Progetto di zonazione delle valli di Cembra e dell’Adige. Analisi del comportamento della varietà Pinot nero in ambiente subalpino

País grape has been estimated to arrive to Chile almost 500 years ago, being the first strain grown in this country. Traditionally, this grape has been used to mix with other varieties, to produce poor quality wines, but today is beginning to be used in the production of high quality wines. However, very little is known about the chemical characteristics of this variety. The aroma is one of the most important quality attributes of wine. Volatile compounds of this beverage may come from the grape (varietal aromas), from the fermentation process, from the ageing. The aromatic compounds are found in the grape in two forms: as free volatile compounds and as non-volatile compounds. The last ones, are aroma precursors present mainly as glycoconjugates formed by a sugar and an aglycone…

Natural factors such as the environment in which the vine is grown play an important role in the quality of the wine. If you want to produce a good wine, it is indeed essential to produce quality grapes. To do this, we must enhance and optimize the terroir effect which, for the moment, plays a role that is not very well known. It is therefore essential, for example, to have scientifically established and well quantifiable relationships in order to have the system of areas of controlled origin accepted. R. Morlat (1989) and G. Seguin (1970) have already carried out studies on the role of certain soil factors on grape quality. In particular, they showed the importance of soil temperature and water content.

Wine polysaccharides (PS) play an important role in balancing mouthfeel and stability of wine and even influence aroma volatility. Despite this, there is limited research into the effect of winemaking additives on the polysaccharide profile and other macromolecules of New Zealand (NZ) Pinot noir wine. In this study the influence of a selection of commercial S. cerevisiae strains on the chemical profile, including polysaccharides, of New Zealand Pinot noir (PN) wine was investigated. Research scale PN fermentations using five strains of commercially available S. cerevisiae (Lalvin EC1118 and RC212, Levuline BRG YSEO, Viallate Ferm R71 and R82) were undertaken. PS were qualified and quantified using HPLC-RID.

Pendant une période de trois années le comportement productif et qualitatif de trois cépages tous indigènes de la région de Campania (Italie méridionale) dans deux terroirs de l’île d’Ischia a été étudié; ceci pour obtenir quelques indications préliminaires sur le comportement productif et qualitatif des cépages et sur la qualité des vins.

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).