Neural networks and ft-ir spectroscopy for the discrimination of single varietal and blended wines. A preliminary study.

Context and purpose. Viticulture has exerted a profound influence on the landscape and biodiversity of numerous countries for centuries.

Dealcoholization of wine has gained increasing attention as consumer preferences shift toward lower-alcohol or
alcohol-free beverages. This process meets key demands, including health-conscious lifestyles, regulatory
compliance, and the expanding non-alcoholic market [1-3].

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.

Proteic haze is a problem which may occur in all fruit-based beverages and fermented juices (beer, cider, wine). When it occurs, the economic loss is important.

Grapevine (Vitis Vinifera L.), one of the most important cultivated fruit crops, is facing significant challenges due to climate change. Specifically, increasing temperatures negatively impact the physiological traits and disrupt plant phenology. Additionally, increased virulence in pathogen attacks and pests leads to significant yield loss, requiring widespread application of plant protection products. Traditional agronomic practices offer only partial mitigation, requiring the development of precise and effective intervention strategies. The economic worth of viticulture has prompted continuous efforts in grapevine genetic improvement programs, traditionally involving conventional breeding and clonal selection that, however, are complex and time-consuming approaches.