Rootstock-scion contributions to seasonal water and light use diversity under field conditions

Actually, many countries around the world are studying different strategies for adapting winegrowing regions to climate changes, focusing on a sustainable viticulture.

It is fundamental for wineries to know the potential yield of their vineyards as soon as possible for future planning of winery logistics. As such, non-invasive image-based methods are being investigated for early yield prediction. Many of these techniques have limitations that make it difficult to implement for practical use commercially. The aim of this study was to assess whether yield can be estimated using images taken in-field with a smartphone at different phenological stages.

This paper presents is the create, the study and amplographic
description the new white Greek table variety grapes “Aztec”, created in 2013 by breeder P. Zamanidis at
the Athens vineyard of the Institute of Olive, Subtropical Plants and Vine.

Xylotrechus arvicola (Coleoptera: Cerambycidae) is a pest in vineyards (Vitis vinifera) in the main Spain wine-producing regions with Protected Denomination of Origin (PDO). The action of the larvae, associated to the spreading of wood fungi, causes damage especially in important varieties of V. vinifera. X. arvicola females lay eggs concentrated in cracks or under the rhytidome in the wood vines, which allows the emerging larvae to get into the wood and make galleries inside the plant being then necessary to prune intensively or to pull up the bored plants (1). The objective of the study was to evaluate captures of X. arvicola insects in five varieties of V. vinifera in PDO León.

The application of sensors in viticulture is a fast and efficient method to monitor grapevine vegetative, yield and quality parameters and determine their spatial intra-vineyard variability. Molecular analysis at the gene expression level can further contribute to the understanding of the observed variability by elucidating how pathways responsible for different grape quality traits behave in zones diverging for one or the other parameter. The intra-vineyard variability of a Cabernet Sauvignon vineyard was evaluated by a standard Normalized Difference Vegetation Index (NDVI) mapping approach, employing UAV platform, accompanied by detailed ground-truthing (e.g. vegetative, yield, and berry ripening compositional parameters) that was applied in 14 spots in the vineyard. Berries from different spots were additionally investigated by microarray gene expression analysis, performed at five time points from fruit set to full ripening.