Colour assessment of port wines using colorimetric and spectrophotometric methods

Green cover in vine rows provides many ecological services, but can also negatively impact the crop, depending on the weed species. The composition of a vineyard weed community is influenced by many parameters. Ensuring an evolution of the vine row flora into a desired direction is therefore very complex. A key step towards this goal is to know which factors influence the establishment of the weed community and which types of communities are best suited for vineyards. In this study, we analysed the weed communities of several vineyards in the Lake Geneva region (379 botanical surveys on 117 plots), with the aim to highlight the links between soil management practices (chemical and mechanical weeding, mowing, mulching roll) and phytosociological profiles, biodiversity and selected functional traits (growth forms, life strategies, root depth). T

2,5-Dimethyl-4-hydroxy-3(2H)-furanone (furaneol) is an important aroma compound in fruits, such as pineapple and strawberry, and is reported to contribute to the strawberry-like note in some wines. Several grapevine species are used in winemaking, and furaneol is one of the characteristic aroma compounds in wines made from American grape (Vitis labrusca) and its hybrid grape, similar to methyl anthranilate. Muscat Bailey A is a hybrid grape variety [V. labrusca (Bailey) x V. vinifera (Muscat Hamburg)], and its wine is one of the most popular in Japan. The inclusion of Muscat Bailey A in the ‘International List of Vine and Varieties and their Synonyms’ managed by the ‘International Organisation of Vine and Wine (OIV)’ in 2013 has further fueled its popularity among winemakers and researchers worldwide.

“The Human being has an excellent ability to detect and discriminate odors but typically has great difficulty in identifying specific odorants”(1). Furthermore, “from a cognitive point of view the mechanism used to judge wines is closer to pattern recognition than descriptive analysis.” Therefore, when one wants to reveal the volatile “wine-like feature” pattern recognition techniques are required. Sensomics is one of the most recent “omics”, i.e. a holistic perspective of a complex system, which deals with the description of substances originated from microorganism metabolism that are “active” to human senses (2). Depicting the relevant volatile fraction in wines has been an ongoing task in recent decades to which several research groups have allocated important resources. The most common strategy has been the “target approach” in order to identify the “key odorants” for a given wine varietal.

Wine is a widely consumed alcoholic beverage with a high commercial value. More specifically, the worldwide consumption of rosé wine has increased by 20% since 2002[1]. But because of its high commercial value, it can become a subject of fraud, and authenticity control is necessarily required. More than one hundred polyphenols have been recently quantified in various rosé wines [2]. They are key components defining color, taste and quality of wines. Their amount and composition depend on many different factors such as grape variety, winemaking and age of the wine. In this study, the influence of geographic origin of some rosé French wines was investigated. An original and very fast UPLC-QTOF-MS method was developed and used to predict the geographic origin authenticity of rosé wines.

Inactive dry yeast treatments in the vineyard are a tool used with the aim to improve the concentration and quality of secondary metabolites in grapes, leading to a better differentiation of the wines made from grapes differently treated. In this work, a foliar spraying treatment with yeast derivatives specifically designed to be used with the patent pending application technology of Lallemand Inc. Canada (LalVigne® Mature, Lallemand Inc., Montreal, Canada) was tested on Vitis vinifera L. cv. Barbera and Nebbiolo black winegrapes. The aim was to evaluate the effect of this treatment on the phenolic compounds accumulation, the skin physical-mechanical properties and the related phenolic extractability. Prior to analysis, the berries were sorted by flotation in order to evaluate their distribution by density class, and to determine the skin texture parameters of berries with different sugar contents, thus understanding also the ripening effect.