Soil Temperature and Climate Change: Implications for Mediterranean Vineyards 

Copper in white wine can be associated with Cu(II) organic acids (Cu fraction I), Cu(I) thiol species (Cu fraction II), and Cu sulfides (Cu fraction III). The first two fractions are associated with the repression of reductive aromas in white wine, but these fractions gradually decrease in concentration during the normal bottle aging of wine. Although exposure of white wine to fluorescent light is known to induce the accumulation of volatile sulfur compounds, causing light-struck aroma, the influence on the loss of protective Cu fractions is uncertain. Riboflavin is known to be a critical initiator of photochemical reac-tions in wine, but the rate of its decay under short-term light exposure in different coloured bottles and for wine of different oxygen concentrations is not well understood.

The need to rationalize agricultural inputs has recently increased interest in assessing vineyard variability in order to implement variable rate input applications, so-called ‘precision viticulture’. In many viticultural areas globally, precision viticulture is already widely used such as for selective harvesting and variable rate application (VRA) of inputs such as irrigation and/or fertilizer. Robust VRA relies on having a geostatistically accurate map (of one or more vineyard attributes) requiring high sampling densities, which can be cost- and time-prohibitive to obtain. Previous work on spatial interpolation using kriging have upscaled ground-based measurements, but such upscaling strategies are applicable only when vineyard conditions are spatially continuous and satisfies the assumption of second-order stationary processes. Alternatively, mixed models that combine kriging and auxiliary information, such as the regression kriging (RK) method, are more instructive for spatial predictions. In order to improve prediction accuracies, it is therefore necessary to incorporate additional information to achieve accurate spatial patterns with low error.

“Pinking” is a term used to define an abnormal pink coloration assumed by white wines in certain cases. Despite the are many hypotheses about the causes of this phenomenon, pinking still represents an issue for the wine industry. In the absence of reliable preventive strategies, wineries often rely on treatments such as charcoal fining, which is also negatively impacting wine aroma. This study aims at evaluating the potential of different fining agents based on animal or vegetal proteins to prevent wine pinking when applied at the level of must clarification. The work was carried out on Lugana wines, which is well-recognised as sensible to pinking problems. METHODS: Two experimental Lugana musts were obtained by applying a standard winemaking protocol and were then clarified with different commercial preparations based on vegetal proteins or casein, alone or in combination with PVPP. A control only using pectolytic enzyme was also prepared. Finings were carried out at 4°C for 16h, and the clear must (200 NTU) was then fermented in controlled conditions.

The accession Criolla Chica Nº2 (CCN2) is catalogued as a floral mutation of cultivar Criolla Chica (synonym for cv. Listán Prieto). Contrary to what is observed in hermaphrodite-cultivated varieties like Criolla Chica, CCN2 exhibits a prevalence of masculinized flowers. Aiming to study the incidence and phenotypical implications of this mutation, CCN2 plants were deeply studied using Criolla Chica ‘Ballista’ (CCBA) as control plants. For each CCN2 plant, two inflorescences per shoot were sampled and segmented into proximal, mid and distal positions, relative to the pedicel. Flowers were observed through magnifying lens and classified according to OIV151 descriptor.

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).