Vine nitrogen status and the terroir effect: a study on cv. Doral in the Vaud vineyard (Switzerland)

Polyphenolic compounds are considered to have a major impact on the quality of red wines. Sensory impact, such as astringency and bitterness, stems directly from tannin composition. Thenceforth, quick analytical measurement of phenolic compounds appears to be a real challenge for winemaking monitoring and process control. Many methods were developed to analyzed polyphenols in wine, but they are time-consuming and require chemistry skills and equipment, not suitable for a rapid routine analysis. A reliable and rapid method to obtain this kind of measurement is Fourier Transform Infrared (FTIR) spectroscopy.

The production of red sparkling wines is lower in Spain in comparison with the winemaking of white or rosé sparkling wines. In red sparkling wine processing it is essential to obtain suitable base wines that should have moderate alcohol content, high acidity, good color values, an adequate mouth-feel and a sweet tannin. Grapes for sparkling wine production have to be harvested at low maturity stages, with lower alcohol contents and higher acidities, which will that the phenolic maturity of the grapes is also low, showing green tannins. This paper analyses different treatments in order to minimize these inconveniences: cold maceration-prefermentation and delestage to elaborate the grapes with lower maturity, must nanofiltration, and the partial osmosis of the wines made from grapes with an adequate maturity degree.

Favoring the formation of volatile compounds and their precursors in must and wine represent one of the principal goals during winemaking technology. In recent years, most attention has been placed on using glycosidases to enlarge the aroma profile of white wines. The effect of enzymes makes odorless glycosidically-bound precursors be converted into aromatic compounds. This paper focuses to study the influence of enzymes (pectolytic and β-glycosides) administered before alcoholic fermentation, even if most studies analyze their use in different winemaking stages. Two semi-aromatic varieties such as Fetească regală and Sauvignon blanc were chosen.

Sustainable weed control with little detrimental effects on vine physiology, yield, berry quality, soil structure, health and biodiversity is a key factor in vineyard management. Few options are available to avoid herbicide utilization and minimize negative effects of frequent tillage on soil quality. The present project aims to investigate and develop different cover management strategies in a cool climate viticultural region in Switzerland. The impact of different treatments on vine, must and wine has been studied in an experimental vineyard in Changins, Switzerland for one year and will be continued over the next three years.

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).