Abstract A major aim in grapevine breeding is the provision of cultivars resistant to downy mildew. As Plasmopara viticola produces sporangia on abaxial surface susceptible cultivars, disease symptoms both leaf sides may be detected and quantified by technical sensors. The response ‘Mueller-Thurgau’, ‘Regent’, ‘Solaris’, which differ resistance P. , was characterized under controlled conditions using hyperspectral Spectral reflectance suitable differentiate between non-infected bicolored...

Due to its perennial nature and size, the acquisition of phenotypic data in grapevine research is almost exclusively restricted field done by visual estimation. This kind evaluation procedure limited time, cost subjectivity records. As a consequence, objectivity, automation more precision are needed increase number samples, manage repositories, enable genetic new traits and, therefore, efficiency plant research. In present study, an automated phenotyping pipeline was setup applied plot...

In grapevine research the acquisition of phenotypic data is largely restricted to field due its perennial nature and size. The methodologies used assess morphological traits phenology are mainly limited visual scoring. Some measurements for biotic abiotic stress, as well quality assessments, done by invasive measures. new evolving sensor technologies provide opportunity perform non-destructive evaluations using different phenotyping platforms. One biggest technical challenges grapevines...

Wine growers prefer cultivars with looser bunch architecture because of the decreased risk for rot. As a consequence, grapevine breeders have to select seedlings and new regard appropriate traits. Bunch is mosaic different single traits which makes phenotyping labor-intensive time-consuming. In present study, fast high-precision pipeline was developed. The optical sensor Artec Spider 3D scanner (Artec 3D, L-1466, Luxembourg) used generate dense point clouds bunches under lab conditions an...

The demand for high-throughput and objective phenotyping in plant research has been increasing during the last years due to large experimental sites. Sensor-based, non-invasive automated processes are needed overcome phenotypic bottleneck, which limits data volumes on account of manual evaluations. A major challenge sensor-based vineyards is distinction between grapevine foreground field background – this especially case red-green-blue (RGB) images, where similar color distributions occur...

Warm and moist weather conditions during berry ripening provoke Botrytis cinerea (B. cinerea) causing notable bunch rot on susceptible grapevines with the effect of reduced yield wine quality. Resistance donors genetic loci to increase B. resistance are widely unknown. Promising traits represented by physical features like thickness permeability grape cuticle. Sensor-based phenotyping methods or markers rare for such traits. In present study, simple-to-handle I-sensor was developed. The...

Bunch compactness (BC) is a complex, multi-trait characteristic that has been studied mostly in the context of wine grapes, with table grapes being scarcely considered. As these groups have marked phenotypic and genetic differences, including BC, study this trait reported here using genetically diverse collection 116 Vitis vinifera L. cultivars lines enriched for over two seasons. For this, 3D scanning-based morphological data were combined ground measurements 14 BC-related traits, observing...

Botrytis bunch rot is one of the economically most important fungal diseases in viticulture (aside from powdery mildew and downy mildew). So far, no active defense mechanisms resistance loci against necrotrophic pathogen are known. Since long, breeders mostly selecting phenotypically for loose grape bunches, which recently evident trait to decrease infection risk rot. This study focused on plant phenomics multiple traits by applying fast sensor technologies measure berry impedance (Z REL ),...

QTL-analysis (quantitative trait loci) and marker development rely on efficient phenotyping techniques. Objectivity precision of a phenotypic data evaluation is crucial but time consuming. In the present study high-throughput image interpretation tool was developed to acquire automatically number, size, volume grape berries from RGB (red-green-blue) images. Individual one cluster were placed black construction (300 x 300 mm) take top. The dataset with an arbitrary number images runs using...

Yield and its prediction is one of the most important tasks in grapevine breeding purposes vineyard management. Commonly, this trait estimated manually right before harvest by extrapolation, which mostly labor-intensive, destructive inaccurate. In present study an automated image-based workflow was developed for quantifying inflorescences single flowers unprepared field images grapevines, i.e. no artificial background or light applied. It a novel approach non-invasive, inexpensive objective...

Abstract Background Grapevine cultivars of the Pinot family represent clonally propagated mutants with major phenotypic and physiological differences, such as different colour or shifted ripening time, well changes in important viticultural traits. Specifically, ‘Pinot Noir’ (PN) Noir Precoce’ (PNP, early ripening) flower at same but vary beginning berry (veraison) and, consequently, harvest time. In addition to genotype, seasonal climatic conditions (i.e. high temperatures) also affect...

The evaluation of phenotypic characters grapevines is required directly in vineyards and strongly limited by time, costs the subjectivity person charge. Sensor-based techniques are prerequisite order to allow non-invasive phenotyping individual plant traits, increase quantity object records reduce error variation. Thus, a Prototype-Image-Acquisition-System (PIAS) was developed for semi-automated capture geo-referenced images an experimental vineyard. Different strategies were tested image...

Background and Aims Vine balance is defined as a relation between vegetative (mass of dormant pruning wood) generative (yield) growth. For grapevine breeding, emphasis usually placed on the evaluation individual seedlings. In this study, we calculated mass wood with assistance an automated image-based method for estimating pixel area wood. The digital images in combination depth map calculation image segmentation new non-invasive tool objective data acquisition. Methods Results proposed was...

In grapevine breeding, loose grape bunch architecture is one of the most important selection traits, contributing to an increased resilience towards Botrytis rot. Grape mainly influenced by berry number, size, total volume, and width length. For objective, precise, high-throughput assessment these architectural 3D imaging sensor Artec® Spider was applied gather dense point clouds visible side bunches directly in field. Data acquisition field much faster non-destructive comparison lab...

Semi minimal pruned hedge (SMPH) is a time and cost saving grapevine training system, which becoming more popular in German viticulture. In this study we compared the canopy architecture its effect on microclimate of SMPH trained grapevines with those plants vertical shoot positioning (VSP). We detected 3 % points higher humidity 0.9 °C lower mean temperature within complex vines to VSP. Moreover, investigated influence differing microclimate, bunch architecture, as well berry skin...

Traditional wine growing regions are increasingly endangered by climatic alterations. One promising approach to mitigate advancing climate change could be an increase of soil organic matter. Here, especially subsoils interest as they provide higher carbon storage potential than topsoils. In this context, vineyard particularly suitable since deeply cultivated once before planting and afterwards, left at rest for several decades due the perennial nature grapevines.For purpose, a biochar...

A precise count of flower number per inflorescence is essential to characterize the reproductive behavior a vine. Previous efforts automatize this process by image-based technologies have failed in development universal system that can be applied multiple grapevine cultivars, or they been tested set inflorescences narrow morphological diversity. Here, we developed an alternative general method open-source platform Fiji for nondestructive counting visible flowers red-green-blue (RGB) images,...

Automated image interpretation is a powerful instrument for the acquisition of objective and precise phenotypic data with high throughput. Cluster length, cluster width, berry size compactness are four important traits impact on morphology, health status yield. For image-based evaluation this grapevine morphology traits, automated Analysis Tool (CAT) was developed in Matlab®. The comparison reference measurements CAT ratings 100 ?Riesling? ?Pinot Noir? showed significant correlation r=0.94...