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

Phenolic, volatile and nitrogen compounds are key to wine quality. On one hand, phenolic compounds are related to wine color, mouthfeel properties, ageing potential. and are associated with beneficial health properties. On the other hand, wine aroma is influenced by hundreds of volatile compounds. Fermentative aromas represent, quantitatively, the wine aroma, and among these volatile compounds, esters, higher alcohols and acids are mainly responsible for the fermentation bouquet.

The sensory characteristics of wine are a topic studied by several researchers over time, but it continues to be a current and challenging subject. These characteristics are fundamental for the consumer acceptability, which has increasingly aroused their interest to modulate them in line with current market trends and innovation demands. The wine physical-chemical and sensory properties depend on a wide set of factors: they begin to be designed in the vineyard and are later constructed during the various stages of winemaking. Afterwards, the wine is placed in bottles and stored or commercialized.

Wine aroma analysis can be done by sensorial or instrumental analysis, the latter involving several me-thodologies based on olfactometric detection, electronic noses or gas chromatography. Gas Chromatography has been widely used for the study of the volatile composition of wines and depending on the detection system coupled to the chromatographic system, quantification and identification of individual compounds can be achieved.

The development of off-flavours in wine distillates, particularly those associated with the tails fraction, is a key issue in the production of high-quality spirits.

Stomatal traits determine grapevine water use, carbon supply, and water stress, which directly impact yield and berry chemistry. Breeding for stomatal traits has the strong potential to improve grapevine performance under future, drier conditions, but the trait values that breeders should target are unknown. We used a functional-structural plant model developed for grapevine (HydroShoot) to determine how stomatal traits impact canopy gas exchange, water potential, and temperature under historical and future conditions in high-quality and hot-climate California wine regions (Napa and the Central Valley). Historical climate (1990-2010) was collected from weather stations and future climate (2079-99) was projected from 4 representative climate models for California, assuming medium- and high-emissions (RCP 4.5 and 8.5). Five trait parameterizations, representing mean and extreme values for the maximum stomatal conductance (gmax) and leaf water potential threshold for stomatal closure (Ψsc), were defined from meta-analyses. Compared to mean trait values, the water-spending extremes (highest gmax or most negative Ysc) had negligible benefits for carbon gain and canopy cooling, but exacerbated vine water use and stress, for both sites and climate scenarios. These traits increased cumulative transpiration by 8 – 17%, changed cumulative carbon gain by -4 – 3%, and reduced minimum water potentials by 10 – 18%. Conversely, the water-saving extremes (lowest gmax or least negative Ψsc) strongly reduced water use and stress, but potentially compromised the carbon supply for ripening. Under RCP 8.5 conditions, these traits reduced transpiration by 22 – 35% and carbon gain by 9 – 16% and increased minimum water potentials by 20 – 28%, compared to mean values. Overall, selecting for more water-saving stomatal traits could improve water-use efficiency and avoid the detrimental effects of highly negative canopy water potentials on yield and quality, but more work is needed to evaluate whether these benefits outweigh the consequences of minor declines in carbon gain for fruit production.