How artificial intelligence (AI) is helping winegrowers to deal with adversity from climate change

Wine cellars are affected by seasonally fluctuating workloads and face challenges especially in the harvest period connected to the required timely processing of the harvested grapes.

Global climate change is exerting a notable influence on viticulture sector and grape composition. The increase in temperature and the changes in rainfall pattern are causing a gap between phenolic and technological grape maturities [1]. As a result, the composition of grapes at harvest time and, consequently, that of wines are being affected, especially with regards to phenolic composition. Hence, wine quality is decreasing due to changes in the organoleptic properties, such as color and astringency, making necessary to implement new adaptive technologies in wineries to modulate these properties in order to improve wine quality.

Most consumers enjoy wine in moderation, however, there remains a minority that may develop risky drinking habits, potentially harming themselves and those around them. For the last fifteen years, a prime objective of the wine in moderation programme has been to educate and empower the wine sector and now for the first time, a central education tool has been developed, integrating the topic of moderate consumption horizontally in all wine activities. The entire wine value chain – from the producer to the salesperson to the restaurant service staff – can contribute to reduce harmful consumption and encourage responsible drinking patterns.

Intensification is considered one of the major drivers of biodiversity loss in farmland. The more intensive management practices that have been adopted the last decades, contributed to species declines from all taxonomic groups. Moreover, agricultural intensification has led to an important change of land use. Complex, mixed agro-ecosystems with cultivated and non-cultivated habitats have been converted to simplified, intensive and homogeneous ones with severe effects on biodiversity.

Vineyard nutrient management is crucial for reaching production-specific quality standards, yet timely evaluation of nutrient status remains challenging. The existing sampling protocol of collecting vine tissue (leaves and/or petioles) at bloom or veraison is time-consuming. Additionally, this sampling practice is too late for in-season fertilizer applications (e.g. N is applied well before bloom). Therefore alternative early-season protocols are necessary to predict the vine nutrient demand for the upcoming season. The main goals of this project are to 1) optimize existing tissue sampling protocols; 2) determine the amount of nutrients removed at the end of the growing season.