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

Phenolic compounds are responsible for the most important red wine quality attributes. Anthocyanins and tannins play crucial roles in color and mouthfeel properties of red wines. Phenolic analysis in the winery is hindered by analytical constrains.

The oenological potential of grapes at harvest depends on a combination of the major components of Terroir: the climate, the soil, the plant material, the training system and the crop management.

The analysis of the distribution of natural plant populations allows an ecological characterization of cultivated environments in thermal, water and trophic terms; it guides the choice or selection of plants (or grape varieties) to cultivate (Astruc et al ., 1984, 1987; Delpoux, 1971; Jacquinet and Astruc, 1979). This approach has given good results in areas where the topography is the determining factor in the ecological differentiation of the terroirs.

Spain is one of the main producers of high-quality fortified wines. Particularly some of them elaborated in Andalusia have acquired a great prestige for being unique due to their production in a specific geographical area with traditional methods, the grape variety used, the climate and the soil. Such is their distinguishing feature achieved that they have been protected by the European Union with the indication “Protected Designation of Origin” (PDO). Thus, there are four PDO of fortified wines in Andalucía (‘Condado de Huelva’, ‘Jerez Xérès Sherry’, ‘Manzanilla Sanlúcar de Barrameda’, and ‘Montilla-Moriles’). Furthermore, within each PDO,there are different categories according to their particular characteristics and winemaking conditions such as the aging process.

Modern grapevine breeding programs have overcome many challenges using genomic selection, which has allowed breeders to make targeted selections at earlier stages in the breeding process. However, the cost of genetic testing may present a burden for some programs, and markers often struggle to accurately predict quantitative traits. Recent advances in high throughput, high-dimensional data have provoked investigation into the use of high-dimensional phenomics as a low-cost addition to the grape breeder’s toolkit that may offer advantages in predicting quantitative traits. High-dimensional secondary trait (HDST) data has been employed in annual crops for prediction of agriculturally important traits such as yield.