Influence de l’ensoleillement sur la composante aromatique des baies de raisin

In recent years, developing more efficient and sustainable viticulture management has been essential due to the impact of climate change in semiarid regions. For this reason, the use of recycled organic mulching (ROM) in the vineyard has become an interesting strategy to cope with water stress, isolated soil from extreme temperatures and improving soil humidity, control the presence of weeds and therefore reduce the inputs of herbicides and improve soil fertility. This work aimed to analyse the effect of three different organic mulches [straw (S), grape pruning debris (GPD) and spent mushroom compost (SMC)] and two traditional soil management techniques [herbicide (H) and interrow (IN)] on weed coverage and the spontaneous plant communities’ presence. Data sampling was collected throughout the vine vegetative cycle of 2021 in La Rioja, Spain. The different soil management techniques had a clear effect on weed coverage and his development during the vine vegetative cycle. SMC and H were the treatments with the highest and the lowest coverage percentage, respectively. IN had a delayed weed emergence at the beginning of the vine vegetative cycle, but finally it reached maximum values nearby SMC. GPD and S had similar effects on weed emergence, reaching 25-30% of the maximum coverage values. A total of 29 herbaceous species were identified during the vegetative cycle, some of them very isolated and occasional. Principal component analysis (PCAs) showed a good association between spontaneous species and treatments, furthermore, specific species-treatment associations were found. Moreover, three clear groups of herbaceous communities were identified by cluster analysis. This study provides interesting information about the effect of different alternative soil management on herbaceous plant coverage and weed species communities which could contribute to making more sustainable viticulture.

The Languedoc-Roussillon wineries are facing a decline in wine yields particularly PGI yields due to many factors. Climate change is just ones, but is expected to increase in the future. There is also structurally a large heterogeneity of yield profiles among terroirs, varieties and strategies. This work investigates the link between yield, competitiveness and resilience to explore how resilient winegrowers have been in the recent past. To this end two approaches have been combined; (i) an accountancy database analysis at estate scale and (ii) municipality level competitiveness analysis. A new resilience indicator that characterizes the capacity of an estate to absorb yield variation is also defined. The FADN database between 2000 and 2018 of ex-Languedoc-Roussillon (France) and other data are used to analyse the current situation and the past evolution of competitiveness and resilience by type of estate (type of farm: PGI and/or PDO & type of commercialization: bulk and/or bottles). The net margin, which defines competitiveness, is not correlated to yield for all types but depends on the type of commercialization and the level of specialisation. The resilience indicator shows that the net margin of estates specialized in PGI is particularly sensitive to yield declines. We also show that price evolutions seem to compensate the effect of yield losses for the majority of types. Municipality scale analysis shows the links between local pedoclimate, yield, commercialization strategies and price. Overlapping a PDO with a PGI does not always increase a municipality’s PGI competitiveness. It is difficult to make links between causes and effects due to the complexity of the wine production system. Production diversification may be a solution. Resorting to the two level of analysis helps resolving the data gap that is necessary to explore the links between yield and economic performance of the wine estates in the long term.

Spatial variability of vine productivity in winegrapes is important to characterise as both yield and quality are relevant for the production of different wine styles and products. The objectives were to understand how patterns of variability of Cabernet Sauvignon fruit composition changed over time and space, how these patterns could be characterised with indirect measurements, and how spatial patterns of the variation in fruit compositional attributes can aid in improving management. Prior to the 2017 vintage, 125 data vines were distributed across each of four vineyards in the Lodi American Viticultural Area (AVA) of California. Each data vine was sampled at commercial harvest in 2017, 2018, and 2019. Yield components and fruit composition were measured at harvest for each data vine, and maps of yield and fruit composition were produced for eight ‘objective measures of fruit quality’: total anthocyanins, polymeric tannins, quercetin glycosides, malic acid, yeast assimilable nitrogen, β-damascenone, C6 alcohols and aldehydes, and 3-isobutyl-2-methoxypyrazine. Patterns of variation in anthocyanins and phenolic compounds were found to be most stable over time. Given this relative stability, management decisions focused on fruit quality could be based on zonal descriptions of anthocyanins or phenolics to increase profitability in some vineyards. In each vineyard, dormant season pruning weights and soil cores were collected at each location, elevation and soil apparent electrical conductivity surveys were completed, and remotely sensed imagery was captured by fixed wing aircraft and two satellite platforms at major phenological stages. The data collected were used to develop relationships among biophysical data, soil, imagery, and fruit composition. The standardised and aggregated samples from four vineyards over three seasons were included in the estimation of ‘common variograms’ to assess how this technique could aid growers in producing geostatistically rigorous maps of fruit composition variability without cumbersome, single season sampling efforts.

Monitoring vine water status is a major challenge for vineyard management because it influences both yield and harvest quality. It is also a challenge at the territorial scale for identifying periods of high water restriction or zones regularly impacted by water stress. This information is of major importance for defining collective strategies, anticipating harvest logistic or applying for irrigation authorisation. At this spatial scale, existing tools and methods for monitoring vine water status are few and often require strong assumptions (e.g. water balance model). This paper proposes to consider a collaborative collection of observations by winegrowers and wine industry stakeholders (crowdsourcing) as an interesting alternative. Indeed, it allows the collection of a large number of field observations while pooling the collection effort. However, the feasibility of such a project and its interest in monitoring vine water status at regional scale has never been tested.

The objective of this article is to explore the possibility of making a regional map of vine water status based on crowdsourcing observations. It is based on the study of the free mobile application ApeX-Vigne, which allows the collection of observations about vine shoot growth. This information is easy to collect and can be considered, under certain conditions, as a proxy for vine water status. This article presents the first results obtained from the nearly 18,000 observations collected by winegrowers and wine industry stakeholders during 2019, 2020 and 2021 seasons. It presents the vine shoot growth maps obtained at regional scale and their evolution over the three vintages studied. It also proposes an analysis of the factors that favoured the number of observations collected and those that favoured their quality. These results open up new perspectives for monitoring vine water status at a regional scale but above they provide references for other crowdsourcing projects in viticulture.

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).