Model-assisted analysis of the root traits underlying RSA genotypic diversity in Vitis: a promising approach for rootstock selection?

Grape quality potential for wine production is strongly influenced by environmental parameters and agronomic factors. Several studies underline the rootstock effect on scions vegetative growth and berry composition [1] with an impact on wine quality. Rootstocks are promising agronomic tools for climate change adaptation and in most grape-growing regions the potential diversity of rootstocks is not fully used and only a few genotypes are planted. Moreover, little is known about the effect of rootstock genetic variability on the aromatic composition in wines.

The vineyard has experienced a general increase in yields mainly due to the elevated use of technology which caused a quality loss of grapes in more than one case. A large percentage of the Spanish vineyard is covered by a Denomination of Origin which limits the productive level of the vineyards as one of its regulations. The maximum production limit is a variable characteristic of each vineyard and is not usually regulated by agronomic criteria, and this explains the fact that each vineyard can reach high quality with a totally different yield from that set by the Denomination of Origin.

Performing accurate vineyard yield estimation is of upmost importance as it provides important benefits to the whole vine and wine industry. Recently, image-analysis approaches have been explored to address this issue however this approach has as main challenge the bunch occlusion, mostly by vegetation but also by neighboring bunches. The present work aims at assessing the magnitude of bunch occlusion by neighboring bunches and to evaluate its dependency on a selection of vegetative and reproductive vine parameters assessed at fruiting zone. Forty vine segments (1 m) of two vineyard plots of the white cultivars ‘Alvarinho’ and ‘Arinto’ were assessed for vegetative and reproductive features at fruiting zone and imaged with a 2D camera.

The barrel-making process is widely recognized as a crucial practice that affects the composition of barrel-aged wine. After the drying process, the staves are considered ready for barrel assembly, which includes the processes of bending and toasting the barrel structure. Toasting is considered one of the most critical stages in determining the physical and chemical composition of the staves, which can influence the chemical and sensory composition of the wine aged in barrels made from them [1].

The application of remote and proximal sensing is a fast and efficient method to monitor grapevine vegetative and physiological parameters and is considered valuable to derive information on associated yield and quality traits in the vineyard. Further details can be obtained by the application of molecular analysis at the gene expression level aiming at elucidating how pathways controlling the formation of different grape quality traits are influenced by spatial variability. This work aims at evaluating intra-vineyard variability in grape composition at harvest and at comparing this with remotely sensed canopy vegetation data and molecular-based approaches.