Historical zoning in the world

Tempranillo is the most widely grown red grapevine variety in Spain, currently representing 42% of the total number of red varieties and 21% of the total vineyard area. Due to the economic importance that this variety represents in Spanish viticulture, in some areas where it is traditionally grown, there is a special concern about the viability of the future growing of this variety is being compromised by the climate change effects.

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.

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.

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Water resource is a major limiting factor impacted by climate change that threatens grapevine production and quality. Understanding the ecophysiological mechanisms involved in the response to water deficit is crucial to select new varieties more drought tolerant. A major bottleneck that hampers such advances is the lack of methods for measuring fine functioning traits on thousands of plants as required for genetic analyses. This study aimed at investigating how water deficit affects the trade-off between carbon gains and water losses in a large panel representative of the Vitis vinifera genetic diversity. 250 genotypes were grown under 3 watering scenarios (well-watered, moderate and severe water deficit) in a high-throughput phenotyping platform.