Influence of processing parameters on aroma profile of conventional and ecological Cabernet-Sauvignon red wine during concentration by reverse osmosis

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There is a growing trend on the transition from conventional to agroecological management of vineyards. However, the impact of practices, such as reduced-tillage, organic fertilization and cover crops, is not well-understood regarding the soil microbial diversity, and its relationship with the soil physicochemical properties in the subsurface depth near the rooting zone. Soil bacterial diversity is an important contributor towards plant health, productivity and response to environmental stresses. A field experiment was conducted by sampling subsurface soil bacterial community (NGS and qPCR) near to the root zone of Macabeu and Xarel·lo vineyards, located at the Penedes. 3 organic (ECO) and 3 conventional (CON) vineyards, with more than 10 years of respective management were sampled (n=5 each plot). ECO practices did not affect bacterial and fungal abundance but increased significantly the ammonium oxidizing bacteria and alpha-diversity (Inv.Simpson). Interestingly beta-diversity was significantly affected by the management strategy. ANOSIM-tests revealed a significative effect of the management (ecological vs conventional) and plot, on the soil microbial structure (ASV abundance). Main phyla depicted were Proteobacteria, Actinobacteria and Acidobacteria, whose relative abundances were not affected by the management. EdgeR assay revealed a significant increase of Cyanobacteria and decrease of Gemmatimonadetes and Firmicutes phyla in ECO. Interestingly, the grapevine variety was not correlated with the soil microbial community structure. Mantel-test revealed an important correlation (Spearman) of some physicochemical parameters with the soil microbiota structure, in order of importance: texture, EC, pH Ca/Mg, Mg/P, K+, Mg2+, Ca2+, SO42-, and OM. N-NH4 and NTK, which were higher in the ECO managed soils, did not correlated significantly with the soil microbiome population. The results revealed the importance of combining a deep physicochemical characterization of each replicate with the microbial diversity assessment to gain better insights on the relationship between soil microbiome and vineyard management.

Water status impact in viticulture has been widely explored, as it strongly affects grapevine physiology and grape chemical composition. It is considered as a key component of vitivinicultural terroir. Most of the studies concerning grapevine water status have focused on either physiological traits, or berry compounds, or traits involved in wine quality. Here, the response of grapevine to water availability during the ripening period is assessed through non-targeted metabolomics analysis of grape berries by ultra-high resolution mass spectrometry. The grapevine water status has been assessed during 2 consecutive years (2019 & 2020), through carbon isotope discrimination on juices from berries collected at maturity (21.5 brix approx.) for 2 Vitis vinifera cv. Pinot noir (PN) and Chardonnay (CH). A total of 220 grape juices were collected from 5 countries worldwide (Italy; Argentina; France; Germany; Portugal). Measured δ13C (‰) varied from -28.73 to -22.6 for PN, and from -28.79 to -21.67 for CH. These results also clearly revealed higher water stress for the 2020 vintage. The same grape juices have been analysed by Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR-MS) and Liquid Chromatography coupled to Mass Spectrometry (LC-qTOF-MS), leading to the detection of up to 4500 CHONS containing elemental compositions, and thus likely tens of thousands of individual compounds, which include fatty acids, organic acids, peptides, phenolics, also with high levels of glycosylation. Multivariate statistical analysis revealed that up to 160 elemental compositions, covering the whole range of detected masses (100 –1000 m/z), were significantly correlated to the observed gradients of water status. Examples of chemical markers, which are representative of these complex fingerprints, include various derivatives of the known abscisic acid (ABA), such as phaesic acid or abscisic acid glucose ester, which are significantly correlated with higher water stress, regardless of the variety. Cultivar-specific behaviours could also be identified from these fingerprints. Our results provide an unprecedented representation of the metabolic diversity, which is involved in the water status regulation at the grape level, and which could contribute to a better knowledge of the grapevine mitigation strategy in a climate change context.

The research includes an analysis of the impact of weather conditions on phenological development of the vine and grape quality, through monitoring of four experimental cultivars (Chardonnay, Graševina, Merlot and Plavac mali) over two production years. In each experimental vineyard, which were evenly distributed throughout the regions of Slavonia and The Croatian Danube, Croatian Uplands,

The main innovation in the VINIoT service is the joint use of two technologies that are currently used separately: vineyard monitoring using multispectral imaging and deployed terrain sensors. One part of the system is based on the development of artificial intelligence algorithms that are feed on the images of the multispectral camera and IoT sensors, high-level information on water stress, grape ripening status and the presence of diseases. In order to obtain algorithms to determine the state of ripening of the grapes and avoid losing information due to the diversity of the grape berries, it was decided to work along the first year 2020 at berry scale in the laboratory, during the second year at the cluster scale and on the last year at plot scale. Different varieties of white and red grapes were used; in the case of Galicia we worked with the white grape variety Treixadura and the red variety Mencía. During the 2020 and 2021 campaigns, multispectral images were taken in the visible and infrared range of: 1) sets of 100 grapes classifying them by means of densimetric baths, 2) individual bunches. The images taken with the laboratory analysis of the ripening stage were correlated. Technological maturity, pH, probable degree, malic acid content, tartaric acid content and parameters for assessing phenolic maturity, IPT, anthocyanin content were determined. It has been calculated for each single image the mean value of each spectral band (only taking into account the pixels of interest) and a correlation study of these values with laboratory data has been carried out. These studies are still provisional and it will be necessary to continue with them, jointly with the training of the machine learning algorithms. Processed data will allow to determine the sensitivity of the multispectral images and select bands of interest in maturation.