Aims
The aim of this work was to investigate the effects of biodynamic management with and without the addition of green manure, in comparison with organic management, on the microbiota in vineyards ...soil.
Methods and Results
High throughput sequencing was used to compare the taxonomic structure of the soil bacterial and fungal communities from vineyards managed with different methods (organic, biodynamic or biodynamic with green manure). Our results showed that microbial communities associated with biodynamic and organic farming systems were very similar, while green manure was the greatest source of soil microbial biodiversity and significantly changed microbial richness and community composition compared with other soils. Green manure also significantly enriched bacterial taxa involved in the soil nitrogen cycle (e.g. Microvirga sp., Pontibacter sp. and Nitrospira sp.).
Conclusions
Our results showed that the diversity and composition of the microbial communities associated with biodynamic and organic farming systems were similar, indicating that the use of biodynamic preparations 500 and 501 did not cause any significant detectable changes to the soil microbial community in the short term, while the effects of green manure were significant in soil microbiota.
Significance and Impact of the Study
The microbiological richness and structure of soil are used as a sensitive indicator of soil quality. The extension of organic/biodynamic farming, associated with green manure application, could contribute to increase the abundance of functional groups of biological and agronomical relevance and maintaining microbial biodiversity in vineyard soils.
With disruptive technologies being employed in the wine industry, the Metaverse - defined as an interactive, immersive environment that allows users to traverse between virtual and physical worlds, ...and enables them to interact with digital content and each other in a shared space, transcending the limitations of time, space, and physicality in a more realistic and engaging way - provides evidence of intriguing opportunities to curate more immersive virtual vineyard experiences for consumers. We offer a glimpse of how the Metaverse can revolutionize consumers' wine tasting experiences. Drawing on extant literature on multisensory wine consumption and different technologies, we provide a comprehensive definition of the Metaverse and propose a VINEYARD framework for academics and practitioners to consider in navigating through the 'metaversification' of virtual vineyard experiences. Furthermore, we identify key benefits and potential challenges when incorporating the Metaverse into vineyard management and marketing. Finally, we propose several metrics for practitioners to assess the sustainable development of virtual vineyard experiences in the Metaverse.
New technologies for management, monitoring, and control of spatio-temporal crop variability in precision viticulture scenarios are numerous. Remote sensing relies on sensors able to provide useful ...data for the improvement of management efficiency and the optimization of inputs. unmanned aerial systems (UASs) are the newest and most versatile tools, characterized by high precision and accuracy, flexibility, and low operating costs. The work aims at providing a complete overview of the application of UASs in precision viticulture, focusing on the different application purposes, the applied equipment, the potential of technologies combined with UASs for identifying vineyards' variability. The review discusses the potential of UASs in viticulture by distinguishing five areas of application: rows segmentation and crop features detection techniques; vineyard variability monitoring; estimation of row area and volume; disease detection; vigor and prescription maps creation. Technological innovation and low purchase costs make UASs the core tools for decision support in the customary use by winegrowers. The ability of the systems to respond to the current demands for the acquisition of digital technologies in agricultural fields makes UASs a candidate to play an increasingly important role in future scenarios of viticulture application.
The detection of water stress in vineyards plays an integral role in the sustainability of high-quality grapes and prevention of devastating crop loses. Hyperspectral remote sensing technologies ...combined with machine learning provides a practical means for modelling vineyard water stress. In this study, we applied two ensemble learners, i.e., random forest (RF) and extreme gradient boosting (XGBoost), for discriminating stressed and non-stressed Shiraz vines using terrestrial hyperspectral imaging. Additionally, we evaluated the utility of a spectral subset of wavebands, derived using RF mean decrease accuracy (MDA) and XGBoost gain. Our results show that both ensemble learners can effectively analyse the hyperspectral data. When using all wavebands (p = 176), RF produced a test accuracy of 83.3% (KHAT (kappa analysis) = 0.67), and XGBoost a test accuracy of 80.0% (KHAT = 0.6). Using the subset of wavebands (p = 18) produced slight increases in accuracy ranging from 1.7% to 5.5% for both RF and XGBoost. We further investigated the effect of smoothing the spectral data using the Savitzky-Golay filter. The results indicated that the Savitzky-Golay filter reduced model accuracies (ranging from 0.7% to 3.3%). The results demonstrate the feasibility of terrestrial hyperspectral imagery and machine learning to create a semi-automated framework for vineyard water stress modelling.
California's Central Valley grows a significant fraction of grapes used for wine production in the United States. With increasing vineyard acreage, reduced water availability in much of California, ...and competing water use interests, it is critical to be able to monitor regional water use and evapotranspiration (ET) over large areas, but also in detail at individual field scales to improve water management within these viticulture production systems. This can be achieved by integrating remote sensing data from multiple satellite systems with different spatiotemporal characteristics. In this research, we evaluate the utility of a multi-scale system for monitoring ET as applied over two vineyard sites near Lodi, California during the 2013 growing season, leading into the drought in early 2014. The system employs a multi-sensor satellite data fusion methodology (STARFM: Spatial and Temporal Adaptive Reflective Fusion Model) combined with a multi-scale ET retrieval algorithm based on the Two-Source Energy Balance (TSEB) land-surface representation to compute daily ET at 30m resolution. In this system, TSEB is run using thermal band imagery from the Geostationary Environmental Operational Satellites (GOES; 4-km spatial resolution, hourly temporal sampling), the Moderate Resolution Imaging Spectroradiometer (MODIS) data (1km resolution, daily acquisition) and the new Landsat 8 satellite (sharpened to 30m resolution, ~16day acquisition). Estimates of daily ET generated in two neighboring fields of Pinot noir vines of different age agree with ground-based flux measurements acquired in-field during most of the 2013 season with relative mean absolute errors on the order of 19–23% (root mean square errors of approximately 1mmd−1), reducing to 14–20% at the weekly timestep relevant for irrigation management (~5mmwk−1). A model overestimation of ET in the early season was detected in the younger vineyard, perhaps relating to an inter-row grass cover crop. Spatial patterns of cumulative ET generally correspond to measured yield maps and indicate areas of variable crop moisture, soil condition, and yield within the vineyards that could require adaptive management. The results suggest that multi-sensor remote sensing observations provide a unique means for monitoring crop water use and soil moisture status at field-scales over extended growing regions, and may have value in supporting operational water management decisions in vineyards and other high value crops.
•Multi-scale, multi-sensor fusion methodology estimates vineyard evapotranspiration.•Combining Landsat 8, MODIS, and GOES data provides daily field scale ET estimates.•Modeled surface energy fluxes agree well with ground flux measurements.•Spatial distribution of ET corresponds with yield estimates.•ET overestimation in early season may be due to cover crop between vines.
La plaga de la filoxera en el siglo XIX produjo importantes pérdidas en el viñedo español, pero también supuso un cambio del mapa vitivinícola. Las zonas más aptas para el cultivo se recuperaron, ...mientras las zonas menos apropiadas como Sierra Morena, que comprende la parte norte de la provincia de Córdoba, lo fueron abandonando paulatinamente hasta casi desaparecer. Mediante sistemas de información geográfica se analiza la cartografía histórica de la segunda mitad del siglo XIX para localizar e identificar las características geográficas de esos antiguos viñedos, su extensión, situación, litología, pendientes, orientación o la convivencia con otros cultivos. Entre los resultados obtenidos se constata que en la zona de estudio su extensión superaba a la del sur de la provincia, en donde existe actualmente la consolidada denominación de vino Montilla-Moriles. A partir de la interpretación de los mapas obtenidos se exponen también algunas características de los desaparecidos paisajes de este viñedo de la montaña media mediterránea y se registran ciertas iniciativas de cara a su puesta en valor.
•Field and landscape parameters are important to enhance wild bees in vineyards.•Forage availability and alternating tillage positively affect wild bees at the field scale.•The proportion of villages ...and woods increase wild bee diversity and abundance.
Vineyard inter-rows can provide habitats for a range of plant and animal species especially when covered with vegetation. However, frequent tillage results in the degradation of habitat quality and the provision of biodiversity-based ecosystem services. Wild bees are important pollinators of crops and wild plants and depend on both, floral resources and suitable nesting sites, which are influenced by the landscape configuration.
We examined effects of field and landscape parameters on wild bee species’ richness, abundance and functional traits in Austrian vineyards over two years using Generalised Linear Mixed models, Detrended Correspondence Analysis and Random Forests. Alternating tillage was compared with no tillage in two inter-rows per vineyard. Forage availability in these inter-rows was estimated by flower coverage at each sampling date, and landscape features were analysed within a radius of 750 m around the vineyards.
Across all vineyards we found 84 wild bee species with a mean abundance (±SD) of 29 (±16.6). Forage availability had the strongest positive effect on wild bee diversity and abundance. In comparison to no tillage, alternating tillage slightly increased wild bee diversity and abundance. Eusocial wild bees were more abundant in untilled inter-rows, whereas solitary wild bees were more closely associated with alternating tilled vineyards. At the landscape scale, the percentage of artificial areas (mostly villages) and distance to semi-natural elements raised wild bee diversity and abundance. The proportion of woodland increased the abundance of wild bees, in particular of eusocial taxa. Solitary wild bee abundance was enhanced by the number of solitary trees.
Pollination provided by wild bees in viticultural areas can be enhanced by maintaining a diversity of different soil management strategies to improve forage availability in vineyards. Furthermore, semi-natural elements such as fallows or solitary trees providing floral resources and nesting habitat should be preserved within viticultural landscapes.
•Integrated production in vineyards comprises minimum tillage and regulated fertilization.•Runoff, sediment and nutrient exports from a Mediterranean vineyard was monitored.•Runoff from vineyards may ...be a diffuse source pollution due to TP and TN exports.•Minimum tillage in vineyards is not enough to prevent land degradation.
Conventional management of Mediterranean vineyards strongly contributes to land degradation. In Portugal, the use of integrated production has been encouraged by governmental subsidies because it is assumed to be a farm management system that protects the environment and favours agriculture sustainability. The purpose of this study is to assess the impact of minimum tillage and regulated fertilization practices, driven by integrated production, on runoff and associated sediment and nutrient exports (total phosphorous – TP, total nitrogen – TN and nitrates – NO3). A vineyard in the Bairrada wine region was instrumented with six runoff plots (80–122 m2). Plots were monitored on a weekly to bi-weekly basis (depending on the rainfall pattern), over two hydrological years (from October 2012 to September 2014). Results indicated that annual runoff coefficients ranged from 10% to 20%, sediment losses from 1.1 to 29.0 Mg ha−1 yr−1, TP exports from 0.4 to 6.5 kg ha−1 yr−1, TN exports from 0.2 to 20.0 kg ha−1 yr−1 and NO3 exports from 0.1 to 0.8 kg ha−1 yr−1. These results highlight the susceptibility of vineyards to land degradation and their role as a diffuse source of pollution. Rainfall strongly influenced runoff as well as sediment and nutrient concentrations, leading to relevant inter-annual and seasonal differences. Over the study period, about 60% of runoff and >85% of sediments and nutrients exported by runoff were recorded during winter. Management practices, namely inter-row tillage deeply influenced sediment exports, whereas fertilization, had a strong effect on nitrate exports. Although integrated production lead to lower runoff and nutrient exports than conventional viticulture, additional measures are needed to effectively prevent soil erosion and nutrient losses in Mediterranean vineyards.
Steep slope vineyards are a complex scenario for the development of ground robots. Planning a safe robot trajectory is one of the biggest challenges in this scenario, characterized by irregular ...surfaces and strong slopes (more than 35°). Moving the robot through a pile of stones, spots with high slope or/and with wrong robot yaw may result in an abrupt fall of the robot, damaging the equipment and centenary vines, and sometimes imposing injuries to humans. This paper presents a novel approach for path planning aware of center of mass of the robot for application in sloppy terrains. Agricultural robotic path planning (AgRobPP) is a framework that considers the A* algorithm by expanding inner functions to deal with three main inputs: multi-layer occupation grid map, altitude map and robot’s center of mass. This multi-layer grid map is updated by obstacles taking into account the terrain slope and maximum robot posture. AgRobPP is also extended with algorithms for local trajectory replanning during the execution of a trajectory that is blocked by the presence of an obstacle, always assuring the safety of the re-planned path. AgRobPP has a novel PointCloud translator algorithm called PointCloud to grid map and digital elevation model (PC2GD), which extracts the occupation grid map and digital elevation model from a PointCloud. This can be used in AgRobPP core algorithms and farm management intelligent systems as well. AgRobPP algorithms demonstrate a great performance with the real data acquired from AgRob V16, a robotic platform developed for autonomous navigation in steep slope vineyards.
Frequently, the vineyards in the Douro Region present multiple grape varieties per parcel and even per row. An automatic algorithm for grape variety identification as an integrated software component ...was proposed that can be applied, for example, to a robotic harvesting system. However, some issues and constraints in its development were highlighted, namely, the images captured in natural environment, low volume of images, high similarity of the images among different grape varieties, leaf senescence, and significant changes on the grapevine leaf and bunch images in the harvest seasons, mainly due to adverse climatic conditions, diseases, and the presence of pesticides. In this paper, the performance of the transfer learning and fine-tuning techniques based on AlexNet architecture were evaluated when applied to the identification of grape varieties. Two natural vineyard image datasets were captured in different geographical locations and harvest seasons. To generate different datasets for training and classification, some image processing methods, including a proposed four-corners-in-one image warping algorithm, were used. The experimental results, obtained from the application of an AlexNet-based transfer learning scheme and trained on the image dataset pre-processed through the four-corners-in-one method, achieved a test accuracy score of 77.30%. Applying this classifier model, an accuracy of 89.75% on the popular Flavia leaf dataset was reached. The results obtained by the proposed approach are promising and encouraging in helping Douro wine growers in the automatic task of identifying grape varieties.
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