertility; harvested quantity; Maturation; ProDrawn leaf water potential quantity.</p> <p>The same data was also used for the article "EFEITO DA INTERVENÇÃO EM VERDE CROP FROCING NA CASTA TOURIGA NACIONAL", DOI 10.5281/zenodo.3686023</p> <p>These datasets are provided as part of the open access policy of VISCA project which is participating to the Open Research Data Pilot (ORDP) initiated in H2020, in particular for data used in scientific publications issued during the lifetime of the project.</p>
MicroCT scans of sun and shade grown leaves of Cabernet Sauvignon and Blaufränkisch grapevine (Vitis vinifera L.) cultivars
<p>Image data set of sun and shade-grown leaves of Cabernet Sauvignon (CS) and Blaufränkisch (BF) grapevine (Vitis vinifera L.) cultivars.</p> <p>When using this dataset, please cite:</p> <blockquote> <p>Théroux-Rancourt G, Herrera C, Voggeneder K, Luijken N, Nocker L, Savi T, Scheffknecht S, Schneck M, Tholen D. (accepted) Analyzing anatomy over three dimensions unpacks the differences in mesophyll diffusive area between sun and shade Vitis vinifera leaves. AoB Plants</p> </blockquote> <p> </p> <p><strong>Data acquisition methodology</strong></p> <p>Plants were brought to the TOMCAT tomographic beamline of the Swiss Light Source at the Paul Scherrer Institute (Villigen, Switzerland) in pots (Cabernet Sauvignon (CS)) or as cut shoots with the cut end placed in water (Blaufränkisch (BF)). Before scanning, a leaf was cut from the stem and a thin strip of ~1.5 mm width and 1.5 cm length was cut in between apparent higher-order veins, immediately wrapped in polyimide tape and inserted into a styrofoam block glued with wax onto a holder. Three (CS) or two (BF) strips were cut at different locations on the leaf surface to ensure within-leaf replications and to get better leaf-level averages. The strip was immediately scanned by imaging 1801 projections of 100 ms under a beam energy of 21 keV and magnified using a 40x (CS) or 20x (BF) objective, yielding respective final voxel sizes of 0.1625 µm (field of view: ~416x416x312 µm) and 0.325 µm (field of view: ~832x832x624 µm). Scanned projections were reconstructed to cross-sectional view using both absorption (gridrec; Marone <em>et al.</em> 2012) and phase contrast enhancement (Paganin <em>et al.</em> 2002) reconstructions.</p> <p><br> <br> <strong>Dataset description</strong></p> <p>After aligning the stacks to be parallel to the image edges using ImageJ (Schneider <em>et al.</em> 2012), at least nine slices were hand labeled using a graphics pen display tablet to precisely segment the background, the epidermis, and the vasculature. The mesophyll cells and the intercellular airspace were segmented by thresholding each absorption and phase contrast scan to maximize airspace volume (background) and taking care to avoid false segmentation within the cells (i.e. false segmentation of airspace). The hand-labeled slices were then used to automatically segment the whole stack using a Python-based random-forest machine learning approach (Théroux-Rancourt, Jenkins, <em>et al.</em> 2020).</p> <p> </p> <p><strong>File naming convention</strong></p> <p>For all stacks, files start with:<br> <em>Cultivar_Treatment_Plantn_leaf_N_</em></p> <ul> <li>Cultivar: <em>CS</em> for Cabernet Sauvignon, <em>BF</em> for Blaufränkisch</li> <li>Treatment: <em>Sun</em> for plants grown under high light, <em>Shade</em> for plants grown under low light</li> <li>Plantn: Plant number; 1-6 for CS, 1-5 for BF</li> <li>leaf: Leaf number; 1-4</li> </ul> <p><em>N</em> specifies the type of stack:</p> <ul> <li><em>GRID</em> (gridrec reconstruction)</li> <li><em>PAGANIN</em> (phase contrast enhancement reconstruction)</li> <li><em>labelled-stack</em> (hand labeled slices / ground truth; stacks have been hand labeled in cross-sectional view.)</li> <li><em>SEGMENTED</em> (automatically segmented stack using random-forest machine learning approach)</li> <li><em>STOMATAL_REGIONS_BBOX_CROPPED</em> (Stack with individually segmented stomatal vaporsheds, i.e. airspace closest to a stoma. The stack has been cropped in paradermal view around the stomata closest to the stack's edges, i.e. a bounding box (BBOX) with stomatal vaporsheds fully enclosed).</li> </ul> <p>All stacks are provided as 8-bit grayscale TIF files. Stacks have been hand labeled in cross-sectional view.</p> <p> </p> <p><strong>Plant material and growth conditions </strong></p> <p>The experiment was carried out over two consecutive years, in 2018 and 2019, at the facilities of BOKU UFT (Tulln, Austria). In the first year, rooted grafts of <em>Vitis vinifera </em>‘Cabernet Sauvignon’ (clone 191E) on 101-14 rootstock (hereafter named CS) were acquired from a local nursery (<em>Reben Iby</em>, Neckenmarkt, Austria). In the second year, rooted grafts of <em>Vitis vinifera </em>‘Blaufränkisch’ (clone 13-3 GM) on 5 BB rootstock (hereafter named BF) were acquired from the same nursery. Blaufränkisch is known to have originated from Lower Styria (present day Styria, Slovenia, Maul <em>et al. </em>2016) and to be genetically different from Cabernet Sauvignon (Magris <em>et al. </em>2021), which originated in the Bordeaux region in France.</p> <p>The rooted grafts were planted in 7-L pots and allowed to grow in a glasshouse without any environmental control. For CS, nutrient-rich, sieved vineyard soil mixed with perlite (3:1 ratio) was used, while for BF pots were filled with commercial pot substrate containing slow release fertilizer (10 g pot-1, 15-5-20 NPK “Entec vino”). Pots were watered to pot capacity automatically every day. Clones were planted June 1 and April 1 in the first and second year, respectively. When all the plants had at least three mature leaves on one shoot, plants were pruned so that only one dominant shoot remained. To ensure that only leaves fully developed under different light conditions were used for further analyses, the last developing leaf below the tip was marked before moving half of the plants to the shaded environment (on June 29, 2018 for CS and on April 18, 2019 for BF). For the shade treatment, a tent of about 2 m (height) x 1.5 m (width) x 1.5 m (depth) was made from black polypropylene cloth (HaGa-Welt GmbH & Co. KG, Elze, Germany), resulting in a 60% reduction in photosynthetic photon flux density (PPFD). A spectrometer (FLAME-S-VIS- ES, Ocean Optics Inc. Largo, USA) was used to confirm that under both light conditions, relative differences in the contribution of red, green blue and far-red light to the total PPFD were below 5% (i.e. spectrally neutral shade).</p> <p>During the week before synchrotron microCT scanning (last week of August in 2018 and first week of September in 2019), one mature leaf per plant was selected at least three leaves above the previously mentioned mark indicating the last developing leaf at the start of the shade treatment. The measured leaves were estimated to be about one month old, resulting in an average daily light integral (DLI) of 30 (CS sun), 12 (CS shade), 24 (BF sun), and 10 (BF shade) mol m<sup>-2</sup> day<sup>-1</sup>. These estimates were computed using solar radiation measured at a weather station a few meters from the glasshouse, and using PPFD values measured inside the glasshouse. Average daily PPFD was below 700 μmol m<sup>-2</sup> s<sup>-1</sup> under full light, with maximum recorded values at leaf level of ~1200 μmol m<sup>-2</sup> s<sup>-1</sup> under full light and ~500 μmol m<sup>-2 </sup>s<sup>-1</sup> under shade, i.e. ~60% reduction.</p> <p> </p> <p><strong>References</strong></p> <p><strong>Marone F, Stampanoni M</strong>. <strong>2012</strong>. Regridding reconstruction algorithm for real-time tomo- graphic imaging. <em>J. Synchrotron Radiat. </em><strong>19</strong>: 1029–1037.</p> <p><strong>Paganin D, Mayo SC, Gureyev TE, Miller PR, Wilkins SW</strong>. <strong>2002</strong>. Simultaneous phase and amplitude extraction from a single defocused image of a homogeneous object. <em>J. Microsc. </em><strong>206</strong>: 33–40.</p> <p><strong>Schneider CA, Rasband WS, Eliceiri KW</strong>. <strong>2012</strong>. NIH Image to ImageJ: 25 years of image analysis. <em>Nat. Methods </em><strong>9</strong>: 671–675.</p> <p><strong>Théroux-Rancourt G, Jenkins MR, Brodersen CR, McElrone A, Forrestel EJ, Earles JM</strong>. <strong>2020</strong>. Digitally deconstructing leaves in 3D using X-ray microcomputed tomography and machine learning. <em>Appl. Plant Sci. </em><strong>8</strong>: e11380.</p>
Vitis vinifera L. (BR0000010812150)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Vitis vinifera L. (BR0000010812211)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Vitis vinifera L. (BR0000012209347)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Vitis vinifera L. (BR0000010812181)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Vitis vinifera L. (BR0000012556571)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Vitis vinifera L. (BR0000024921183)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Vitis vinifera L. (BR0000012185290)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Vitis vinifera L. (BR0000010811856)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Vitis vinifera L. (BR0000010811887)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Vitis vinifera L. (BR0000010811825)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Vitis vinifera L. (BR0000024572903)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Vitis vinifera L. (BR0000024921176)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Vitis vinifera L. (BR0000012543762)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Vitis vinifera L. (BR0000012563227)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
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