Individual Grapevines Research Articles

Versatile method for grapevine row detection in challenging vineyard terrains using aerial imagery

Accurate detection and differentiation of grapevine canopies from other vegetation, along with individual grapevine row identification, pose significant challenges in precision viticulture (PV), especially within irregularly structured vineyards shaped by natural terrain slopes. This study employs aerial imagery captured by unmanned aerial vehicles (UAVs) and introduces an image processing methodology that relies on the orthorectified raster data obtained through UAVs. The proposed method adopts a data-driven approach that combines visible indices and elevation data to achieve precise grapevine row detection. Thoroughly tested across various vineyard configurations, including irregular and terraced landscapes, the findings underscore the method’s effectiveness in identifying grapevine rows of diverse shapes and configurations. This capability is crucial for accurate vineyard monitoring and management. Furthermore, the method enables clear differentiation between inter-row spaces and grapevine vegetation, representing a fundamental advancement for comprehensive vineyard analysis and PV planning. This study contributes to the field of PV by providing a reliable tool for grapevine row detection and vineyard feature classification. The proposed methodology is applicable to vineyards with varying layouts, offering a versatile solution for enhancing precision viticulture practices.

Non-destructive quantification of key quality characteristics in individual grapevine berries using near-infrared spectroscopy.

It is crucial for winegrowers to make informed decisions about the optimum time to harvest the grapes to ensure the production of premium wines. Global warming contributes to decreasing acidity and increasing sugar levels in grapes, resulting in bland wines with high contents of alcohol. Predicting quality in viticulture is thus pivotal. To assess the average ripeness, typically a sample of one hundred berries representative for the entire vineyard is collected. However, this process, along with the subsequent detailed must analysis, is time consuming and expensive. This study focusses on predicting essential quality parameters like sugar and acid content in Vitis vinifera (L.) varieties 'Chardonnay', 'Riesling', 'Dornfelder', and 'Pinot Noir'. A small near-infrared spectrometer was used measuring non-destructively in the wavelength range from 1 100 nm to 1 350 nm while the reference contents were measured using high-performance liquid chromatography. Chemometric models were developed employing partial least squares regression and using spectra of all four grapevine varieties, spectra gained from berries of the same colour, or from the individual varieties. The models exhibited high accuracy in predicting main quality-determining parameters in independent test sets. On average, the model regression coefficients exceeded 93% for the sugars fructose and glucose, 86% for malic acid, and 73% for tartaric acid. Using these models, prediction accuracies revealed the ability to forecast individual sugar contents within an range of ± 6.97 g/L to ± 10.08 g/L, and malic acid within ± 2.01 g/L to ± 3.69 g/L. This approach indicates the potential to develop robust models by incorporating spectra from diverse grape varieties and berries of different colours. Such insight is crucial for the potential widespread adoption of a handheld near-infrared sensor, possibly integrated into devices used in everyday life, like smartphones. A server-side and cloud-based solution for pre-processing and modelling could thus avoid pitfalls of using near-infrared sensors on unknown varieties and in diverse wine-producing regions.

Genetic Diversity of Grapevine Virus A in Three Australian Vineyards Using Amplicon High Throughput Sequencing (Amplicon-HTS).

Shiraz disease (SD) is one of the most destructive viral diseases of grapevines in Australia and is known to cause significant economic loss to local growers. Grapevine virus A (GVA) was reported to be the key pathogen associated with this disease. This study aimed to better understand the diversity of GVA variants both within and between individual SD and grapevine leafroll disease (LRD) affected grapevines located at vineyards in South Australia. Amplicon high throughput sequencing (Amplicon-HTS) combined with median-joining networks (MJNs) was used to analyze the variability in specific gene regions of GVA variants. Several GVAII variant groups contain samples from both vineyards studied, suggesting that these GVAII variants were from a common origin. Variant groups analyzed by MJNs using the overall data set denote that there may be a possible relationship between variant groups of GVA and the geographical location of the grapevines.

Health Status of Ready-to-Plant Grapevine Nursery Material in Canada Regarding Young Vine Decline Fungi.

Young vine decline (YVD), caused by several taxonomically different fungi, results in the decline and death of grapevines within a few years after planting. Infection can occur in nursery mother blocks and/or at several stages in the nursery propagation process, but the final plant material may remain asymptomatic. Four nurseries that sell ready-to-plant grapevines in Canada were sampled to evaluate the health status with regard to YVD fungi, including Botryosphaeriaceae spp., Cadophora luteo-olivacea, Dactylonectria macrodidyma, Dactylonectria torresensis, Phaeoacremonium minimum, and Phaeomoniella chlamydospora. Plants representing three cultivars, 'Chardonnay', 'Merlot', and 'Pinot noir', either grafted onto '3309C' rootstock or self-rooted, were provided by the nurseries. Samples from the roots, base of the rootstock or self-rooted cultivar, graft-union, and scion were collected from each plant. DNA was extracted, and the total abundance of each fungus was quantified using Droplet Digital PCR. Results revealed that 99% of plants harbored at least one of the fungi studied, with a mean of three different fungal species that were present per grapevine. Droplet Digital PCR results showed that the abundance of the different fungi significantly varied between different sections of each plant, individual plants for each cultivar, and cultivars from the same nursery. Necrosis measurements were recorded from the base of the rootstock or self-rooted cultivars and did not correlate with fungal abundance recorded in that section for each grapevine, but necrosis was consistent across cultivars within nurseries. Five different rootstocks were compared from one nursery, and results showed no differences between rootstocks and their health status. Among all nurseries, C. luteo-olivacea was the most prevalent fungus (97% of the plants), while D. macrodidyma was the least commonly found (13% of the plants). This study shows that ready-to-plant nursery material sold in Canada is likely to be infected with several YVD fungi and that presence and abundance of fungi vary significantly among individual grapevines and nurseries.

Detection of Esca‐associated fungi in grapevine trunks using loop‐mediated isothermal amplification (LAMP) assays

AbstractEsca is a grapevine trunk disease (GTD) that is caused by filamentous fungi. It is responsible for considerable economic losses in viniculture on a global scale. Despite many unknown factors contributing to the development of symptoms in affected plants, Phaeoacremonium minimum (PMI), Phaeomoniella chlamydospora (PCH) and Fomitiporia mediterranea (FMED) are generally considered as the main causative fungal species. Early detection and specific identification of these pathogens therefore play an important role in disease control and evaluation of suitable countermeasures. In this study, loop‐mediated isothermal amplification (LAMP) assays were developed for each of the three pathogens. A genome‐based approach was applied for detection and selection of unique target DNA sequences. The designed primer sets showed overall good specificities, with some observed cross‐reactions towards closely related Phaeoacremonium species for the PMI primer set. The developed assays had detection limits of 100 pg (FMED, PMI) and 1 pg (PCH) per reaction (corresponding to 1460 [FMED]; 1950 [PMI]; 342 [PCH] genome copies per reaction). The application of the assays to field samples was demonstrated by testing individual infected grapevine trunks from two European viticultural regions using crude DNA obtained in a rapid sample preparation step. LAMP assay results matched those of PCR following a conventional DNA extraction protocol. The study showed that LAMP‐based rapid molecular detection of major Esca agents can serve as a useful tool for further research and surveillance of a highly devastating grapevine disease. The application of computer‐based whole genome comparison between target and non‐target species for the identification of unique target sequences as the basis for LAMP (or PCR) primer design was demonstrated to be a useful approach in species for which scarce sequence information is available. Moreover, the developed method for rapid DNA preparation from grapevine trunks may potentially be adapted to the DNA‐based detection also of other fungal species that cause grapevine trunk diseases.

Novel algorithms for high-resolution prediction of canopy evapotranspiration in grapevine

Developing low-cost technology for custom water delivery to individual or small groups of plants is a critical next step to advance precision irrigation. Current systems for estimating evapotranspiration (ET), or plant water use, work on the scale of a full vineyard (e.g., 3–5 acres) or the scale of a single vine, but at a cost that prohibits monitoring past a small number of representative vines. To develop and evaluate low-cost ET sensors for individual grapevines, we used three head-pruned Zinfandel vines in pots and placed them on load cells to collect continuous weights indicative of actual ET. We mounted research-grade sensors for humidity, temperature, and wind speed on each vine and saved data at 2-minute intervals during three growing seasons. We developed three models based on first principles (Convective Mass Transfer or Mass Balance approaches) or simple correlations to predict actual single-plant ET from these data. We present here the results of a multi-year trial at the UC-Davis RMI vineyard to illustrate the performance of each of the models for ET estimation. Relative model performance was assessed by comparing model predictions to ground truth data provided by measurements from load cells–including assessments of estimated instantaneous ET rate, estimated cumulative water use over a one-hour window surrounding solar noon, and estimated cumulative water use over a full 24-hour period. The three algorithms developed consistently performed well, with single vine ET rate predictions showing a strong linear relationship with ground truth (range in r2 over three seasons CMT r2 = 0.61–0.86; MB r2 = 0.07–0.91; EM r2 = 0.57–0.92). The MB approach, which includes two measurements of relative humidity and temperature, was the most variable, likely due to the impact of sensor placement. In all seasons, we also examined the trend in the plant scaling factor found in each model, deemed As, which, based on model theory, is a function of vine size. Taken together, these results suggest that high-resolution irrigation (HRI) models are a promising new method for ET estimation at the single plant level.

Evaluating the Potential of High-Resolution Visible Remote Sensing to Detect Shiraz Disease in Grapevines

Background and Aims. Shiraz disease (SD) is a viral disease associated with Grapevine virus A that causes significant yield loss in economically important grape cultivars in Australia such as Shiraz and Merlot. Current diagnostic methods are time-consuming and costly. This study evaluates an alternative methodology using visible remote sensing imagery to detect SD in Shiraz grapevines. Methods and Results. High-resolution visible remote sensing images were captured of Shiraz grapevines in two South Australian viticultural regions over two seasons. The projected leaf area (PLA) of individual grapevines was estimated from the images. Virus-infected vines had significantly lower PLA than healthy vines in the early season but fewer difference after veraison. The lower PLA was only observed in grapevines coinfected with grapevine leafroll-associated viruses (GLRaVs) and Grapevine virus A (GVA). Shiraz vines infected with either GLRaVs or GVA had similar PLA to healthy vines. Conclusions. High-resolution RGB remote sensing technology has the potential to rapidly estimate SD infection in Shiraz grapevines. Our observations of shoot devigouration only in coinfected vines calls into question the etiology of SD. Further validation of the PLA technique incorporating different regions, seasons, cultivars, and combinations of viruses is needed for improving the robustness of the method. Significance of the Study. This preliminary study presents a new rapid and low-cost surveillance method to estimate SD infections in Shiraz vineyards, which could significantly lower the cost for growers who conduct on-ground SD visual assessments or lab-based tissue testing at the vineyard scale.

A Field Collection of Indigenous Grapevines as a Valuable Repository for Applied Research.

The grapevine is an economically important plant, with a historical connection to the development of human culture. Currently, over 6000 accessions are known as individual grapevine varieties, some of which are important to national heritage, valuable for current viticultural practices, and as genetic resources to maintain plasticity under changing climatic conditions, environmental sustainability, and market demands. Recently, the diversity of cultivated grapevines has declined significantly, due to the increased focus of global wine industries on a few major cultivars. Moreover, due to biotic and abiotic stresses, the wild V. vinifera germplasm’s genetic diversity has declined, with some varieties on the verge of extinction. Vitis germplasm conservation can be achieved via either in situ (e.g., protected areas) or Ex situ (e.g., field collections, seed banks, and tissue culture collections) methods. This study aims to highlight the importance of Vitis field bank collections. We demonstrate the research done in the Israeli indigenous Vitis vinifera collection. The multi-layer analysis of the varieties enabled the identification of drought stress-resistant varieties, and suggested a mechanism for this resistance through noting the dramatic phenological differences in foliage development between resistant and sensitive varieties. In addition, we show a general characterization of the varieties via major grape characteristics, including bunch and berry shape, as well as their possible utilization based on their aromatic and phenolic profiles.

The Compositional Turnover of Grapevine-Associated Plant Pathogenic Fungal Communities Is Greater Among Intraindividual Microhabitats and Terroirs than Among Healthy and Esca-Diseased Plants.

Grapevine trunk diseases (GTDs) are a major threat to the wine industry, causing yield loss and dieback of grapevines. While the increasing damage caused by GTDs in recent decades have spurred several studies on grapevine-associated pathogenic fungi, key questions about the emergence and severity of GTDs remain unanswered, including possible differences in plant pathogenic fungal communities in asymptomatic and symptomatic grapevines. We generated fungal DNA metabarcoding data from soil, bark, and perennial wood samples from asymptomatic and symptomatic grapevines sampled in three terroirs. We observed larger compositional differences in plant pathogenic fungi among different plants parts within grapevine plants than among individual grapevines. This is driven by the dominance of GTD-associated fungi in perennial wood and non-GTD pathogens in soil, as well as by the lack of significant differences among asymptomatic and Esca symptomatic grapevines. These results suggest that fungi generally associated with Esca disease belong to the core grapevine microbiome and likely are commensal endophytes and/or latent saprotrophs, some of which can act as opportunistic pathogens on stressed plants. In addition, we found significant compositional differences among sampling sites, particularly in soil, which suggest a certain influence of local edaphic and mesoclimatic factors on plant pathogenic fungal communities. Furthermore, the observed differences among terroirs in plant pathogenic fungal communities in grapevine woody parts indicate that environmental factors likely are important for the development of Esca disease and further studies are needed to investigate the abiotic conditions on fungal compositional dynamics in Esca-affected plants.

Automatic Grapevine Trunk Detection on UAV-Based Point Cloud

The optimisation of vineyards management requires efficient and automated methods able to identify individual plants. In the last few years, Unmanned Aerial Vehicles (UAVs) have become one of the main sources of remote sensing information for Precision Viticulture (PV) applications. In fact, high resolution UAV-based imagery offers a unique capability for modelling plant’s structure making possible the recognition of significant geometrical features in photogrammetric point clouds. Despite the proliferation of innovative technologies in viticulture, the identification of individual grapevines relies on image-based segmentation techniques. In that way, grapevine and non-grapevine features are separated and individual plants are estimated usually considering a fixed distance between them. In this study, an automatic method for grapevine trunk detection, using 3D point cloud data, is presented. The proposed method focuses on the recognition of key geometrical parameters to ensure the existence of every plant in the 3D model. The method was tested in different commercial vineyards and to push it to its limit a vineyard characterised by several missing plants along the vine rows, irregular distances between plants and occluded trunks by dense vegetation in some areas, was also used. The proposed method represents a disruption in relation to the state of the art, and is able to identify individual trunks, posts and missing plants based on the interpretation and analysis of a 3D point cloud. Moreover, a validation process was carried out allowing concluding that the method has a high performance, especially when it is applied to 3D point clouds generated in phases in which the leaves are not yet very dense (January to May). However, if correct flight parametrizations are set, the method remains effective throughout the entire vegetative cycle.

Classification of 3D Point Clouds Using Color Vegetation Indices for Precision Viticulture and Digitizing Applications

Remote sensing applied in the digital transformation of agriculture and, more particularly, in precision viticulture offers methods to map field spatial variability to support site-specific management strategies; these can be based on crop canopy characteristics such as the row height or vegetation cover fraction, requiring accurate three-dimensional (3D) information. To derive canopy information, a set of dense 3D point clouds was generated using photogrammetric techniques on images acquired by an RGB sensor onboard an unmanned aerial vehicle (UAV) in two testing vineyards on two different dates. In addition to the geometry, each point also stores information from the RGB color model, which was used to discriminate between vegetation and bare soil. To the best of our knowledge, the new methodology herein presented consisting of linking point clouds with their spectral information had not previously been applied to automatically estimate vine height. Therefore, the novelty of this work is based on the application of color vegetation indices in point clouds for the automatic detection and classification of points representing vegetation and the later ability to determine the height of vines using as a reference the heights of the points classified as soil. Results from on-ground measurements of the heights of individual grapevines were compared with the estimated heights from the UAV point cloud, showing high determination coefficients (R² > 0.87) and low root-mean-square error (0.070 m). This methodology offers new capabilities for the use of RGB sensors onboard UAV platforms as a tool for precision viticulture and digitizing applications.

Individual Grapevine Analysis in a Multi-Temporal Context Using UAV-Based Multi-Sensor Imagery

The use of unmanned aerial vehicles (UAVs) for remote sensing applications in precision viticulture significantly increased in the last years. UAVs’ capability to acquire high spatiotemporal resolution and georeferenced imagery from different sensors make them a powerful tool for a better understanding of vineyard spatial and multitemporal heterogeneity, allowing the estimation of parameters directly impacting plants’ health status. In this way, the decision support process in precision viticulture can be greatly improved. However, despite the proliferation of these innovative technologies in viticulture, most of the published studies rely only on data from a single sensor in order to achieve a specific goal and/or in a single/small period of the vineyard development. In order to address these limitations and fully exploit the advantages offered by the use of UAVs, this study explores the multi-temporal analysis of vineyard plots at a grapevine scale using different imagery sensors. Individual grapevine detection enables the estimation of biophysical and geometrical parameters, as well as missing grapevine plants. A validation procedure was carried out in six vineyard plots focusing on the detected number of grapevines and missing grapevines. A high overall agreement was obtained concerning the number of grapevines present in each row (99.8%), as well as in the individual grapevine identification (mean overall accuracy of 97.5%). Aerial surveys were conducted in two vineyard plots at different growth stages, being acquired for RGB, multispectral and thermal imagery. Moreover, the extracted individual grapevine parameters enabled us to assess the vineyard variability in a given epoch and to monitor its multi-temporal evolution. This type of analysis is critical for precision viticulture, constituting as a tool to significantly support the decision-making process.

High genetic differentiation of grapevine rootstock varieties determined by molecular markers and artificial neural networks

The genetic differentiation of grapevine rootstock varieties was inferred by the Artificial Neural Network approach based on the Self-Organizing Map algorithm. A combination of RAPD and SSR molecular markers, yielding polymorphic informative loci, was used to determine the genetic characterization among the rootstock varieties 420-A, Schwarzmann, IAC-766 Campinas, Traviú, Kober 5BB, and IAC-572 Jales. A neural network algorithm, based on allelic frequency, showed that the individual grapevine rootstocks (n = 64) were grouped into three genetically differentiated clusters. Cluster 1 included only the Kober 5BB rootstock, Cluster 2 included rootstocks of the varieties Traviú and IAC-572, and Cluster 3 included 420-A, Schwarzmann and IAC-766 plants. Evidence from the current study indicates that, despite the morphological similarities of the 420-A and Kober 5BB varieties, which share the same genetic origin, two new varieties were generated that are genetically divergent and show differences in performance.

Performance of direct root-zone deficit irrigation on Vitis vinifera L. cv. Cabernet Sauvignon production and water use efficiency in semi-arid southcentral Washington

The direct root-zone irrigation system is a new technique to deliver water directly to the root zone of grapevines at specific irrigation rates and delivery depths. The response of Vitis vinifera L. cv. Cabernet Sauvignon to direct root-zone deficit irrigation was investigated in a commercial vineyard with loamy sand soil in the semi-arid lower Columbia Basin of southcentral Washington State, USA. Three irrigation rates and three delivery depths were compared for effects on grape yield and crop water use efficiency during three consecutive growing seasons. Furthermore, we investigated the influence of irrigation rate on grape quality, and used an in situ root imaging system for root phenotyping under different delivery depths for two years. Results showed that delivery depth had no significant effect on grape yield and crop water use efficiency; however, increases in delivery depth from 30 cm to 90 cm resulted in 60–70% decreased root number and 46–59% decreased root length in the upper soil profile (0–60 cm). Moderate irrigation rates (35% less water use on average) improved crop water use efficiency by 14–23% and only reducing grape yield 15–18% per individual grapevine, without sacrificing grape quality or inducing early defoliation for the first two years. Surprisingly, no significant reduction of grape yield was found in the third year, which can be attributed to cooler and wetter weather and potentially vine acclimation to the direct root-zone irrigation strategy. We conclude that direct root-zone deficit irrigation could be a convenient and efficient subsurface irrigation method to improve crop water use efficiency without reducing grape quality under seasonal drought. Future studies should compare the economic and environmental returns of direct root-zone deficit irrigation with other traditional irrigation strategies under different environmental conditions to optimize the direct root-zone deficit irrigation method.

Prevalence of Viruses in Commercial Wine Grape Vineyards in Georgia

Virus diseases are major constraints to Vitis vinifera wine grape production worldwide. Grapevine leafroll-associated virus 3 (GLRaV-3) was first confirmed in Georgia in 2008. The negative impacts of GLRaV-3, such as decreased fruit yield and quality, were confirmed from samples taken in 2009 and 2010. In light of these findings, studies were initiated to determine the prevalence and types of grapevine viruses present in vineyards in Georgia. Five vineyard blocks were visited during August and September of 2011 and 2012. Leaf samples were collected from a total of 50 grapevines showing symptoms of and suspected as being infected by grapevine leafroll disease (GLD). Samples from individual grapevines were extracted and tested separately for 20 grapevine viruses listed in standard virus indexing programs. Reverse transcription polymerase chain reaction (RT-PCR) or PCR, depending on the nature of the virus genome, was used to detect these viruses with species-specific primers. The results showed the presence of GLRaV-1, -2, -3, and -4 (strains 4, 5, and 6), grapevine virus B, grapevine rupestris stem pitting-associated virus, and grapevine red blotch virus. Many vineyards had multiple viruses detected from individual grapevines showing typical GLD or GLD-like symptoms.

First Report of Grapevine fabavirus in Diverse Vitis Species in Korea

HomePlant DiseaseVol. 101, No. 10First Report of Grapevine fabavirus in Diverse Vitis Species in Korea PreviousNext DISEASE NOTES OPENOpen Access licenseFirst Report of Grapevine fabavirus in Diverse Vitis Species in KoreaY. Jo, M. K. Song, H. Choi, J. S. Park, J. W. Lee, and W. K. ChoY. JoSearch for more papers by this author, M. K. SongSearch for more papers by this author, H. ChoiSearch for more papers by this author, J. S. ParkSearch for more papers by this author, J. W. Lee†Corresponding authors: J. W. Lee, E-mail Address: [email protected]; and W. K. Cho, E-mail Address: [email protected]Search for more papers by this author, and W. K. Cho†Corresponding authors: J. W. Lee, E-mail Address: [email protected]; and W. K. Cho, E-mail Address: [email protected]Search for more papers by this authorAffiliationsAuthors and Affiliations Y. Jo , Department of Agricultural Biotechnology, College of Agriculture and Life Sciences, Seoul National University, Seoul, 08826, Republic of Korea M. K. Song , Grape Research Institute, Chungbuk Agricultural Research and Extension Services, Okcheon, 29017, Republic of Korea H. Choi , Department of Agricultural Biotechnology, College of Agriculture and Life Sciences, Seoul National University, Seoul, 08826, Republic of Korea J. S. Park J. W. Lee † , Grape Research Institute, Chungbuk Agricultural Research and Extension Services, Okcheon, 29017, Republic of Korea W. K. Cho † , Department of Agricultural Biotechnology, College of Agriculture and Life Sciences, Seoul National University, Seoul, 08826, Republic of Korea. Published Online:26 Jul 2017https://doi.org/10.1094/PDIS-04-17-0513-PDNAboutSections ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinked InRedditEmailWechat Grapevine fabavirus (GFabV) is a novel virus that has been recently identified from two Japanese table grapes, Vitis vinifera cvs. Black Beet (BB) and Nagano Purple (NP), derived from South Korea in 2013 (Al Rwahnih et al. 2016). GFabV is a putative member of the genus Fabavirus in the family Secoviridae. The genome of GFabV consists of two RNA fragments named RNA1 and RNA2. To date, GFabV has been identified in North America, India, South Korea, and China (Al Rwahnih et al. 2016; Fan et al. 2017). In 2016, we sampled grapevine leaves from 16 individual grapevine plants representing 12 different grapevine cultivars. Except for a Shine Muscat (V. labruscana Bailey × V. vinifera) plant sampled from a vineyard in Okcheon, all 15 grapevine plants were grown in the Grape Research Institute. Only two grapevine plants of the Shine Muscat cultivar showed viral disease symptoms such as leaf malformations, vein clearing, and yellowing, whereas the other 14 plants did not display any visible disease symptoms. Sixteen libraries were paired-end sequenced using Illumina’s HiSeq 2000 followed by bioinformatics analyses as described previously (Jo et al. 2016). We identified 143 GFabV-associated contigs (75 contigs for RNA1 and 68 contigs for RNA2) ranging from 215 to 5,804 bp from 11 libraries. The GFabV-infected grapevine plants were as follows: Campbell Early (V. labruscana) (two plants), 188-08 (V. monticola × V. riparia) (two plants), Jaok (Vitis hybrid), Shine Muscat (two plants), Chungporang (Vitis hybrid), Okrang (Vitis hybrid), Chungrang (Vitis hybrid), and Jarang (V. vinifera). We assembled two nearly complete genomes for isolate 188-08 (5,675-nt RNA1 and 3,069-nt RNA2) and isolate Shine Muscat (5,804-nt RNA1 and 3,137-nt RNA2). However, four V. vinifera cultivars (i.e., Alicante, Cabernet franc, Cabernet Sauvignon, and Chardonnay) were not infected by GFabV. To confirm the NGS results, we carried out RT-PCR using known GFab-RNA1-specific primers and GFab-RNA2-specific primers (Al Rwahnih et al. 2016). The 642-bp products were amplified from seven cultivars but not from Shine Muscat using GFab-RNA1-specific primers. The 628-bp products were amplified from only two plants of Shine Muscat using GFab-RNA2-specific primers. This result suggests that at least two different primer pairs should be applied to detect GFabV due to their sequence diversity. The 642-bp amplified products from 188-08 and Campbell Early were cloned in the pGEM-T-Easy Vector (Promega, Wisconsin, U.S.A.) followed by Sanger sequencing. The amplified sequences (GenBank KY808370 and KY808371) confirmed that both isolates shared 99% of the nucleotide identity with the known isolate NP. Based on our result, diverse Vitis spp. including V. labruscana and other Vitis hybrids grown in the Grapevine Research Institute except imported grapevine cultivars belonging to V. vinifera have been infected by GFabV. Our results revealed a high prevalence of GFabV in important grapevine cultivars in Korea. Furthermore, a majority of grapevine plants infected by GFabV was asymptomatic; however, the possible role of the isolates of GFabV from Shine Muscat showing disease symptoms should be further studied. Taken together, this is the first report of GFabV infecting diverse Vitis spp. in Korea.

Viral small RNAs reveal the genomic variations of three grapevine vein clearing virus quasispecies populations

Viral small RNAs (vsRNAs) include viral small interfering RNAs (vsiRNAs) that are initiators and products of RNA silencing, and small RNAs that are derived from viral RNAs with function still unknown. Sequencing of vsRNAs allows assembling of viral genomes and revelation of viral population variations at genomic levels. Grapevine vein clearing virus (GVCV) is a new member of the family Caulimoviridae whose DNA genome is replicated by reverse transcription of pre-genomic RNA molecules. In this short report, three genomic sequences of GVCV were assembled from vsRNAs that were isolated and sequenced from three individual grapevines in commercial vineyards and compared to the GVCV-CHA reference genome. Profiles of single nucleotide polymorphism among three viral populations indicated a closer relatedness between two populations in different grape cultivars at the same location than those in the same grape cultivar at different locations, suggesting the spread of GVCV populations among vineyards of close proximity. Classic types of vsiRNAs (21-nt, 22-nt, and 24-nt) were found in the three GVCV vsiRNA populations, but these did not produce alignment hotspots on the GVCV-CHA reference genome. The number of 36-nt reads is the highest among vsRNAs, the role of these vsRNAs remains unclear. The analysis of vsRNAs provides a first holistic picture of genomic variations among GVCV viral quasispecies populations that help monitor epidemics and evolution of GVCV populations, an emerging virus that is becoming a threat to grape production in the Midwest region of the USA.

A high-throughput UHPLC MS/MS method for evaluation of tartaric and malic acid concentration in individual grapevine berries

Background and Aims The chemical composition of grape berries during development exhibits large variation within a single bunch. To monitor the change in the concentration of tartaric acid and malic acid between individual berries, a high-throughput method using UHPLC-MS/MS was developed to quantify these acids in berry extracts. Methods and Results The results from analysis of single-vine datasets indicated that there was a large variation in the concentration of tartaric acid and malic acid between individual berries and also between bunches of berries across a vine. From these data, an optimum sampling size of 30 berries per vine was determined, which has an estimated standard error under 10% of the expected average berry acid concentration. Conclusions A high-throughput UHPLC-MS/MS method using the stable isotope dilution analysis has been developed to quantify tartaric acid and malic acid in individual berry extracts and extracts prepared from samples of multiple berries. Significance of the Study This method enabled the study of variation in acid concentration and content between individual berries. This makes it possible to quantify the variation in the acids at several levels (berries, bunches and plants) and to recommend ideal sampling sizes for data collection in vineyards.

An automated field phenotyping pipeline for application in grapevine research.

Due to its perennial nature and size, the acquisition of phenotypic data in grapevine research is almost exclusively restricted to the field and done by visual estimation. This kind of evaluation procedure is limited by time, cost and the subjectivity of records. As a consequence, objectivity, automation and more precision of phenotypic data evaluation are needed to increase the number of samples, manage grapevine repositories, enable genetic research of new phenotypic traits and, therefore, increase the efficiency in plant research. In the present study, an automated field phenotyping pipeline was setup and applied in a plot of genetic resources. The application of the PHENObot allows image acquisition from at least 250 individual grapevines per hour directly in the field without user interaction. Data management is handled by a database (IMAGEdata). The automatic image analysis tool BIVcolor (Berries in Vineyards-color) permitted the collection of precise phenotypic data of two important fruit traits, berry size and color, within a large set of plants. The application of the PHENObot represents an automated tool for high-throughput sampling of image data in the field. The automated analysis of these images facilitates the generation of objective and precise phenotypic data on a larger scale.

Genetic Diversity ofGrapevine virus Ain Washington and California Vineyards

Grapevine virus A (GVA; genus Vitivirus, family Betaflexiviridae) has been implicated with the Kober stem grooving disorder of the rugose wood disease complex. In this study, 26 isolates of GVA recovered from wine grape (Vitis vinifera) cultivars from California and Washington were analyzed for their genetic diversity. An analysis of a portion of the RNA-dependent RNA polymerase (RdRp) and complete coat protein (CP) sequences revealed intra- and inter-isolate sequence diversity. Our results indicated that both RdRp and CP are under strong negative selection based on the normalized values for the ratio of nonsynonymous substitutions per nonsynonymous site to synonymous substitutions per synonymous site. A global phylogenetic analysis of CP sequences revealed segregation of virus isolates into four major clades with no geographic clustering. In contrast, the RdRp-based phylogenetic tree indicated segregation of GVA isolates from California and Washington into six clades, independent of geographic origin or cultivar. Phylogenetic network coupled with recombination analyses showed putative recombination events in both RdRp and CP sequence data sets, with more of these events located in the CP sequence. The preponderance of divergent variants of GVA co-replicating within individual grapevines could increase viral genotypic complexity with implications for phylogenetic analysis and evolutionary history of the virus. The knowledge of genetic diversity of GVA generated in this study will provide a foundation for elucidating the epidemiological characteristics of virus populations at different scales and implementing appropriate management strategies for minimizing the spread of genetic variants of the virus by vectors and via planting materials supplied to nurseries and grape growers.