La hiérarchisation des Coteaux du Languedoc: une application concrète du zonage vitivinicole

Following the idea of « Grande Filiera » (GF) (Great chain), of « Grande Zonazione » (GZ) (Great Zonation), of “interpretation, estimation and valorisation of vineyards and wines landscape, of “qualities”(we have classified more than ninety), of quality economy.

Tempranillo Tinto (TT) is the third-most planted red wine variety in the world, and it is mostly grown in the Iberian Peninsula. Spontaneous somatic variation appearing during vegetative propagation can be exploited to improve elite varieties as Tempranillo Tinto, including the selection of new phenotypes enhancing berry quality. We described previously that a somatic variant of TT with darker fruit color, the clone VN21, exhibits increased extractability of polyphenols during the winemaking process. To unravel the molecular mechanism underlying this phenomenon, we performed whole-genome resequencing to compare VN21 to other TT clones, revealing a 10 Mb deletion in chromosome 11 that likely affected only the L1 meristem cell layer of VN21 and tissues derived from it, such as external cell layers of berry skin.

Grapevine rootstocks have traditionally been chosen in order to manage scion vigour, soil pests and soil conditions. Riparia Gloire de Montpellier (RGM) has been in use since the turn of the 19th century, over 100 years and still a remarkably stable source of phylloxera (Daktulosphaeria vitifoliae Fitch) resistance. The original source material was probably collected near the Missouri/Mississippi river confluence, a mid-continental but more southerly location in the United States. It has been hypothesized that more northerly selections of V. riparia Michx might improve both fall acclimation rate and depth of the scion, thus mitigating late fall frost and midwinter freeze damage.

The SUSTAIN project aims at assessing the soil organic carbon (SOC) stock and vulnerability in vineyard in a climate change scenario.

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.