461 research outputs found

    The "missing link" 'Blaue Zimmettraube' reveals that 'Blauer Portugieser' and 'BlaufrÀnkisch' originated in Lower Styria

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    Parent offspring analysis already revealed genetic relationships for 'Blauer Portugieser' and 'BlaufrĂ€nkisch', sharing at each locus one allele with 'GrĂŒner Silvaner' and 'Weisser Heunisch', respectively. The missing second progenitor of 'Blauer Portugieser' and 'BlaufrĂ€nkisch' is a recently rediscovered black grapevine, called 'Blaue Zimmettraube'. It was found in the largest German wine growing area Rheinhessen. The same cultivar was detected as a single vine in Friuli, Italy and named SbulzĂŹna. The 'Blaue Zimmettraube', bearing female flowers, and thus the female parent in the crosses, was cultivated in the 19th century in Lower Styria together with 'GrĂŒner Silvaner' and 'Weisser Heunisch'. Because the 'Blaue Zimmettraube' did not exist in Austria and red wine production was fairly rare in that country before 1800, it is suspected that the cradle of 'Blauer Portugieser' and 'BlaufrĂ€nkisch' is in Lower Styria. Furthermore, according to chlorotype analysis, it turned out that 'Blauer GĂ€nsfĂŒsser' is the male parent of 'Blaue Zimmettraube' and thus the 'Blaue Zimmettraube' represents a veritable "missing link". To prove the genetic relationships the nine GrapeGen06-markers and additional forty microsatellite markers were applied. Likelihood analysis with allele frequencies of 22 SSR-markers from 772 cultivars revealed a very high degree of probability that the proposed parents are consistent, due to rare alleles inherited from 'Blaue Zimmettraube'. To investigate on the geographical origin of 'Blauer Portugieser' and 'BlaufrĂ€nkisch' historical Austrian and Styrian references were consulted

    Rpv14, a new genetic source for Plasmopara viticola resistance conferred by Vitis cinerea

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    A biparental population segregating for downy mildew resistance was studied to identify resistance linked molecular markers. The progeny of 202 individuals from a cross of V3125 (susceptible breeding line) with 'Börner' (resistant rootstock) was phenotyped in the field in four seasons and by evaluating artificially infected leaf discs. QTL mapping revealed a major resistance locus on chromosome 5 that explained up to 17.4 % of the phenotypic variance. This new resistance locus was named Rpv14. It was transmitted from the male grandparent V. cinerea Arnold to 'Börner' and is associated with the marker GF05-13

    Efficient identification, localization and quantification of grapevine inflorescences and flowers in unprepared field images using Fully Convolutional Networks

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    Yield and its prediction is one of the most important tasks in grapevine breeding purposes and vineyard management. Commonly, this trait is estimated manually right before harvest by extrapolation, which mostly is labor-intensive, destructive and inaccurate. In the present study an automated image-based workflow was developed for quantifying inflorescences and single flowers in unprepared field images of grapevines, i.e. no artificial background or light was applied. It is a novel approach for non-invasive, inexpensive and objective phenotyping with high-throughput.First, image regions depicting inflorescences were identified and localized. This was done by segmenting the images into the classes "inflorescence" and "non-inflorescence" using a Fully Convolutional Network (FCN). Efficient image segmentation hereby is the most challenging step regarding the small geometry and dense distribution of single flowers (several hundred single flowers per inflorescence), similar color of all plant organs in the fore- and background as well as the circumstance that only approximately 5 % of an image show inflorescences. The trained FCN achieved a mean Intersection Over Union (IOU) of 87.6 % on the test data set. Finally, single flowers were extracted from the "inflorescence"-areas using Circular Hough Transform. The flower extraction achieved a recall of 80.3 % and a precision of 70.7 % using the segmentation derived by the trained FCN model.Summarized, the presented approach is a promising strategy in order to predict yield potential automatically in the earliest stage of grapevine development which is applicable for objective monitoring and evaluations of breeding material, genetic repositories or commercial vineyards

    The use of molecular markers for pyramiding resistance genes in grapevine breeding

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    The practical application of pyramiding resistance genes by the use of molecular markers was investigated in a F1 progeny derived from the cross of VHR 3082-1-42 x ‘Regent’. VHR 3082-1-42 is a cross between Muscadinia rotundifolia x Vitis vinifera, backcrossed another four times with V. vinifera (PAUQUET et al. 2001). It carries the Run1-gene which causes resistance to powdery mildew and the Rpv1-gene which is related to resistance against downy mildew. Both genes were introduced from Muscadinia rotundifolia (BOUQUET et al. 2000; WIEDEMANN-MERDINOGLU et al. 2006). ‘Regent’ is a new cultivar with quantitative resistance against downy and powdery mildew (EIBACH and TÖPFER 2003) released in Germany in 1996 for commercial use. 119 individuals of the F1 progeny were screened with a molecular marker for the Run1-gene (DONALD et al. 2002), with two SSR-markers for the Rpv1-gene (WIEDEMANN-MERDINOGLU et al. 2006) and with several markers from ‘Regent’ that showed good correlation to powdery and downy mildew resistance (ZYPRIAN et al. 2002, SALAKHUTDINOV et al. 2003, AKKURT 2004, FISCHER et al. 2004, AKKURT et al. 2007). Phenotypic evaluation for downy mildew resistance was done by artificial inoculation of leaf discs, and for powdery mildew by natural infection in a greenhouse. Comparison of the phenotypic data with the results of the molecular marker analyses showed a clear correlation between the degree of resistance and the presence of the resistance related alleles. According to the phenotypic data, 20 genotypes of the offspring were free of powdery and downy mildew infections. Based on a marker-assisted evaluation, out of these 20 genotypes a subset of four carried all the resistance related alleles for powdery and downy mildew indicating that resistance genes from both parents were effectively combined.

    Grapevine DNA polymorphisms revealed by microsatellite-derived markers from soybean and rice

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    We report detection of DNA polymorphisms in grapevine by the use of microsatellite-flanking primer pairs from soybean and rice. These “cross species” microsatellite-derived markers were checked for their inheritance patterns in controlled grapevine crosses. They produced multiple bands that segregated and can be scored as individual genetic markers of dominant type. Employed in genetic mapping studies they offer advantages such as improved reproducibility in comparison to commonly used multi-locus marker systems like RAPDs and AFLPs.

    The prolific grape variety (Vitis vinifera L.) ‘Heunisch Weiss’ (= ‘Gouais blanc’): bud mutants, “colored” homonyms and further offspring

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    ‘Heunisch Weiss’ (syn. ‘Gouais blanc’) contributed to a considerable increase of our varietal assortment, including renowned varieties like ‘Chardonnay’ and ‘Riesling Weiss’. Three phenotypic variants of ‘Heunisch Weiss’ were discovered in the grapevine collection at the JKI Institute for Grapevine Breeding Geilweilerhof: (a) ‘Heunisch Dreifarbig’ (three coloured ‘Heunisch’; VIVC prime name ‘Heunisch Dreifarbig’) expressing intense anthocyanin coloration on shoots, inflorescences and leaf petioles before fruit set and even red berry skin at fruit set stage; (b) ‘Pekasore’ (VIVC prime name ‘Heunisch Rotgestreift’; red striped ‘Heunisch’;) with rose to red stripes on white berries and (c) the stenospermocarpic ‘Aspirant’ (VIVC prime name ‘Heunisch Weiss Seedless’). Four cultivars proving to be homonymous in relation to ‘Heunisch’ were investigated at 24 loci to determine their identity or relatedness to ‘Heunisch Weiss’, respectively. ‘Heunisch Schwarz’ turned out to be a ‘Heunisch Weiss’ offspring. No parent offspring relationship was detected for ‘Heunisch Rot’, ‘Haenisch Rot’ = ‘Pamid’, and ‘Heunisch Blau’ . Ampelographic description was carried out for some of the accessions to trace back historical evidences. In addition five new ‘Heunisch Weiss’ offsprings were identified and confirmed by analysing 35 nuclear microsatellite loci. The accession ‘Furmint Apiren’ turned out to be a seedless bud mutant of the ‘Heunisch Weiss’ offspring ‘Iordan’

    A simple, inexpensive and environmentally friendly method for high throughput DNA extraction from grapevine (Vitis spp.)

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    The extraction of DNA is a basic tool for molecular analyses, which is difficult for grapevine due to its content of secondary metabolites. In terms of purity and yield, DNA extraction kits are superior; however, they are also expensive. Here we describe an efficient protocol to re-use the DNeasy 96 Plant Kit from Qiagen GmbH (Hilden, Germany) by preparing homemade buffers and regenerating the commercial 96 column plates. Leaf tissue extractions of different grapevine samples resulted in genomic DNA with a high molecular weight and sufficient purity suitable for molecular studies like restriction assays or various amplification analyses. This high throughput method is especially economical and does not require the use of laboratory robotics for pipetting steps.

    Efficiency of Single Nucleotide Polymorphisms to improve a genetic map of complex pedigree grapevines

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    A set of 47 SNP (single nucleotide polymorphisms) markers (Cabezas et al. 2011) was tested for their usefulness to improve a genetic map from the cross of GF.GA‑52-42 x 'Solaris' previously established with SSR markers (Schwander et al. 2012). 55.3 % of the SNPs showed informative segregation and 26 SNP markers were localized on 16 of the 19 linkage groups of grapevine. Five chromosome regions with large gaps of recombining SSR markers could be equipped by positioning a SNP marker there. One SNP marker, VV10992, was found linked to the major resistance locus Rpv10 and should be applicable for marker-assisted selection

    HT-Phenotyping methods for yield parameters in grapevine

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