Grape pomace, an active ingredient at the intestinal level: Updated evidence

In the context of climate change with increasing evaporative demand, understanding the water use behavior of different grapevine cultivars is of critical importance. Carbon isotope discrimination (δ13C) measurements in wine provide a precise and integrated assessment of the water status of the vines during the sugar accumulation period in grape berries. When collected over multiple vintages on different cultivars, δ13C measurements can also provide insights into the effects of genotype on water use efficiency.

Plant roots fulfil important functions as they are responsible for the acquisition of water and nutrients, for anchorage and stability, for interaction with symbionts and, in some cases, for the storage of carbohydrates. These functions are associated with the Root System Architecture (RSA, i.e. the form and the spatial arrangement of the roots in the soil). The RSA results from several biological processes (elongation, ramification, mortality…) genetically determined but with high structural plasticity.

Since the mid-1980s, several surveys have been carried out in La Rioja to search for populations of the sylvestris grapevine subspecies (Vitis vinifera L. subsp. sylvestris Gmelin). The banks of the Ebro River and its tributaries (Alhama, Cidacos, Leza, Iregua, Najerilla, Oja and Tirón rivers), as well as the surrounding vegetation of their valleys have been covered. So far, all the populations found are alluvial, forming part of the riparian vegetation of the Najerilla (the first reported population in La Rioja [1]), Iregua, and the vicinity of Oja valleys.

The interest in sustainable and ecologic agricultural practices in grapevine has grown significantly in recent years in the context of ecological transition. Organic mulches are treatments that support the circular economy and positively affect the soil and the plant. They are an alternative to herbicides and other conventional practices since they may influence soil moisture, erosion, structure and weed control. However, their effects on the soil and must microbiota remain unknown.

The main objective of the work was to develop a simple, robust and selective analytical tool that allows predicting the authenticity of Tempranillo wines from DOCa Rioja. The techniques of voltammetry and absorbance-transmission and fluorescence excitation emission matrix (A-TEEM) spectroscopy have been applied in combination with machine learning (ML) algorithms to classify red wines from DOCa Rioja according to region (Alavesa, Alta or Oriental) and category (young, crianza or reserva).