Geological characterization of plot belonging to the left bank terraces terroir of the Gaillac vineyard (Tarn, Midi-Pyrénées). Consequences on determination of choice of vegetative material

To evaluate the current and future impact of climate change on Viticulture requires an integrated view on a complex interacting system within the soil-plant-atmospheric continuum under continuous change. Aside of the globally observed increase in temperature in basically all viticulture regions for at least four decades, we observe several clear trends at the regional level in the ratio of precipitation to potential evapotranspiration. Additionally the recently published 6th assessment report of the IPCC (The physical science basis) shows case-dependent further expected shifts in climate patterns which will have substantial impacts on the way we will conduct viticulture in the decades to come. Looking beyond climate developments, we observe rising temperatures in the upper soil layers which will have an impact on the distribution of microbial populations, the decay rate of organic matter or the storage capacity for carbon, thus affecting the emission of greenhouse gases (GHGs) and the viscosity of water in the soil-plant pathway, altering the transport of water. If the upper soil layers dry out faster due to less rainfall and/or increased evapotranspiration driven by higher temperatures, the spectral reflection properties of bare soil change and the transport of latent heat into the fruiting zone is increased putting a higher temperature load on the fruit. Interactions between micro-organisms in the rhizosphere and the grapevine root system are poorly understood but respond to environmental factors (such as increased soil temperatures) and the plant material (rootstock for instance), respectively the cultivation system (for example bio-organic versus conventional). This adds to an extremely complex system to manage in terms of increased resilience, adaptation to and even mitigation of climate change. Nevertheless, taken as a whole, effects on the individual expressions of wines with a given origin, seem highly likely to become more apparent.

Vitis vinifera L. ‘Gewürztraminer’ is a historical grape variety of Alto Adige (Südtirol), Italy, which is widely grown in the area of Tramin an der Weinstraße, but is also grown globally. It produces highly aromatic wines that are strongly influenced by the terroir of the vineyard sites where they are grown. This study looked at musts and young wines from ‘Gewürztraminer’ grapes harvested in seven distinct vineyards near Tramin and then processed at Cantina di Termeno, minimizing winemaking protocol variability. Samples were profiled using bidimensional gas chromatography–time-of-flight mass spectrometry, liquid chromatography coupled to electrochemical detection, and near-IR spectrometry. The data were subjected to Principle Component Analysis and Hierarchical Clustering Analysis. Sensory discriminant testing was undertaken using the sorting method with a semi-trained panel, and the data were processed using Multidimensional Scaling. Seven must/wine pairs could be distinguished based on their untargeted volatilome profiles and on sensory evaluation. As expected, there were greater differences in the volatile compounds between the wines than between the musts. The wines from vineyards 4 and 5 were nonetheless quite homogenous in terms of chemical and sensory analyses, as were the wines from vineyards 1 and 3. For the phenolic profile, differences were noted between the musts and wines of vineyards 2, 3, and 4, but the musts from vineyards 5 and 7 were similar. Sensory analysis showed the wines from vineyards 6 and 7 to be distinct from the rest. These results reinforce that the composition of ‘Gewürztraminer’ musts and wines is strongly determined by vineyard site, even in a small geographic area with high variability of the terroir (soil and microclimate), and that these differences are apparent in the flavours and aromas of the finished wines. Further confirmation would require a larger sample of wines, preferably from several vintages.

Currently, the main goal of agriculture is to promote the resilience of agricultural systems in a sustainable way through the improvement of use efficiency of farm resources, increasing crop yield and quality under climate change conditions. This last is expected to drastically modify plant growth, with possible negative effects, especially in arid and semi-arid regions of Europe on the viticultural sector. In this context, the monitoring of spatial behavior of grapevine during the growing season represents an opportunity to improve the plant management, winegrowers’ incomes, and to preserve the environmental health, but it has additional costs for the farmer. Nowadays, UAS equipped with a VIS-NIR multispectral camera (blue, green, red, red-edge, and NIR) represents a good and relatively cheap solution to assess plant status spatial information (by means of a limited set of spectral vegetation indices), representing important support in precision agriculture management during the growing season. While differences between UAS-based multispectral imagery and point-based spectroscopy are well discussed in the literature, their impact on plant status estimation by vegetation indices is not completely investigated in depth. The aim of this study was to assess the performance level of UAS-based multispectral (5 bands across 450-800nm spectral region with a spatial resolution of 5cm) imagery, reconstructed high-resolution satellite (Sentinel-2A) multispectral imagery (13 bands across 400-2500 nm with spatial resolution of <2 m) through Convolutional Neural Network (CNN) approach, and point-based field spectroscopy (collecting 600 wavelengths across 400-1000 nm spectral region with a surface footprint of 1-2 cm) in a plant status estimation application, and then, using Bayesian regularization artificial neural network for leaf chlorophyll content (LCC) and plant water status (LWP) prediction. The test site is a Greco vineyard of southern Italy, where detailed and precise records on soil and atmosphere systems, in-vivo plant monitoring of eco-physiological parameters have been conducted.

“Flavescence dorée” (FD) is a grapevine quarantine disease associated with phytoplasmas and transmitted to healthy plants by insect vectors, mainly Scaphoideus titanus. Infected plants usually develop symptoms of stunted growth, unripe cane wood, leaf rolling, leaf yellowing or reddening, and shrivelled berries. Since plants can remain symptomless up to four years, they may act as reservoirs of FD contributing to the spread of the disease. So far, conventional management strategies rely mainly on the insecticide treatments, uprooting of infected plants and use of phytoplasma-free propagation material. However, these strategies are costly and could have undesirable environmental impacts. Thus, the development of sustainable and noninvasive approaches for early detection of FD and its management are of great importance to reduce disease spread and select the best cultural practices and treatments. The present study aimed to evaluate if multispectral/hyperspectral technologies can be used to detect FD before the appearance of the first symptoms and if infected grapevines display a spectral imaging fingerprint. To that end, physiological parameters (leaf area, chlorophyll content and photosynthetic rate) were collected in concomitance to the measurements of plant reflectance (using both a portable apparatus and a remote sensing drone). Measurements were performed in two leaves of 8 healthy and 8 FD-infected grapevines, at four timepoints: before the development of disease symptoms (21st June); and after symptoms appearance (ii) at veraison (2nd August); at post-veraison (11th September); and at harvest (25th September). At all timepoints, FD infected plants revealed a significant decrease in the studied physiological parameters, with a positive correlation with drone imaging data and portable apparatus analyses. Moreover, spectra of either drone imaging and portable apparatus showed clear differences between healthy and FD-infected grapevines, validating multispectral/ hyperspectral technology as a potential tool for the early detection of FD or other grapevine-associated diseases.

Air temperature is the key driver of grapevine phenology and a significant environmental factor impacting yield and quality for a winegrape growing region. In this study the optimal downscaled CMIP5 ensemble for computing thegrowing season average temperature (GST) viticulture climate classification index was determined to spatially compute on a decadal basis predictions of the GST climate index and the grapevine sugar ripeness (GSR) model for Pinot Noir throughout the Willamette Valley (WV) American Viticultural Area (AVA). Forecasts for average temperature and a 220 g/L target sugar concentration level were computed using daily Localized Constructed Analogs (LOCA) downscaled CMIP5 historic and Representative Concentration Pathways (RCP) future climate projections of minimum and maximum daily temperature. We explore spatiotemporal trends of the GST climate classification index and Pinot Noir specific applications of the GSR phenology model for the WV AVA. Spatiotemporal computations of the GST climate index and Pinot Noir specific applications of the GSR model enable the opportunity to explore relationships between their computed values with one intent being to provide updated GST ranges that better align with current temperature-based modeling understanding of Pinot Noir grapevine phenology and the viticultural application of LOCA CMIP5 climate projections for the WV AVA. The Pinot Noir specific applications of the GSR model or the GST index with updated bounds indicate that the percent of the WV AVA area suitable for Pinot Noir production is currently at or near its peak value in the upper 80s to lower 90s of this century.