NIR based sensometric approach for consumer preference evaluation

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).

There is evidence in the literature that non-volatile wine matrix can modify the release and therefore the perception of the compounds involved in wine aroma [1-3].

The ’Furmint’ is the most important grape variety in the Tokaj Wine Region, constituting around 65% of its vineyard area. Before the phylloxera disease many types were grown, but as selection started in the 20th century, its diversity dramatically narrowed. As a result, the cultivation of Furmint was based mainly on two heavy-cropping clones, T.85 and T.92 at the end of the ’80s. Aims of present clone research take into account that after solely quantity as target, quality emerged in the 1990’s and most recently, typicity appeared as more private estates began their own selection program.

Wine quality may be compromised by mouldy off‒flavours related to cork taint. Although different compounds are considered to be involved in this wine defect, haloanisoles (HAs), and among them the 2,4,6-trichloroanisole (TCA), are claimed as the main responsible.

The year-on-year rise in temperatures and the increase in extreme weather events due to climate change are already having an impact on agriculture. Among the perennial fruit species, grapevine is already negatively impacted by these events through an acceleration of its phenology, more damage from late frosts or through an increase in the sugar level of the berries (and therefore the alcoholic degree of the wine) and a decrease of acidity, impacting the wine quality. Sun’Agri, in partnership with INRAE, Chambre d’agriculture du Vaucluse, Chambre d’agriculture des Pyrénées-Orientales and IFV, developed a protection system based on dynamic agrivoltaics to protect grapevine. It consists of photovoltaic solar panels positioned above the crop, high enough not to impede the passage of agricultural machinery, and tiltable from +/- 90° to adjust the level of shading on the vineyard. These smart louvers, driven by artificial intelligence (physical models & plant growth models), are steered according to the plant’s needs and provide real climate protection.