Fast, and full microbiological wine analysis using triple cellular staining.

The development of new generations of multispectral satellites such as Sentinel-2 opens possibilities as to vine water status assessment (Cohen et al., 2019). Based on a three years field campaign, a model of Stem Water Potential (SWP) estimation on vine using four satellite bands in Red, Red-Edge, NIR and SWIR domains was developed (Laroche-Pinel et al., 2021). The model relies on SWP field measures done using a pressure chamber (Scholander et al., 1965), which is a common, robust and precise method to assess vine water status (Acevedo-Opazo et al., 2008). The model was mainly developed from from SWP measures on Syrah N (Laroche Pinel E., 2021). A large scale monitoring was organized in different vineyards in the Mediterranean region in 2021. 10 varieties amongst the most represented in this area were monitored (Cabernet sauvignon N, Chardonnay B, Cinsault N, Grenache N, Merlot N, Mourvèdre N, Sauvignon B, Syrah N, Vermentino B, Viognier B). The model was used to produce water status maps from Sentinel-2 images, starting from the beginning of June (fruit set) up to September (harvest). The average estimated SWP for each vine was compared to actual field SWP measures done by wine growers or technicians during usual monitoring of irrigation programs. The correlations between mean estimated SWP and mean measured SWP were at the same level than expected by the model. (Laroche Pinel, 2021) The general SWP kinetics were comparable. The estimated SWP would have led to same irrigation decisions concerning the date of first irrigation in comparison with measured SWP. Acevedo-Opazo, C., Tisseyre, B., Ojeda, H., Ortega-Farias, S., Guillaume, S. (2008). Is it possible to assess the spatial variability of vine water status? OENO One, 42(4), 203. Cohen, Y., Gogumalla, P., Bahat, I., Netzer, Y., Ben-Gal, A., Lenski, I., … Helman, D. (2019). Can time series of multispectral satellite images be used to estimate stem water potential in vineyards? In Precision agriculture ’19, The Netherlands: Wageningen Academic Publishers, pp. 445–451. Laroche-Pinel, E., Duthoit, S., Albughdadi, M., Costard, A. D., Rousseau, J., Chéret, V., & Clenet, H. (2021). Towards vine water status monitoring on a large scale using sentinel-2 images. remote sensing, 13(9), 1837. Laroche-Pinel,E. (2021). Suivi du statut hydrique de la vigne par télédétection hyper et multispectrale. Thèse INP Toulouse, France. Scholander, P.F., Bradstreet, E.D., Hemmingsen, E.A., & Hammel, H.T. (1965). Sap pressure in vascular plants: Negative hydrostatic pressure can be measured in plants. Science, 148(3668), 339–346.

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.

A unique “terroir” can be found in southern Bolivia, which combines the specific features of climate, topography and altitude of high valleys, with the management of grapevines staked on trees. It is one of the rare remnants of agroforestry viticulture. A survey was carried out among 29 grapegrowers in three valleys, to characterize the structure and management of these vineyards, and identify the services they expect from trees. Farms were small (2.2 ha on average) and 85% of vineyards were less than 1 ha. Viticulture was associated with vegetable, fruit and fodder production, sometimes in the same fields. Molle trees were found in all plots, together with one or two other native tree species. Traditional grapevine varieties such as Negra Criolla, Moscatel de Alejandría and Vicchoqueña were grown with a large range of densities from 1550 to 9500 vines ha-1. From 18 to 30% of them were staked on trees, with 1.2 to 4.9 vines per tree. The management of these vineyards (irrigation, fertilization and grapevine protection) was described, the most particular technical operation being the coordinated pruning of trees and grapevines. Three types of management could be identified in the three valleys. Grapegrowers had a clear idea of the ecosystem services they expected from trees in their vineyards. The main one was protection against climate hazards (hail, frost, flood). Then they expected benefits in terms of pest and disease control, improvement of soil fertility and resulting yield. At last, some producers claimed that tree-staking was quicker and cheaper than conventional trellising. It can be hypothesized then that agroforestry is a promising technique for the agroecological transition of viticulture. Its contribution to the “terroir” of the high valleys of southern Bolivia and its link with the specificities of the wines and spirits produced there remain to be explored.

Grapevine yield has been historically overlooked, assuming a strong trade-off between grape yield and wine quality. At present, menaced by climate change, many vineyards in Southern France are far from the quality label threshold, becoming grapevine yield-gaps a major subject of concern. Although yield-gaps are well studied in arable crops, we know very little about grapevine yield-gaps. In the present study, we analysed the environmental component of grapevine yield-gaps linked to climate and soil resources in the Languedoc Roussillon. We used SAFRAN data and IGP Pays d’Oc wine yields from 2010 to 2018. We selected climate and soil indicators proving to have a significant effect on average wine yield-gaps at the municipality scale. The most significant factors of grapevine yield were the Soil Available Water Capacity; followed by the Huglin Index and the Climatic Dryness Index. The Days of Frost; the Soil pH; and the Very Hot Days were also significant. Then, we clustered geographical zones presenting similar indicators, facilitating the identification of resources yield-gaps. We discussed the number of zones with the experts of IGP Pays d’Oc label, obtaining 7 zones with similar limitations for grapevine yield. Finally, we analysed the main resources causing yield-gaps and the grapevine varieties planted on each zone. Mapping grapevine resource yield-gaps are the first stage for understanding grapevine yield-gaps at the regional scale.

Effects of climate change on viticulture systems and winemaking processes are being felt across the world. The IPCC 6thAssessment Report concluded widespread and rapid changes have occurred, the scale of recent changes being unprecedented over many centuries to many thousands of years. These changes will continue under all emission scenarios considered, including increases in frequency and intensity of hot extremes, heatwaves, heavy precipitation and droughts. Wine companies need tools and models allowing to peer into the future and identify the moment for intervention and measures for mitigation and/or avoidance. Previously, we presented conceptual guidelines for a 5-stage framework for defining adaptation strategies for wine businesses. That framework allows for direct comparison of different solutions to mitigate perceived climate change risks. Recent global climatic evolution and multiple reports of severe events since then (smoke taint, heatwave and droughts, frost, hail and floods, rising sea levels) imply urgency in providing effective tools to tackle the multiple perceived risks. A coordinated drive towards a higher level of resilience is therefore required. Recent publications such as the Australian Wine Future Climate Atlas and results from projects such as H2020 MED-GOLD inform on expected climate change impacts to the wine sector, foreseeing the climate to expect at regional and vineyard scale in coming decades. We present examples of practical application of the Climate Change Adaptation Framework (CCAF) to impacts affecting wine production in two wine regions: Barossa (Australia) and Douro (Portugal). We demonstrate feasibility of the framework for climate adaptation from available data and tools to estimate historical climate-induced profitability loss, to project it in the future and to identify critical moments when disruptions may occur if timely measures are not implemented. Finally, we discuss adaptation measures and respective timeframes for successful mitigation of disruptive risk while enhancing resilience of wine systems.