Exploring high throughput secondary trait phenomics to improve grapevine breeding

Grapevine (vitis spp.) Is one of the major and most economically important fruit crops worldwide. Unlike other cropping systems, viticulture has ancient historical connections with the development of human culture and with the socio-cultural background of grape-growing areas. The vitis genus is characterised by high levels of genetic diversity, as result of natural genetic mutations, which are common in grapevines and further assisted by ongoing vegetative propagation.

The wine industry worldwide faces more and more challenges due to climate change, such as increased dryness in some areas, water stress, sunburn and early harvesting during hot summer temperatures¹. One of the resulting problems for the wine quality might be a higher prevalence of the untypical aging off-flavor (ATA)². A substance, which Rapp and Versini made responsible for ATA, is the 2-aminoace-tophenone (2-AAP)³. 2-AAP in wine causes a naphthalene, wet towels, wet wool, acacia flower or just a soapy note⁴.

Aim: Downy mildew is a crucial disease in viticulture. In-field evaluation of downy mildew has been classically based on visual inspection of leaves and fruit. Nevertheless, non-invasive sensing technologies could be used for disease detection in grapevine. The aim of this study was to assess downy mildew severity in grapevine leaves using machine vision.

Some wine producers, in good years, can produce free-SO2 red wines and decide to add the minimum amount of sulphur dioxide only at bottling. To manage this addition

Aims: Shiraz is the most widely cultivated grape variety in Australia, and is grown under a range of viticultural and climatic conditions. Given its importance to the Australian wine sector, a number of studies have been conducted in recent years which involved a comprehensive assessment of grape composition, in order to objectively predict wine quality and style outcomes.