Cell wall remodeling mediated by specific PME genes plays a role in grapevine response to Botrytis cinerea

The main goal of the current study is the development of a cost-effective and easy-to-use method suitable for use in the laboratory of commercial wineries to analyze wine aroma. Additionally, this study attempted to establish a prediction model for wine quality gradings based on their aroma, which could reveal the important aroma compounds that correlate well with different grades of perceived quality METHODS: Parameters of the SHS−GC−IMS instrument were first optimized to acquire the most desirable chromatographic resolution and signal intensities. Method stability was then exhibited by repeatability and reproducibility. Subsequently, compound identification was conducted. After method development, a total of 143 end-ferment wine samples of three different quality gradings from vintage 2020 were analyzed with the SHS−GC−IMS instrument. Six machine learning methods were employed to process the results and construct a quality prediction model. Techniques that aim to explain the model to extract useful insights were also applied.

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.

The most recent methodological developments in soil survey and land evaluation, that can be taken as reference in the viticultural field, go over usage of the GIS and database. These informatic tools, which begin to be widely utilised, consent to realise evaluations at different geographic scale and with different data quality and quantity in entrance.

In the course of the present work, which is the first part of a study on the “characterization of Barbera dell’Oltrepo Pavese D.O.C.” 30 wines Barbera from 1993 vintage have been compared only regarding their sensory characteristics. An unstructured scale card, composed by 15 descriptors have been used.

From a fertility standpoint, the vine has to extract from the soil mineral substances necessary for its existence. However, the amount of certain available nutrients does not always correspond to a proportional increase in quality.