A sensometabolomic approach to understand wine mouthfeel percepts

Grapevine (Vitis vinifera L.) exhibits a high level of genetic and phenotypic diversity among the approximately 6000 cultivars recorded. This perennial crop is highly vulnerable to numerous fungal diseases, including esca, which is a complex vascular pathology that poses a significant threat to the wine sector, as there is currently no cost-efficient curative method[1]. In this context, an effective approach to mitigate the impact of such diseases is by leveraging the crop’s genetic diversity. Indeed, susceptibility to esca disease appears to vary between cultivars, under artificial or natural infection. However, the mechanisms and varietal characteristics underlying cultivar susceptibility to esca are still unknown.

Croatian viticulture is mainly based on native grapevine varieties susceptible to various diseases and pests, which leads to unsustainable use of large amounts of pesticides. The sustainable development of viticulture in the future will only be possible by increasing the resistance of the grapevine through the development of new resistant varieties. Breeding programs have been launched in the leading wine-growing countries to develop resistant varieties possessing high-quality levels. Native cultivars from Croatia are not included in the breeding programs of other countries.

The use of grapevine genetic diversity is a way to mitigate the negative impacts of climate change on viticulture systems. Leaf epidermal flavonoids (including flavonols and anthocyanins) are involved in plant defense mechanisms against environmental stresses, like high temperatures or excessive solar radiation [1,2]. Among other factors, they modulate light absorption, which reduces photoinhibition processes in photosynthetic tissues [1]. Therefore, the identification of grapevine cultivars with an increased content on leaf epidermal flavonoids arises as a potential avenue to improve grapevine tolerance to some detrimental environmental stresses.

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).

Trichoderma is one of the most widely used fungal biocontrol agents on vineyards due to its multiple benefits on this crop, such as its fungicidal and growth promoting capacity. In this work, we have analyzed the effect on the concentration of nutrients in grapevine leaves and on the quality of the grape must after spraying an autochthonous strain of Trichoderma harzianum and one of the main secondary metabolites produced by this genus, 6-pentyl-α-pyrone (6PP).