Caractérisation et gestion de la maturation par terroir en Champagne

As viticulture faces challenges such as climate change or vineyard dieback, the choice of the variety and rootstock becomes more and more crucial. To study rootstock levers in the Bordeaux region, a parcel of Cabernet Sauvignon (CS) was planted with four rootstocks in 2014. Twenty repetitions of each of the following four rootstocks were set up: 101-14 MGt, Nemadex AB, 420A MGt and Gravesac. The number of bunches, yields and pruning weights of the vine shoots were measured individually on 240 vines from 2017 to 2021. Since 2020, nitrogen status assessed by assimilable nitrogen level, hydric status assessed by δ13C and berry maturity were measured on 80 samples taken from 20 repetitions of the four rootstocks. A lower yield was measured for CS grafted onto Nemadex AB due to the lower number of bunches and the lower weight of berries. The differences between the other three rootstocks are small, but CS grafted onto 420A MGt was the most productive. The CS grafted onto Nemadex AB had the lowest pruning weight while 101-14 MGt had the highest. In 2020, δ13C showed a more moderate water stress with 101-14 MGt and 420A MGt than with Nemadex AB. Surprisingly, the Gravesac was under more stress than the 101-14 MGt. The nitrogen status in the berries was better for Nemadex AB but this was perhaps due to the significantly lower weight of the berries.Rootstock 101-14 MGt attained the highest accumulation of sugars in the berries while 420A MGt allows to preserve higher acidity. The parcel is still young which may explain some of the results. These measures must therefore be continued over the next several years to fully assess the effects of these rootstocks on the development of the vines and the quality of the production under new climatic conditions.

The use of rootstock of American origin has been the classic method of fighting against Phylloxera for more than 100 years. For this reason, it is interesting to establish if different rootstock modifies nutrient composition as well as trace elements content that could be important for determining the traceability of the vine products. A survey of four classic rootstocks (110-Richter, SO4, FERCAL and 1103-Paulsen) and four new ones (M1, M2, M3 and M4) provided by Agromillora Iberia. S.L.U., all of them grafted with the Tempranillo variety, has been carried out during 2019. The eight rootstocks were planted in pots of 500 cc, on three soils with very different characteristics from Castilla-La Mancha (Spain). In the month of July, the leaves were collected and dried in a forced air oven for seven days at 40ºC. Then, the samples were prepared for the analysis determination, carried out by X-Ray fluorescence spectrometry. The results obtained showed that in the case of content in mineral elements in leaf, separated by soil type, we can report the importance of few elements such as Si, Fe, Pb and, especially, Sr. The rootstock does not influence the composition of the vine leaf for the studied elements that are the most important in determining the geochemical footprint of the soil. The influence of the soil can be discriminated according to some elements such as Fe, Pb, Si and, especially, Sr.

With contemporary climate change, cultivated Vitis vinifera L. is at risk as climate is a critical component in defining ecologically fitted plant materiel. While winegrowers can draw on the rich diversity among grapevine varieties to limit expected impacts (Morales-Castilla et al., 2020), replacing a signature variety that has created a sense of local distinctiveness may lead to several challenges. In order to sustain wine identity in uncertain climate outcomes, the study of intra-varietal diversity is important to reflect the adaptive and evolutionary potential of current cultivated varieties. The aim of this ongoing study is to understand to what extent can intra-varietal diversity be a climate change adaptation solution. With a focus on early (Sauvignon blanc, Riesling, Grolleau, Pinot noir) to moderate late (Chenin, Petit Verdot, Cabernet franc) ripening varieties, data was collected for flowering and veraison for the various studied accessions (from conservatory plots) and clones. For these phenological growing stages, heat requirements were established using nearby weather stations (adapted from the GFV model, Parker et al., 2013) and model performances were verified. Climate change projections were then integrated to predict the future behaviour of the intra-varietal diversity. Study findings highlight the strong phenotypic diversity of studied varieties and the importance of diversification to enhance climate change resilience. While model performances may require improvements, this study is the first step towards quantifying heat requirements of different clones and how they can provide adaptation solutions for winegrowers to sustain local wine identity in a global changing climate. As genetic diversity is an ongoing process through point mutations and epigenetic adaptations, perspective work is to explore clonal data from a wide variety of geographic locations.

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.

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).