A novel dataset and deep learning object detection benchmark for grapevine pest surveillance

Climate is a key parameter when the modulation of berry and subsequent wine composition is considered. Recent decades have already seen an increase in global surface temperatures

Wine grape pomace quantitatively and qualitatively represents the most important fraction of wine waste. Namely, this by-product makes ~ 20% of the total mass of vinified grapes, and it is characterized with high concentrations of polyphenolic antioxidants, as well as grape seed oil. Hence, valorization of wine pomace, as an alternative to traditionally employed disposal, has drown considerable interest in recent years. Earlier studies were mostly focused on the extraction of phenolics, while mechanisms enhancing the extraction of lipid fraction from grape pomace, as well as their impact on the grape seed oil quality are far less investigated.

to maintain viticulture under global warming conditions, it is important to carefully select the appropriate genotypes for each vine-growing region and develop cultivars that are drought resistant. this ability is highly dependent on hydraulic traits, which are dynamic and vary according to the vine’s developmental stage and climatic conditions. this framework steadily enhances our understanding of the differences in drought resistance among vitis genotypes. however, there is still a need to comprehensively grasp the intra-specific variability, particularly between oenological and table grape cultivars.

Grapevine varieties from South-America, commonly known as criollas, originated because of the natural crossbreeding of grapevine varieties brought by the Spaniards. The objective of this work was to evaluate the potential of some varieties to produce sparkling wines considering the effect of lees contact time. The following varieties were used: Moscatel Rosado, Criolla Chica, Pedro Gimenez, Blanca Oval, Canelón, and the European variety Chardonnay (control), planted in the ampelographic collection of EEA Mendoza INTA (Argentina). Pilot-scale vinifications were carried out to obtain the base wines, in 20 L glass containers. The second fermentation was performed through the traditional method.

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).