Implementation of hyperspectral image analysis for evaluating table grape quality on bunch and berry level

In recent decades, the scarcity of water resources in agriculture in certain areas has been aggravated by climate change, which has caused an increase in temperatures, changes in rainfall patterns, as well as an increase in the frequency of extreme phenomena such as droughts and heat waves. Although the vine is considered a drought-tolerant specie, it has to satisfy important water requirements to complete its cycle, which coincides with the hottest and driest months. Achieving sustainable viticulture in this scenario requires high levels of efficiency in the use of water, a scarce resource whose use is expected to be severely restricted in the near future. In this regard, the use of drought-tolerant varieties that are able to maintain grape yield and quality could be an effective strategy to face this change. During three consecutive seasons (2018-2020) the behavior in rainfed regime of 13 traditional red grapevine varieties of the Spain central region was studied. These varieties were cultivated in a collection at Centro de Investigación de la Vid y el Vino de Castilla-La Mancha (IVICAM-IRIAF) located in Tomelloso (Castilla-La Mancha, Spain). Yield components (yield, mean bunch and berry weight, pruning weight), physicochemical parameters of the musts (brix degree, total acidity, pH) and some physiological parameters related with water stress during ripening period (δ13C, δ18O) were analysed. The application of different statistical techniques to the results showed the existence of significant differences between varieties in their response to stressful conditions. A few varieties highlighted for their high ability to adapt to drought, being able to maintain high yields due to their efficiency in the use of water. In addition, it was possible quantify to what extent climate can be a determinant in the δ18O of musts under severe water stress conditions.

Major and trace elements are essential for the development of grapes used for the wine. They are primarily originating from the soil. Some elements are also seldomly added during the wine making process. Therefore, the largest spectrum of major, trace and ultra-trace elements in the final wine product is a good signature of its geographical origin. In the frame of the European tracewindu, we have developed a very original multi-isotopic dilution method using triple quadrupole icp/ms.

The color is the first attribute perceived by consumers and a major factor determining the quality of red wines. This depends mainly on the content of grape anthocyanins and their extraction into the juice/wine during winemaking. Furthermore, these compounds can undergo reactions that influence the chemical and sensory characteristics of the wine. Monomeric forms are prone to oxidation and adsorption on solid parts.

Grape volatile compounds are mainly responsible for wine aroma, so it is important to know the va-rietal aromatic composition throughout ripening process. Currently, there are no tools that allow mea-suring the aromatic composition of grapes, in intact berries and periodically, throughout ripening, in the vineyard or in the winery. For this reason, this work evaluated the use of near infrared spectroscopy (NIR) to estimate the aromatic composition and total soluble solids (TSS) of Tempranillo Blanco berries during ripening. For this purpose, NIR spectra (1100-2100 nm) were acquired from 240 samples of in-tact berries, collected at different dates, from veraison to overripening.

Promoting sustainable agricultural practices is one of the challenges of the last decades. Organic and biodynamic viticulture can be an alternative to intensive viticulture, furthermore contributing to reduction of impact on environment and human health and guaranteeing soil preservation and quality products1. The aim of this experimentation was to evaluate the medium and long-term effects of different agronomic practices in viticulture on nutrient availability and heavy metal accumulation in soil.