Study of yeast biocatalytic activity on grape aroma compounds

In response to changes in their environment, grapevines regulate transpiration using various physiological mechanisms that alter conductance of water through the soil-plant-atmosphere continuum. Expressed as bulk stomatal conductance at the canopy scale, it varies diurnally in response to changes in vapor pressure deficit and net radiation, and over the season to changes in soil water deficits and hydraulic conductivity of both soil and plant. It is necessary to characterize the response of conductance to these variables to better model how vine transpiration also responds to these variables. Furthermore, to be relevant for vineyard-scale modeling, conductance is best characterized using data collected in a vineyard setting. Applying a crop canopy energy flux model developed by Shuttleworth and Wallace, bulk stomatal conductance was estimated using measurements of individual vine sap flow, temperature and humidity within the vine canopy, and estimates of net radiation absorbed by the vine canopy. These measurements were taken on several vines in a non-irrigated vineyard in Bordeaux France, using equipment that did not interfere with ongoing vineyard operations. An inverted Penman-Monteith equation was then used to calculate bulk stomatal conductance on 15-minute intervals from July to mid-September 2020. Time-series plots show significant diurnal variation and seasonal decreases in conductance, with overall values similar to those in the literature. Global sensitivity analysis using non-parametric regression found transpiration flux and vapor pressure deficit to be the most important input variables to the calculation of bulk stomatal conductance, with absorbed net radiation and bulk boundary layer conductance being much less important. Conversely, bulk stomatal conductance was one of the most important inputs when calculating vine transpiration, further emphasizing the need for characterizing its response to environmental changes for use in vineyard water use modeling.

Among the different strategies to cope with the negative impacts of climate change on viticulture, the exploitation of genetic diversity is one of the most promising to adapt to new conditions and maintain wine production and quality. One of the biggest concerns in the context of climate change is to improve water use efficiency (WUE). In this way, the use of genotypes that present a better response to drought and high WUE is a key issue. In this work, physiological performance analysis was conducted to compare the water deficit stress (WDS) responses of local and widespread grapevines cultivars. Leaf gas exchange, water use efficiency (WUE) at different levels (leaf and long-term WUE (∆13C)), leaf osmotic adjustment and other water relations parameters were determined in plants under well-watered and WDS conditions alongside assessment of the levels of foliar hormones concentrations. Results denote that local cultivars displayed better physiological performance under WDS as compared to the widely-distributed ones. he results corroborate the hypothesis that better stomatal control allows increasing leaf WUE under drought as occurred in the local Callet cv.; but the minority local cultivar Escursac cv. showed high WUE under both treatments. In this case, high WUE can be related to maintaining higher photosynthetic activity under drought. The different mechanisms underlying the better performance under WDS and high WUE of minority local cultivars are discussed.

In Champagne, the vine adaptation to different climatic and technical changes during these last 20 years can be seen through physiological balance disruptions. These disruptions emphasize the general grapevine decline. Since the 2000s, among other nitrogen stress indicators, the must nitrogen has been decreasing. The combination of restricted mineral fertilizers and herbicide use, the growing variability of spring rainfall, the increasing thermal stress as well as the soil type heterogeneity are only a few underlying factors that trigger loss of physiological balance in the vineyards. It is important to weigh and quantify the impact of these factors on the vine. In order to do so, the Comité Champagne uses two key-tools: networking and modelization. The use of quantitative and harmonized ecophysiological indicators is necessary, especially in large spatial scales such as the Champagne appellation. A working group with different professional structures of Champagne has been launched by the Comité Champagne in order to create a common ecophysiology protocol and thus monitor the vine physiology, yearly, around 100 plots, with various cultural practices and types of soil. The use of crop modelling to follow the vine physiological balance within different pedoclimatic conditions enables to understand the present balance but also predict the possible disruptions to come in future climatic scenarios. The physiological references created each year through the working group, benefit the calibration of the STICS model used in Champagne. In return, the model delivers ecophysiology indicators, on a daily scale and can be used on very different types of soils. This study will present the bottom-up method used to give accurate information on the impacts of soil, climate and cultural practices on vine physiology.

Under-vine (UV) management has traditionally consisted of synthetic herbicide use to limit competition between weeds and grapevines. With growing global interest towards non-synthetic chemical use, this study aimed to capture the effects of alternative UV management at two commercial Shiraz vineyards in South Australia, where the sole management variables were UV management since 2016. In adjacent treatment blocks, cultivation (CU) was compared to spontaneous vegetation (SV) in McLaren Vale (MV), and herbicide was compared to SV in Eden Valley (EV). Soil water infiltration rates were slower and grapevine stem water potential was lower in CU compared to SV in MV, with the latter having a plant community dominated by soursob (Oxalis pes-caprae) during winter; while in EV, there was little separation between the treatments. Yields were affected at both sites, with SV being higher in MV and HE being higher in EV. In MV, the only effect on grape must was a lower 13C:12C isotope ratio in CU, indicating greater grapevine water stress. In the grape must at EV, SV had higher total soluble solids, total phenolics, anthocyanins, and yeast available nitrogen; and lower pH and titratable acidity. Pruning weights were not affected by the treatments in MV, while they were higher in HE at EV. Assessments revealed that the differing soil types at the two sites were likely the main determinants of the opposing production outcomes associated with UV management. In the silty loam soil of MV, the higher yields in SV were likely due to more plant-available water, as a potential result of the continuous soil bio-pores formed by winter UV vegetation. Conversely, in the loamy sand soils of EV with a lower cation exchange capacity, the lower yields and pruning weights in SV suggest the UV vegetation competed significantly with the grapevines for available water and nutrients.

A large varietal collection including over 1700 varieties was maintained in Conegliano, ITA, since the 1950s. Phenological data on a subset of 400 grape varieties including wine grapes, table grapes, and raisins were acquired at bud break, flowering, veraison, and ripening since 1964. Despite the efforts in maintaining and acquiring data over such an extensive collection, the data set has varying degrees of missing cases depending on the variety and the year. This is ubiquitous in phenology datasets with significant size and length. In this work, we evaluated four state-of-the-art methods to estimate missing values in this phenological series: k-Nearest Neighbour (kNN), Multivariate Imputation by Chained Equations (mice), MissForest, and Bidirectional Recurrent Imputation for Time Series (BRITS). For each phenological stage, we evaluated the performance of the methods in two ways. 1) On the full dataset, we randomly hold-out 10% of the true values for use as a test set and repeated the process 1000 times (Monte Carlo cross-validation). 2) On a reduced and almost complete subset of varieties, we varied the percentage of missing values from 10% to 70% by random deletion. In all cases, we evaluated the performance on the original values using normalized root mean squared error. For the full dataset we also obtained performance statistics by variety and by year. MissForest provided average errors of 17% (3 days) at budbreak, 14% (4 days) at flowering, 14.5% (7 days) at veraison, and 17% (3 days) at maturity. We completed the imputations of the Conegliano dataset, one of the world’s most extensive and varied phenological time series and a steppingstone for future climate change studies in grapes. The dataset is now ready for further analysis, and a rigorous evaluation of imputation errors is included.