NIR based sensometric approach for consumer preference evaluation

Specific inactivated yeast derivatives (SYDS) are obtained from s. cerevisiae yeasts by various processes (thermal, mechanical, and enzymatic) and have diverse oenological applications to improve wine quality. However, different impacts on wine sensory and aromas were reported, depending on syds types and fractions, wine matrices, and experimental settings. Few works have examined the impact of SYDS on aromas considering also those on wine macromolecules influencing organoleptic properties.

Nitrogen is an important nutrient of yeast and its low content in grape must is a major cause for sluggish fermentations. To prevent problems during fermentation, a supplementation of the must with ammonium salts or more complex nitrogen mixtures is practiced in the cellar. However this correction seems to improve only partially the quality of wine [1]. In fact, yeast is using nitrogen in many of its metabolic pathways and depending of the sort of the nitrogen source (ammonium or amino acids) it produces different flavor active compounds. A limitation in amino acids can lead to a change in the metabolic pathways of yeast and consequently alter wine quality.

Today the knowledge in terms of molecular composition of the colloidal matrix is ​​not enough in order to control its stability, according to the number of winemaking and wine stabilization processes. The physico-chemical processes during the winemaking change the composition and quantity of wine macromolecules. The goal today is to determine which analytical techniques will allow to discriminate these winemaking processes in order to better understand their impact on colloidal matrix stability as well as which molecules are responsible for its instabilities. METHODS: Wines obtained after conventional winemaking were subjected to different fining and chemical stabilization treatments. Different methods were used to investigate the wine macromolecular composition and stability after chemical stabilization, including quantitative and qualitative analyzes of total soluble polysaccharides by extraction under acidified ethanol, and by size exclusion separation as well as qNMR metabolomics. RESULTS: Observation of a slight difference at the quantitative level using classical analysis between the winemaking processes was observed as well as a strong discrimination by qNMR metabolomics.

Aim: Downy mildew is a crucial disease in viticulture. In-field evaluation of downy mildew has been classically based on visual inspection of leaves and fruit. Nevertheless, non-invasive sensing technologies could be used for disease detection in grapevine. The aim of this study was to assess downy mildew severity in grapevine leaves using machine vision.

Landscapes such as its representation express values, beliefs and intentions of the individuals and the communities that produce them.