Determinazione della frazione aromatica dei vini, quale strumento per-la valorizzazione del territorio viticolo

Knowledge has been accumulated on the impact of microclimate, in particular berry temperature and irradiation, for a wide range of red varieties. However, little research has been dedicated on the effects of the same factors on the quality of white grape varieties.

Botrytis bunch rot occurrence is one of the most important limitations for the wine industry in humid environments. A positive correlation between grapevine growth and susceptibility to fungal pathogens has been found. In theory the effect of grapevine vegetative growth on bunch rot expression results from direct effects (cluster architecture, nitrogen status among others) and indirect ones (via microclimate). However, a reduction in bunch rot incidence can be achieved in some circumstances without major vine growth reduction. The present study was aimed to test the general hypothesis that bunch rot susceptibility is affected by vine vigor, but other factors associated with grapevine vegetative expression could be even more relevant.

The AOC Gaillac area is divided into three main terroirs : « The left bank terraces », « The right bank coteaux » and
« The plateau Cordais ». This division is valid at a regional scale, but it suffers of a number of local-scale exceptions. This spatial variability of the pedologic-geologic characteristics at the plot scale has been derived mainly from the main late-Würmian solifluxion phase occurring at the transition between the peri-glacial climate and the Holocene temperate conditions (13,000-10,000 yrs BP).

Volatile compounds play a significant role on the organoleptic properties defining wines quality. This particular role was exploited in several studies with the aim to differentiate wines from a more or less extensive production area, according to their sensory profile [1], as well as their chemical composition [2,3] (Di Paola-Naranjo et al., 2011; Kustos et al., 2020). Indeed, since aroma compounds development in grapes depends primarily on the environmental conditions of the vines and grapes (soil and climate), it is conceivable that these parameters craft the aromatic signature of the wine produced, in relation to its origin (Van Leeuwen et al., 2020). In this work, a general study on the aromatic and sensorial profile of wines produced in five sub-regions of the Corbières denomination, a renowned red grape varieties viticultural region in South France, was reported.

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).