Terroir and Typicity: proposed definitions for two essential concepts in the understanding of Geographical Indications and sustainable development

Terroir studies are common nowadays but few have used precise pedoclimatic measures in order to evaluate the precocity potential. The objectives of this work were (i) to assess the effect of main terroir parameters (soil, climate and topography) influencing the phenological development of the vine, and (ii) to evaluate a geostatistic approach by using a high number of already existing plots (higher variability) to analyze the terroir parameters’ impact.

Consumer expectations are increasingly shifting towards “residue-free wines.” However, from an analytical standpoint, “zero” does not exist. Laboratories often use the quantification limits of analysis methods to signify ‘zero.’ Improved techniques now allow for the quantification of levels that were previously undetectable. This is why we prefer to use the term “unquantifiable residue” rather than “absence of residues.”

Aromatic composition contributes mainly to the quality aroma of white wine. A natural and gradual evolution of the aroma in the bottle occurs over storage with a very low oxygen content.

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).

Although several studies investigated the impact of crop size or fruit zone microclimate on aromatic or phenolic composition of wines, the effects of these two practices were not assessed and compared in the same study through a technological experiment within the same vineyard. Therefore, their relative effectiveness is hard to compare, which in turn is essential for providing producers with valuable information as a basis to choose adequate approach in yield and canopy management. The aim of the study was to investigate the effects of two crop sizes and two different fruit zone microclimate conditions obtained by leaf removal in a two-factorial experiment, in order to assess and compare their relative impact on Istrian Malvasia (Vitis vinifera L.) white wine aroma and phenolic composition.