Caratterizzazione varietale della CV. Vranac del Montenegro: primi risultati

The combination of a non-parametric dissimilarity index with auger boring recordings was tested in a project of soil suitability evaluation for quality wine production in a 2000-ha hill slope portion of the “Colli Orientali del Friuli” AOC district (Italy).

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).

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.

An intelligent packaging might, among others, provide information and allow monitoring of the quality of the packed product or its surrounding environment. A recent project on micro-flow wine bottles closed with aluminium screw cap and tightness liner, highlighted the importance of monitoring the internal overpressure continuously, in real-time and at least for 72 hours, since the internal pressure on the tightness liner and the micro-flow are related. Real-time and continuous measurements are not the standard methods of measurement of the overpressure, yet. The most used equipment for the determination of the pressure in wine bottle is the aphrometer, a destructive device that supplies a single value of pressure.

AIM: The refractive index is a basic optical property of materials and a key tool for the determination of major components in musts, such as sugars