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

The reproducibility of elemental profile in wines produced across multiple vintages has been previously reported using grapes from a single scion clone of Vitis vinifera L. cv. Pinot noir. The grapevines were grown on fourteen different vineyard sites, from Oregon to southern California in the U.S.A., which span distances from approximately hundreds of meters to 1450 km, while elevations range from near sea level to nearly 500 m. In addition, sensorial (i.e. aroma, taste, and mouthfeel) and chemical (i.e. polyphenolic and volatile) differences across the different vineyard sites have also been observed among these wines at two aging time points. While strong evidence exists to support that grapes grown in different regions can produce wines with unique chemical and sensorial profiles, even when a single clone is used, the understanding of growing site characteristics that result in this reproducible differentiation continues to emerge. One hypothesis is that the elemental profile that a vineyard site imparts to the grape berries and the resulting wine is an important contributor to this differentiation in chemistry and sensory of wines. For example, various classes of enzymes that catalyze the formation of key aroma compounds or their precursors require specific metals. In this work, we begin to report correlations between elemental and volatile aroma profiles of site-specific Pinot noir wines, made under standardized winemaking conditions, that have been previously shown to be distinguished separately by these chemical analyses.

The study of wine evolution during barrel aging is an important aspect of wine quality. Our previous works have shown that wine metabolome monitoring by

1H-NMR approaches allows determining the impact of different winemaking processes including traitements using enzymes or finning agents [1].

The aim of this work was to determine the reaction products of bisulfite with grape seed flavanols and changes therein over different storage conditions in a model wine

Berry composition at ripeness can be explained by many factors. This study was carried out from 2004 through 2011 in a 60 block network in the Yonne region, Burgundy.

Viticulture and grapevine breeding programs have to face and adapt to the rapidly changing growing conditions due to the ongoing climate change, the scarcity of resources and the demand for sustainability within the whole value chain of wine production. In times of highly effective and cost-efficient genotyping technologies routinely applied in plant research and breeding, the need for comparable high-speed and high-resolution phenotyping tools has increased substantially. The disciplines of grapevine research, breeding and precision viticulture picked up this demand – mostly independent from each other – by the development, validation and establishment of different sensor technologies in order to extend management strategies or to transform labor-intensive and expensive phenotyping.