Influence of organic plant treatment on the terroir of microorganisms

Global warming is one of the biggest environmental, social, and economic threats. In the Douro Valley, change to the climate are expected in the coming years, namely an increase in average temperature and a decrease in annual precipitation. Since vine cultivation is extremely vulnerable and influenced by the climate, these changes are likely to have negative effects on the production and quality of wine.
Adaptation is a major challenge facing the viticulture sector where the choice of plant material plays an important role, particularly the rootstock as it is a driver for adaptation with a wide range of effects, the most important being phylloxera, nematode and salt, tolerance to drought and a complex set of interactions in the grafted plant.
In an experimental vineyard, established in the Douro Region in 1997, with four randomized blocs, with five varieties, Touriga Nacional, Tinta Barroca, Touriga Franca and Tinta Roriz, grafted in four rootstocks, Rupestris du Lot, R110, 196-17C, R99 and 1103P, data was collected consecutively over 20 years (2001-2020). Phenological observations were made two to three times a week, following established criteria, to determine the average dates of budbreak, flowering and veraison. During maturation, weekly berry samples were taken to study the dynamics of sugar accumulation, amongst other parameters. Climate data was collected from a weather station located near the vineyard parcel, with data classified through several climatic indices.
The results achieved show a very low coefficient of variations in the average date of the phenophases and an important contribution from the rootstock in the dynamic of the phenology, allowing a delay in the cycle of up to10-12 days for the different combinations. The Principal Component Analysis performed, evaluating trends in the physical-chemical parameters, highlighted the effect of the climate and rootstock on fruit quality by grape varieties.

La prise en compte des paysages viticoles dans le développement durable ou l’aménagement du territoire est un thème non négligeable pour la valorisation de la filière viti-vinicole à l’échelle d’une exploitation ou d’une A.O.C.

Remote sensing technology captures spectral data beyond the visible range, making it useful for monitoring plant stress. Vis-NIR (Visible-Near Infrared) spectroscopy (400-1000 nm) is commonly used to indirectly assess plant status during drought. One example is the widespread use of normalized difference vegetation index (NDVI) that is strongly linked to green biomass. However, a knowledge gap exists regarding the applicability of this method to all the drought conditions and if it is a direct correlation to the water status of the plant.

Le marché international du vin est désormais tourné vers la qualité et les vignobles de vin de masse se transforment pour construire la qualité et la réputation de leurs produits. Cette construction s’appuie notamment sur la valorisation de ressources territoriales de nature physique (terroir, pacage, écosystème) et humaine (savoir-faire, culture, patrimoine…). Les « Routes des Vins » sont des exemples concrets de ces processus de «territorialisation», combinant ces ressources territoriales pour communiquer sur l’ancrage géographique et la spécificité des vins. Les «Routes des Vins» émergentes, observées dans les régions vitivinicoles en transition vers la qualité, en Languedoc Roussillon, à Mendoza (Argentine) et au Western Cape (Afrique du Sud), participent souvent à la valorisation des terroirs, en organisant un itinéraire sur le territoire associé, en faisant découvrir les vins «de qualité», les paysages, les pratiques et le savoir-faire associés à leur élaboration.

It is often said that wine is a complex matrix and the chemical analysis of wine with the thousands of compounds detected and often measured is proof. New technologies can assist not only in separating and identifying wine compounds, but also in providing information about the sample as a whole. Information-rich techniques can offer a fingerprint of a sample (untargeted analysis), a comprehensive view of its chemical composition. Applying statistical analysis directly to the raw data can significantly reduce the number of compounds to be identified to the ones relevant to a particular scientific question. More data can equal more information, but also more noise for the subsequent statistical handling.