Leaf removal to regulate fruit ripening in Cabernet-Sauvignon

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.

Vine downy mildew is one of the most frequent diseases in intensive vineyards. Bordeaux mixture (B.m.), in order to control the disease has been applied onto vineyards since the end of the 19th century. The intensive use of Cu-fungicides could influence the physiology of grapevine. It is also possible that high amounts of foliar Cu sprays trigger stress responses in vine leaves.

In vineyards, management and the surrounding landscape can have different effects on spiders. In temperate regions management (organic vs. conventional) may have less strong effects than for other crops.

The projected rise in mean air temperatures together with the frequency, intensity, and length of heat waves in many wine-growing regions worldwide will deeply impact grape berry development and quality. Several studies have been conducted and a large set of molecular data was produced to better understand the impact of high temperatures on grape berry development and metabolism[1]. According to these data, it is highly likely that the metabolomic dynamics could be strongly modulated by heat stress (HS).

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.