Genome wide association mapping of phenology related traits in Vitis vinifera L

Rio grande do sul is the main grape producing state in Brazil, with the largest wine-growing area, responsible by 90% of the national production of wines and grape juices. Serra Gaúcha is the main vitivinicultural region, where around 15% of the area is destined to produce wines from vitis vinifera L. grapes. This region presents high rainfall during the grape maturation cycle, a factor that leads to great risk of attacks by fungal pathogens. the use of resistant varieties can reduce the cost and quantity of spraying, improving wine quality, focusing on a sustainable vitiviniculture.

The use of new technologies such as microwaves (MW) arose in recent years as an efficient alternative to reduce the use of sulfur dioxide (SO2) and as a method for improving wines in terms of color and aroma [1, 2]. MW (non-ionizing electromagnetic waves with frequencies between 300 MHz and 300 GHz) have been widely applied in the food industry in order to reduce processing time and favor food preservation.

Volatile organic compounds (VOCs) are emitted by nearly all plant organs of the plants, including leaves. They play a key role in the communication with other organisms, therefore they are involved in plant defence against phytopathogens. In this study VOCs from grapevine leaves of two varieties of Vitis vinifera infected by Erysiphe necator were analysed. The varieties were selected based on their susceptibility to pathogen, Kishmish Vatkana has the Ren1 resistance gene and Zamarrica showed high susceptibility in previous trials.

Aim: Early leaf removal, generally applied before flowering, is mostly conceived as a technique to control grape yield and improve the health of grapes and focused on the final objective of increasing wine quality.

The components and methodology for characterization of the terroir have been described by Gómez-Miguel & Sotés (1993-2014, 2003) and Gómez-Miguel (2011) taking into account the full range of environmental factors (i.e: climate, lithology, vegetation, topography, soils, altitude, etc.), landscape variables (derived from photo-interpretation and a digital elevation model), and specific variables to the country’s viticulture (i.e: size and distribution of the vineyards, varieties, phenology, productivity, quality, designation regulations, etc.).