High-resolution aerial thermography for water stress estimation in grapevines

Aim: The aim of this work is educating people about soil variability and terroir. Soil monoliths are used to educate the wine industry about how to describe a soil profile, interpret the soil formation processes operating in a particular soil profile and consequently the impact of soil properties on vine growth, fruit quality and wine production. Soil monoliths are a permanent artistic tool for educating, research and management of soil variability.  

l lavoro presenta l’evoluzione dei contenuti di arsenico nelle uve durante lo sviluppo e la maturazione, e la sua distribuzione nell’acino; verifica inoltre la relazione tra i contenuti di As nelle uve

In vineyard management, the block is considered today as the technical work unit. However, considerable variability can exist inside a block with regard to physiological parameters, such as vigour, particularly because of soil heterogeneity. To represent this variability spatially, many measurements have to be taken, which is costly in both time and money. High resolution remote sensing appears to be an efficient tool for mapping intra-block heterogeneity.

The agri-food industry is constantly searching for ingredients of high functional value, healthy and of natural origin. One species of particular interest is Vitis vinifera, due to its recognized antioxidant potential. Among the grape varieties, one group possesses these antioxidant compounds not only in the skin, but also in its pulp: Teinturier. The red grape has traditionally been used for color correction purposes in winemaking, however, its high antioxidant content transforms it into a raw material of high potential for new formulations of ingredients and foods for the health and wellness market.

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. The accuracy of the method for predicting bunch weight at different phenological stages was assessed for seven different varieties.