Identification of key-odorants in Sauternes Wines

Protected Designation of Origin “Jumilla” (PDO Jumilla) is located in the Spanish provinces of Albacete and Murcia, in the South-eastern part of the Iberian Peninsula, where most of the models predict a severe impact of climate change in next decades. PDO Jumilla covers an area of 247,054 hectares, of which more than 22,000 hectares

The favorable effect of symbiosis with arbuscular mycorrhizal fungi (AMF) has been known and studied since the 60s. Nowadays, many companies took the chance to start promoting and selling commercial inoculants of AMF, in order to be used as biofertilizers and encourage sustainable biological agriculture. However, the positive effect of these commercial biofertilizers on plant growth is not always demonstrated, especially under field conditions. In this study, we used a commercial inoculum on newly planted grapevines of a local cultivar grafted on a common rootstock R110. We followed the physiological status of vines, growth and productivity and functional biodiversity of soil bacteria during the first and second years of 20 inoculated with commercial inoculum bases on Rhizophagus irregularis and Funeliformis mosseaeAMF at field planting time and 20 non-inoculated control plants. All the parameters measured showed a neutral to negative effect on plant growth and production. The inoculated plants always presented lower values of photosynthesis, growth and grape production, although in some cases the differences did not reach statistical significance. On the contrary, the inoculation supposed an increase of the bacterial functional diversity, although the differences were not statistically significant either. Several studies show that the effect of inoculation with AMF is context-dependent. The non-favorable effects are probably due to inoculation ineffectiveness under complex field conditions and/or that, under certain conditions, AMF presence may be a parasitic association. This puts into question the effectiveness of its application in the field. Therefore, it is recommended to only resort to this type of biofertilizer when the cultivation conditions require it (e.g., very low previous microbial diversity, foreseeable stress due to drought, salinity, or lack of nutrients) and not as a general fertilization practice.

Grapevine yield is a key indicator to assess the impacts of climate change and the relevance of adaptation strategies in a vineyard landscape. At this scale, a yield model should use a number of parameters and input data in relation to the information available and be able to reproduce vineyard management decisions (e.g. soil and canopy management, irrigation). In this study, we used data from six experimental sites in Southern France (cv. Syrah) to calibrate a model of grapevine yield limited by water constraint (GraY). Each yield component (bud fertility, number of berries per bunch, berry weight) was calculated as a function of the soil water availability simulated by the WaLIS water balance model at critical phenological phases. The model was then evaluated in 10 grapegrowers’ plots, covering a diversity of biophysical and technical contexts (soil type, canopy size, irrigation, cover crop). We identified three critical periods for yield formation: after flowering on the previous year for the number of bunches and berries, around pre-veraison and post-veraison of the same year for mean berry weight. Yields were simulated with a model efficiency (EF) of 0.62 (NRMSE = 0.28). Bud fertility and number of berries per bunch were more accurately simulated (EF = 0.90 and 0.77, NRMSE = 0.06 and 0.10, respectively) than berry weight (EF = -0.31, NRMSE = 0.17). Model efficiency on the on-farm plots reached 0.71 (NRMSE = 0.37) simulating yields from 1 to 8 kg/plant. The GraY model is an original model estimating grapevine yield evolution on the basis of water availability under future climatic conditions.  It allows to evaluate the effects of various adaptation levers such as planting density, cover crop management, fruit/leaf ratio, shading and irrigation, in various production contexts.

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.

Elevated temperature during the grape maturation period is a major threat for grape quality and thus wine quality. Therefore, characterizing the grape composition response to temperature at a larger scale would represent a crucial step towards adaptation to climate change. In response to changes in temperature, various physiological mechanisms regulate grape composition. Primary and secondary metabolisms are both involved in this response, with well-known effects, for example on anthocyanins, and lesser known effects, for example on aromas or aroma precursors. At the field scale or at the regional scale, however, numerous environmental or plant-specific factors intervene to make the effects of temperature difficult to distinguish from overall variability. In this study, it was attempted to overcome this difficulty by selecting well-characterized situations with differing temperatures.
A long-term study of air temperature variability across several Merlot vineyards in the Saint-Emilion and Pomerol wine producing area found significant temperature differences and gradients at various time scales linked to environmental factors. From this study area, a few sites were selected with similar age, soil and training system conditions, and with repeated and contrasted temperature differences during the maturation period. The average temperature difference during the maturation period was about 2°C between cooler and warmer sites, a difference similar to that expected under future climate change scenarios. In close vicinity to the temperature sensors at each site, grape berries were sampled at different times until full maturity during 2019 and 2020. Also, berries from bunches on either side of the row were analyzed separately, allowing an investigation of bunch exposure effect associated with the coupling of berry temperature and solar radiation. Four replicates of pooled berries for each time – site – bunch exposure combination were obtained and analyzed for biochemical composition. Analyses of variance of the biochemical composition data collected at different sampling times reveal significant effects associated with temperature, site, and bunch azimuth. For instance, anthocyanins in grape skins are clearly influenced by temperature and solar radiation exposure, with up to 30% reduction in warmer conditions.