The revision of the delimitation of the AOC “Champagne”

The wine sector generates a considerable amount of wealth but is facing a growing problem of fraud. Wine counterfeiting is one of the oldest and most common cases of food fraud worldwide. Therefore, the authenticity and traceability of wine are major concerns for both the industry and consumers. To address these issues, robust and reliable analysis and control methods are necessary. Several methods have been developed, ranging from simple organoleptic tests to more advanced methodologies such as isotopic techniques or residual radioactivity measurements.

The use of glutathione (GSH) in winemaking has been legitimated recently, according to OIV resolutions OENO 445-2015 and OENO 446-2015 a maximum dose of 20 mg/L is now allowed to use in must and wine. Several studies have proven the benefits of GSH, predominantly in Sauvignon blanc. Thus, oxidative coloration of must and wine is limited, aroma compounds such as volatile thiols are preserved, and the development of ageing flavors such as sotolon and 2-aminoacetophenone is impeded. The protective effect may be explained by the high affinity of GSH to bind o-quinones which are formed during phenolic oxidation and which are known to initiate browning and other oxidative changes. Some researchers have proposed the hydroxycinnamic acid to GSH ratio (HGR) as an indicator of oxidation susceptibility of must and could show that lower ratios yielded lighter musts.

In the actual scenario of climate change, optimization of water usage is becoming critical in sustainable viticulture. Most of the current approaches to assess grapevine water status and drive irrigation scheduling are either destructive, time and labour consuming and monitor a small, limited number of plants. This work presents a novel methodology using a contactless, miniaturized, low-cost NIR spectrometer to monitor the vineyard water status variability from a moving vehicle, to provide reliable information towards precision irrigation.

La délimitation de l’aire de production d’une appellation d’origine contrôlée française est une opération essentielle. Le décret-loi du 30 juillet 1935, qui a créé le système des appellations d’origine contrôlées

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).