A novel dataset and deep learning object detection benchmark for grapevine pest surveillance

La adaptación de nuevas variedades a zonas de cultivo fuera de su área de origen presenta múltiples interrogantes. En Castilla-La Mancha se está produciendo en los últimos años una gran inquietud por la diversificación y la reconversión de variedades.

The application of remote and proximal sensing in viticulture have been demonstrated as a fast and efficient method to monitor vegetative and physiological parameters of grapevines. The collection of these parameters could be highly valuable to derive information on associated yield and quality traits in the vineyard. However, to leverage the informative potential of the sensing systems, a series of preliminary evaluations should be carried out to standardize working protocols for the specific features of a winegrowing area (e.g., pedoclimate, topography, cultivar, training system). This work aims at evaluating remote and proximal sensing systems for their performance and suitability to provide information on the vegetative, physiological, yield and qualitative aspects of vines and grapes as a function of different training systems in the Valpolicella wine region (Verona, Italy).

Le climat a de fortes implications sur le bon fonctionnement physiologique de la vigne et a besoin d’être quantifié afin de déterminer l’aptitude des régions à la culture de la vigne. Une méthode, qui pourrait éventuellement servir à prévoir l’aptitude des régions à la culture de la vigne, est proposée.

In addition to aroma compounds also protein composition strongly influences the quality of wines. Proteins of wine derive mainly from the plant Vitis vinifera and may be influenced by abiotic stress as well as fermentation conditions or fining. Additionally, fungal infections can affect the protein content as well by introducing fungal proteins or affecting grape protein composition. An infection of the vine with the plant pathogenic fungus Botrytis (B.) cinerea was shown to cause a degradation of proteins in the resulting wine. Moreover, it influences the foaming properties in sparkling wine.

Studies on wineomics (wine’s metabolome) have increased considerably over the last two decades. Wine results from many environmental, human and biological factors leading to a specific metabolome for each terroir. NMR metabolomics is a particularly effective tool for studying the metabolome since it allows the rapid and simultaneous detection of major compounds from several chemical families.1 Quantitative NMR has already proven its effectiveness in monitoring the authenticity of still wines.