applicazione dei metodi isotopici e dell’analisi sensoriale negli studi sull’origine dei vini

Aim: Regional characters relating to Shiraz in Australia are not well documented. This study aimed to characterize the sensory, chemical and climate profiles of wines from various Australian Shiraz producing regions. 

Agroscope is investigating the impact of yield on nitrogen (N) partitioning in grapevine and on must composition. The mechanism of N assimilation

The wine industry, a key sector for the European Union’s economy, exhibits significant energy consumption, amounting to approximately 1,750 million kWh annually within this geographic context, with major contributions from Italy, France, Spain, and Portugal (Fuentes Pila et al., 2015).

Aims: This study aims to: (1) characterize the agroclimatic conditions of the Portuguese Denominations of Origin, using a compound index that combines thermal and soil water balance conditions and a high-resolution climatic dataset (~1 km spatial resolution); (2) categorize the main grapevine varieties as a function of this compound index.

Barolo DOCG is an economically important wine producing region in Northwest Italy. It is a small region of approximately 70 km2 gross area. The topography is very complex with steep sloped hills ranging in elevation from below 200 m to 550 m. Barolo DOCG wine is made exclusively from the Nebbiolo grape. Bioclimatic indexes are often used in viticulture to gain a better understanding of broader climate trends which can be compared temporally and geographically. These indexes are also used for identifying potential phenological timing, growing region suitability, and potential risks associated with expected climatic changes. Understanding how topography influences bioclimatic indexes can help with understanding of mesoscale climate behaviour leading to improved decision making and risk management strategies. The average monthly maximum and minimum temperatures, the Cool Night Index, the Huglin Index, and the monthly diurnal range (from July to October) were calculated using data from 45 weather stations within a 40 km radius of the Barolo DOCG growing area between the years 1996 and 2019. Linear and multiple regression models were developed using independent variables (elevation, aspect, slope) extracted from a digital elevation model to identify significant relationships. Bioclimatic indexes were then kriged with external drift using independent variables that showed significant relationships with the bioclimatic index using a 100 m resolution grid. The maximum monthly temperatures and the Huglin Index showed consistent significant negative relationships with elevation in all years. The minimum monthly temperatures showed no relationship with elevation but in some months a small but significant relationship was observed with aspect. Due to the lack of a relationship between minimum monthly temperatures and elevation compared to the significant relationship between maximum monthly temperatures and elevation, monthly diurnal range had a negative relationship with elevation.