Barbera d’Asti: the characterization of the vineyard sites

The use of pesticides for vine growing is responsible for generating an important volume of wastewater. In 2009, 13 processes were authorized for wastewater treatment but they are expensive and the toxicological impact of the secondary metabolites that are formed is not clearly established. Recently photodecomposition processes have been studied and proved an effectiveness to degrade pesticides and to modify their structures (Maheswari et al., 2010, Lassale et al., 2014). In this field, Pulsed Light (PL) seems to be an interesting and efficient process (Baranda et al., 2017). Therefore, the aim of this work was to investigate the PL technology as a new process for the degradation of pesticides.

Artificial intelligence (AI) for winegrowers refers to robotics, smart sensor technology, and machine learning applied to solve climate change problems. Our research group has developed novel technology based on AI in the vineyard to monitor vineyard growth using computer vision analysis (VitiCanopy App) and grape maturity based on berry cell death to predict flavor and aroma profiles of berries and final wines.

Context and purpose of the study. Climate change is affecting wine production and induces a large variability in wine composition between vintages.

Over the last decades, climate change and rising temperatures have impacted the wine industry. Wines from warm regions tend to have a higher pH and lower total acidity.

AIM: This study aimed to use simultaneous measurements of absorbance, transmittance, and fluorescence excitation-emission matrix (A-TEEM) combined with chemometrics as a rapid method to authenticate wines from three vintages within a single geographical indication (GI) according to their subregional variations