Use of mathematical modelling and multivariate statistical process control during alcoholic fermentation of red wine

Climate change is challenging viticulture worldwide compromising its sustainability due to warmer temperatures and the increased frequency of extreme events. Grafting Vitis vinifera L.

The research includes an analysis of the impact of weather conditions on phenological development of the vine and grape quality, through monitoring of four experimental cultivars (Chardonnay, Graševina, Merlot and Plavac mali) over two production years. In each experimental vineyard, which were evenly distributed throughout the regions of Slavonia and The Croatian Danube, Croatian Uplands,

Winemaking areas recognized as protected designations of origin (PDOs) shape important economic, environmental and cultural values that are tied to closely defined geographic locations. To preserve wine products and wine-growing practices adopted in different PDOs these areas are strictly regulated by legal specifications. However, quality viticulture is increasingly under pressure from climate change, which is altering the local conditions of many winegrowing areas. Therefore, maintaining traditional wine products will require the adoption of tailored adaptation strategies, including possible changes in the legal regulation of protected wines. To this end, it is necessary to have a comprehensive knowledge on PDOs including their extension, products and allowed practices. While there have been efforts to build databases that summarize the characteristics for individual wine PDO areas and to quantify the related effects of climate change, much information is still included only in the official documentation of the EU geographical indication register and has never been collected in a comprehensive manner. With this study we aim at filling this gap by building a spatial inventory of European wine PDOs that supports decision making in viticulture in the context of climate change. To map and characterize European wine PDOs, we analysed their legal documents and extracted relevant information useful for climate change adaptation. The output consists of a comprehensive geographical dataset that identifies the boundaries of all 1200 European wine PDOs at unprecedented spatial resolution and includes a set of legally binding regulations, such as authorized vine varieties, maximum yields and planting density. The inventory will allow researchers to analyse the impacts of climate change on European wine PDOs and support decision makers in developing tailored adaptation strategies. This includes, among others, the evaluation of new vineyard site selection, the expansion of cultivated varieties or the authorization of irrigation in vineyards.

Land use, plays a relevant role in the climatic system. It endows means for agriculture practices thus contributing to the food supply. Since climate and land are closely intertwined through multiple interface processes, climate change may lead to significant impacts in land use. In this study, 1-km observational gridded datasets are used to assess changes in the Köppen–Geiger and Worldwide Bioclimatic (WBCS)

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).