Climate, grapes, and wine: structure and suitability in a variable and changing climate

The past three decades of terrestrial remote sensing research have delivered unprecedented insights into our fundamental ability to detect, quantify, and differentiate plant disease (Gold 2021). However, much of our fundamental knowledge in this domain has come from studies in non-agricultural systems and until recently, most agricultural studies, when extant, have focused on tree crops where canopy closure and large plot and plant size facilitate stress detection at low spatial resolution. Recent engineering innovations and advancements in constellation architecture design have refined the accuracy and scalability of airborne and spaceborne sensing platforms, enabling us to monitor diverse specialty crops, including grapevine, planted in smaller, spatially varied fields.

A partir des recherches conduites sur la caractérisation des terroirs viticoles par des chercheurs de l’Unité de Recherches Vigne et Vin (1, 2, 3, 4, 5) du Centre INRA d’Angers, Terre des Sciences, le Centre de Culture Scientifique et Technique d’Angers (CCSTA) a mis au point un parcours de découverte d’une journée dans le vignoble angevin avec une approche pluridisciplinaire.

A large population of vines of the Mandón minority red variety (synonymous with Garró) has been located in old vineyards of the D.O. Arribes (Zamora and Salamanca) to conserve and recover this minority variety. The wines made with this variety are characterized by their good structure and color, interesting harmony, an excellently low pH, with high acidity, as well as complex aromas of blue fruits and a marked and expressive minerality.

Vineyard floors in warm, dry landscapes including those in South Australia, have traditionally been managed using intensive practices such as tillage and herbicides to control weeds and vegetation, thereby limiting competition with grapevines for water and nutrients in order to not compromise yields.

Fast, accurate, and non-destructive analytical techniques based on hyperspectral imaging (hsi) represent effective tools for food quality evaluation. A visible change in the appearance of a fresh product often negatively impacts the perceived quality from a consumer’s point of view.