Impact of glutathione-rich inactivated yeast on wine chemical diversity

There is increasing scientific consensus that climate changeis the underlying cause of the prolonged dry and hot conditions that have increased the risk of extreme fire weather in many countries around the world. In December 2019, a bushfire event occurred in the Adelaide Hills, South Australia where 25,000 hectares were burnt and in vineyards and surrounding areas various degrees of scorching and infrastructure damage occurred. The ability to coordinate and plan recovery after a fire event relies on robust and timely data. The current practice for measuring the scale and distribution of fire damage is to walk or drive the vineyard and score individual vines based on visual observation. The process is time consuming, subjective, or semi-quantitative at best. After the December 2019 fires, it took many months to access properties and estimate the area of vineyard damaged. This study compares the rapid assessment and mapping of fire damage using high-resolution satellite imagery with more traditional ground based measures. Satellite imagery tracking vineyard recovery in the season following the bushfire is being correlated to field assessments of vineyard productivity such as canopy health and development, fertility and carbohydrate storage. Canopy health in the seasons following the fires correlated to the severity of the initial fire damage. Severely damaged vines had reduced canopy growth, were infertile or had very low fertility as well as lower carbohydrate levels in buds and canes during dormancy, which reduced productivity in the seasons following the bushfire event. In contrast, vines that received minor damage were able to recover within 1-2 years. Tools that rapidly and affordably capture the extent and severity of damage over large vineyard area will allow producers, government and industry bodies to manage decisions in relation to fire recovery planning, coordination and delivery, improving the efficiency and effectiveness of their response.

It is fundamental for wineries to know the potential yield of their vineyards as soon as possible for future planning of winery logistics. As such, non-invasive image-based methods are being investigated for early yield prediction. Many of these techniques have limitations that make it difficult to implement for practical use commercially. The aim of this study was to assess whether yield can be estimated using images taken in-field with a smartphone at different phenological stages. The accuracy of the method for predicting bunch weight at different phenological stages was assessed for seven different varieties.

To characterize a wine, the most frequently used criteria describe its color, its origin, the grape varieties from which they come, or even for white wines its residual sugar content (dry, semi-dry, sweet). In france, the system of appellations of origin set up in 1919 was initially based solely on the notoriety and origin of the wines. But given the unfavorable consequences that this lack of details generated, the public authorities quickly integrated in 1927 into the “capus” law criteria for access to designations of origin, relating to the specific characteristics of the soils of the vineyards and the grape varieties used, in particular exclusion of interspecific hybrid varieties. In 1935 the creation of the aoc system confirmed the interest in precisely defining all the production conditions that must be implemented to be able to claim the benefit of an aoc, and grape varieties were an essential condition for acquisition.

A white wine model solution (12% v/v ethanol, 4 g/L tartaric acid, pH 3.2) was used to assess wine colloidal instability as well as the influence of several wine components on bentonite performance in protein removal.

One of the main effects of global warming is an increase in the sugar concentration of grapes at harvest time, resulting in wines with a high alcohol content and an unbalanced structure. The fruit to leaf ratio is a key factor in determining the final sugar concentration, and training systems and management techniques can help to control this parameter.