Study of the vine performance and the wine composition of Tannat on the terroir of Colonia del Sacramento – Uruguay

Context and purpose of the study ‐ An advancement of grapevine phenological development has been observed worldwide in the last two decades. In South Australia this phenomenon is even more accentuated since grapevine is often grown in a hot climate. The main consequences are earlier harvests at higher sugar levels which also result in more alcoholic wines. These are deemed undesirable for the Australian wine industry with consumer preferences shifting towards lower alcohol wines. Vineyard practices can be implemented to control and delay ripening. Amongst them, apical late leaf removal has been successfully applied in Europe to delay ripening by up to two weeks in Sangiovese, Aglianico and Riesling. In those studies, no negative effects were observed on grape colour, phenolics and on the carbohydrate storage capacity of the vines. To date, this technique has not been studied in Australia. In this study late leaf removal, apical to the bunch zone was applied to the variety Semillon for four seasons and compared to an untreated control.

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Pomace, stem, grapevine leaves, and vine shoots arise as so called winery by-products during the wine production process.

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).

Nitrogen fertilisation of grapevines is known to influence not only plant development and production yield, but also yeast assimilable nitrogen (YAN). This parameter is related to the growth of yeast