Limiting magnesium availability: a novel approach to managing brettanomyces spoilage in winemaking

Ultraviolet radiation (UVR) is a minor part of the solar spectrum, but it represents an important ecological factor that influences many biological processes related to plant growth and development. In recent years, the application of UVR in agriculture and food production is emerging as a clean and environmentally friendly technology.
In grapevine, many studies have been conducted on the effects of ambient levels of UVR, but there are few considering the effects of UV-B application on grape phenolic composition under commercial growing or postharvest conditions.

The vinification by Carbonic maceration (CM) involves the process whereby the whole bunches are subjected to anaerobic conditions during several days. In this anaerobic condition, the grape endogenous enzymes begin an intracellular fermentation. This situation favors that whole grapes split open and release their juice into the tank, increasing the liquid phase that is fermented by yeasts [1]. Then, two types of wines are obtained; one from the free-run liquid in the tank (FCM) and other from the liquid after pressing the whole grape bunches (PCM). PCM wines are recognized as high quality young wines because their fruity and floral aromas[2] that although they are very intense at the end of the winemaking they gradually disappear during conservation.

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.

Wine perception is a multisensory experience that makes use of the sight, smell, and taste senses. When wine is sensorially assessed, the stimulus received generates multiple signals that tasters convert into organoleptic descriptors. Colour is commonly the first attribute evaluated during wine tasting. Moreover, the colour properties provide the taster with a priori information of the wine’s aroma. This preconceived perception is later confirmed or denied during the aroma evaluation.

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).