Mining terroir influence on bioactive polyphenols from grape stems: A correlation-network-driven approach to spatialize metabolomics data

Drought is one of the main challenges for viticulture in the context of global change. The choice of rootstock could be leveraged for vineyard adaptation to drought as we can improve plant performance without modifying the scion variety. However, most of the existing rootstocks, selected over a century ago, have a narrow genetic background which could compromise their adaptive potential.

New and developing technologies, that provide sensors and the software systems for using and interpreting them, are becoming pervasive through our lives and society. From smart phones to cars to farm machinery, all contain a range of sensors that are monitored automatically with intelligent software, providing us with the information we need, when we need it. This technological revolution has the potential to monitor all aspects of vineyard activity, assisting growers to make the management choices they need to achieve the outcomes they want. For example, a future vineyard may possess automated imaging that generates a three dimensional model of the vine canopy, highlighting differences from the desired structure and how to use canopy management to improve fruit composition, or generates maps with yield estimates and measurements of berry composition throughout the growing season.

Dehydrodicatechins have recently received attention as oxidation markers especially in grapes and wine. Their analysis mainly uses LC-MS/MS which is able to differentiate them from their natural isomers (dimeric procyanidins), based on specific fragments

Botrytis cinerea Pers., the causal agent of grey mould disease, is responsible for substantial economic losses, as it causes reduction of grape and wine quality and quantity. Exploitation of antagonistic yeasts is a promising strategy for controlling grey mould incidence and limiting the usage of synthetic fungicides. In our previous studies, 119 different indigenous yeasts were screened for putative multidimensional modes of action against filamentous fungus B. cinerea [1]. The most promissing biocontrol yeast was Pichia guilliermondii ZIM624, which exhibited several anatagonistic traits (production of cell wall degrading enzymes, chitinase and β-1,3-glucanase; demonstration of in vitro inhibitory effect on B. cinerea mycelia radial growth; production of antifungal volatiles, assimilation of a broad diversity of carbon sources, contributing to its competitivnes in inhabiting grapes in nature).

Because terroir and cultivar are drivers of wine quality, is essential to investigate theirs effects on polyphenolic profile before promoting the implantation of a red minority variety in a specific area. This work, included in MINORVIN project, focuses in the polyphenolic profile of 7 red grapevines minority varieties of Vitis vinifera L. (Morate, Sanguina, Santafe, Terriza Tinta Jeromo Tortozona Tinta) and Tempranillo) from six typical viticulture Spanish areas: Aragón (A1), Cataluña (A2), Castilla la Mancha (A3), Castilla –León (A4), Madrid (A5) and Navarra (A6) of 2020 season. Polyphenolic substances were extracted from grapes. 35 compounds were identified and quantified (mg subtance/kg fresh berry) by HPLC and grouped in anthocyanins (ANT) flavanols (FLAVA), flavonols (FLAVO), hydroxycinnamic (AH), benzoic (BA) acids and stilbenes (ST). Antioxidant activity (AA, mmol TE /g fresh berry) was determined by DPPH method. The results were submitted to a two-way ANOVA to investigate the influence of variety, area and their interaction for each polyphenolic family and cluster analysis was used to construct hierarchical dendrograms, searching the natural groupings among the samples. Sanguina (A3) had the most of total polyphenols while Tempranillo (A5) those of ANT. Sanguina (A2) and (A3) reached the highest values of FLAVO, FLAVA and AA. These two last samples had also the maximum of AA. The effect cultivar and area were significant for all polyphenolic families analyzed. A high variability due to variety (>50%) was observed in FLAVA and the maximum value of variability due to growing area was detected in AA (86.41%), ANT and FLAVO (51%); the interaction variety*zone was significant only for ANT, FLAVO, EST and AA. Finally, dendrograms presented five cluster: i) Sanguina (A2); ii) Sanguina (A3); iii) Tempranillo (A5); iv) Tempranillo (A3); Terriza (A3,A5), Morate (A5,A6); v) Santafé (A1,A6); Tortozona tinta (A1,A3,A6); Tinta Jeromo (A3,A4).