Oenococcus oeni clonal diversity in the carbonic maceration winemaking

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).

The market trend heads to food products with less chemical inputs, including in oenology. During the winemaking process, sulfites are commonly use to avoid microbiological contamination and stabilization of the wine thanks to its antimicrobial and antioxidant activities. Nevertheless, this use is not without consequences on human health and environment, leading for example to allergic reaction and pollution. A biological alternative to these sulfites has emerges: the bioprotection.

The presence of acetic acid bacteria in wine can lead to the appearance of acetic acid at concentrations above the perception threshold, causing the wine rejection by the consumer. During the winemaking process, avoiding the presence of acetic acid bacteria is very difficult, as there is always a residual population accompanying the wine[1], and the problem arises with the significant development of these microorganisms that metabolizes large amounts of acetic acid.
The concern of wineries to control the presence of acetic acid bacteria in wines during their conservation is due to the absence of simple and effective analyses that allow the detection of these microorganisms in the initial stages.

Implementing alternative grapevine systems that incorporate sustainable strategies and innovative farming practices is essential. However, we lack tools for measuring the impact of these new practices on the overall sustainability of vineyards. DEXi PM Vigne (Gary et al., 2015) is a tool developed for ex ante assessment of the sustainability of grapevine cropping systems, from the plot to the farm scale. In the present study, we focused on implementing new strategies of integrated crop protection management with limited pesticide use in vineyards.

Performing accurate vineyard yield estimation is of upmost importance as it provides important benefits to the whole vine and wine industry. Recently, image-analysis approaches have been explored to address this issue however this approach has as main challenge the bunch occlusion, mostly by vegetation but also by neighboring bunches. The present work aims at assessing the magnitude of bunch occlusion by neighboring bunches and to evaluate its dependency on a selection of vegetative and reproductive vine parameters assessed at fruiting zone. Forty vine segments (1 m) of two vineyard plots of the white cultivars ‘Alvarinho’ and ‘Arinto’ were assessed for vegetative and reproductive features at fruiting zone and imaged with a 2D camera.