Freeze-thaw treatment to enhance phenolic ripening and tannin oxidation of seeds

Grapevine leaves are known to contain different polyphenols such as flavonols, catechins and stilbenes, which are known to act as main contributors for plant defense against pathogens (1). While the composition for some major cultivars has been studied, there is lack of systematic comparison about the content of these compounds in the wide ecodiversity of Vitis vinifera cv. Recent advances in Mass Spectrometry-based Metabolomics allow a wider and more sensitive description of these polyphenols, as instance of those present in leaves (2). Such information could help to better explain leaf traits regarding the development of the leaf or to the plant tolerance to a pathogen. Moreover, these compounds offer appealing applications for human health due to their antioxidant activities.

The climate change is afecting particulary to the South of Spain, with high temperatures. It is important to develop new strategies in order to mantain the quality of wines

Vitis vinifera is the most grown grapevine species, which originated about 6 million years ago in the trans-caucasian area as the ancestral (wild) type v. Vinifera spp. Sylvestris. On the other hand, the human being (homo sapiens) is much younger since he originated about 300.000 years ago in north africa.

The amino acids in grape juice are an important nitrogen source for yeast during alcoholic fermentation. Additionally, certain AAs are precursors to some of the volatile compounds found in wine and overall

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.