Rootstocks of prestigious Bordeaux vineyards: implications on quality and yield

“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.

Climate influence on grapevine physiology is prevalent and this influence is only expected to increase with climate change. Although governed by a general determinism, climate influence on grapevine physiology may present variations according to the terroir. In addition, these site-specific differences are likely to be enhanced when climate influence is studied using farm data. Indeed, farm data integrate additional sources of variation such as a varying representativity of the conditions actually experienced in the field. Nevertheless, there is a real challenge in valuing farm data to enable grape growers to understand their own terroir and consequently adapt their practices to the local conditions. In such a context, this article proposes a framework to site-specifically study climate influence on grapevine physiology using farm data. It focuses on improving the analysis of time series of weather data. The analytical framework includes the synchronization of time series using site-specific thermal indices computed with an original method called Extended Growing Degree Days (eGDD). Synchronized time series are then analyzed using a Bayesian functional Linear regression with Sparse Steps functions (BLiSS) in order to detect site-specific periods of strong climate influence on yield development. The article focuses on temperature and rain influence on grape yield development as a case study. It uses data from three commercial vineyards respectively situated in the Bordeaux region (France), California (USA) and Israel. For all vineyards, common periods of climate influence on yield development were found. They corresponded to already known periods, for example around veraison of the year before harvest. However, the periods differed in their precise timing (e.g. before, around or after veraison), duration and correlation direction with yield. Other periods were found for only one or two vineyards and/or were not referred to in literature, for example during the winter before harvest.

The project VINIoT pursues the creation of a new technological vineyard monitoring service, which will allow companies in the wine sector in the SUDOE space to monitor plantations in real time and remotely at various levels of precision. The system is based on spectral images and an IoT architecture that allows assessing parameters of interest viticulture and the collection of data at a precise scale (level of grape, plant, plot or vineyard) will be designed. In France, three subjects were specifically developed: evaluation of maturity, of water stress, and detection of flavescence dorée. For the evaluation of maturity, it has been decided first to work at the berry scale in the laboratory, then at the bunch scale and finally in the vineyard. The acquisition of the spectral hyperstal image as well as the reference analyzes to measure the maturity, were carried out in the laboratory after harvesting the berries in a maturity monitoring context. This work focuses on a case study to predict sugar content of three different grape varieties: Syrah, Fer Servadou and Mauzac. A robust method called Roboost-PLSR, developed in the framework of this work (Courand et al., 2022), to improve prediction model performance was applied on spectra after the acquirement of hyperspectral images. Regarding the evaluation of water stress, to work with a significant variability in terms of water status, it has been worked first with potted plants under 2 different water regimes. The facilities have allowed the supervision of irrigation and micro-climatic conditions. The regression models on agronomic variables (stomatal conductance, water potential, …) are studied. To detect flavescence dorée, the experimental plan has consisted of work at leaf scale in the laboratory first, and then in the field. To detect the disease from hyper-spectral imaging, a combination of multivariate curve resolution-alternating least squares (MCR-ALS) and factorial discriminant analysis (FDA) was proposed. This strategy proved the potential towards the discrimination of healthy and infected leaves by flavescence dorée based on the use of hyperspectral images (Mas Garcia et al., 2021).

Commercial grape production relies on training grapevine cultivars onto a variety of trellis systems. Training allows for well-lit leaves and clusters, maximizing fruit quality in addition to facilitating cultivation, harvesting, and diseases control. Although grapevines can be trained onto an infinite variety of trellis systems, most red and white cultivars are trained to the standard VSP (Vertical Shoot Positioning) system. However, red and white cultivars respond differently to VSP in fruit composition and growth characteristics, which are yet to be fully understood. Therefore, the objective of this study was to examine the influence of the VSP trellis system on fruit composition of three red, Cabernet Sauvignon, Merlot and Syrah, and three white, Chardonnay, Riesling, and Gewurztraminer cultivars grown under uniform growing conditions in the same vineyard. All cultivars were monitored for maturity and harvested at their physiologically maximum possible sugar concentration to compare various fruit quality attributes such as Brix, pH, TA, malic and tartaric acids, glucose and fructose, potassium, YAN, and phenolic compounds including total anthocyanins, anthocyanin profile, and tannins. A distinct pattern in fruit composition was observed in each cultivar. In regards to growth characteristics, Syrah grew vigorously with the highest cluster weight. Although all cultivars developed pyriform seeds, the seed size and weight varied among all cultivars. Also varied were mesocarp cell viability, brush morphology, and cane structure. This knowledge of the canopy architectural characteristics assessed by the widely employed fruit compositional attributes and growth characteristics will aid the growers in better management of the vines in varied situations.

The wine sector is of great relevance and tradition in Mediterranean countries, however, it may be most susceptible to climate change. In recent years, wine production is facing changes worldwide, both at environmental as well as commercial levels, due to global warming and the shift in consumers’ preferences. Wine growers and wine makers are in search of solutions that allow to face these new challenges. One of the most promising initiatives in the long term is the introduction of new plant materials, specifically intraspecific hybridizations between premium varieties that may improve traditional germplasm in its adaptation to climate change. These inter-varietal crosses have the potential to generate quality wines, whilst maintaining the regional typicity, and constitute an attractive alternative for the consumer due to their sensory attributes. In this study, we have evaluated wines from 29 intraspecific Garnacha x Tempranillo hybrids in two different locations, with the aim to assess their oenological potential and sensory attributes. Thirteen of the selections were white and 16 were red. Microvinifications were conducted with two or three replications depending on grape availability. Conventional oenological parameters were determined for all wines. The sensory evaluation and hedonic scores were given by five experts. Red selections obtained higher quality scores than white ones. Among the white selections with higher quality scores, GT-41 Varea and GT-159 Varea outstand, due to their high total acidity and high malic acid content. Regarding red selections, GT-57 Varea and GT-57 UR were perceived as higher in quality, highlighted for their moderate alcoholic and high anthocyanin content. Our results indicate that intraspecific hybridization may be a powerful tool for adapting traditional cultivars to climate change in Rioja.