Grapes are rich in primary and secondary metabolites. Among the secondary metabolites, polyphenolic compounds are the most abundant in grape berries. Besides their important impacts on grape and wine quality, this class of compounds has beneficial effects on human health. Due to their antioxidant activity, polyphenols and phenolic acids can act as anti-inflammatory and anticancerogenic agents, and can modulate the immune system. In grape berries, polyphenols and phenolic acids can be located in the pericarp and seeds, but distribution differs considerably among these tissues. Although some classes of polyphenols and phenolic acids are under strict genetic control, the final content is highly influenced by environmental factors, such as climate, soil, vineyard, and management. This review aims to present the main classes of polyphenolic compounds and phenolic acids in different berry tissues and grape varieties and special emphasis on their beneficial effect on human health.

(1) Background: Solid phase microextraction (SPME)-Arrow is a new extraction technology recently employed in the analysis of volatiles in food materials. Grape volatile organic compounds (VOC) have a crucial role in the winemaking industry due to their sensory characteristics of wine.; (2) Methods: Box–Behnken experimental design and response surface methodology were used to optimise SPME-Arrow conditions (extraction temperature, incubation time, exposure time, desorption time). Analyzed VOCs were free VOCs directly from grape skins and bound VOCs released from grape skins by acid hydrolysis.; (3) Results: The most significant factors were extraction temperature and exposure time for both free and bound VOCs. For both factors, an increase in their values positively affected the extraction efficiency for almost all classes of VOCs. For free VOCs, the optimum extraction conditions are: extraction temperature 60 °C, incubation time 20 min, exposure time 49 min, and desorption time 7 min, while for the bound VOCs are: extraction temperature 60 °C, incubation time 20 min, exposure time 60 min, desorption time 7 min.; (4) Conclusions: Application of the optimized method provides a powerful tool in the analysis of major classes of volatile organic compounds from grape skins, which can be applied to a large number of samples.

Important contributors to grape quality are secondary metabolites, that will consequently define the wine quality and consumer acceptance. Secondary metabolites that influence the aromatic profile of grapes are volatile organic compounds (VOCs). Over the years, several hundred VOCs have been identified in grapes and wines, ranging from trace amounts up to several milligrams, belonging to the classes of terpenoids (monoterpenes, sesquiterpenes, and norisoprenoids), volatile phenols, methoxypyrazines, and aliphatic compounds. In grapes these compounds are influenced by numerous factors, such as grape variety, climate, and vineyard management practices. Thus, the analysis of grape VOCs, including sample preparation, identification, and quantification, is important to understand the influence of individual compounds in the aromatic profile. The biosynthetic pathways and genes involved are still not fully elucidated due to the large number of genes and precursors that participate in VOC metabolism and contribute to the complexity. Our aim is to provide an overview of volatile compounds synthesized in grape berries, explore their biosynthetic pathways, and discuss the analytical methods used for their identification and quantification.

Grape volatile organic compounds (VOCs) play an important role in the winemaking industry due to their contribution to wine sensory characteristics. Another important role in the winemaking industry have the grapevine varieties used in specific regions or countries for wine production. Due to the high variability of grapevine germplasm, grapevine varieties are as classified based on their genetic and geographical origin into genetic-geographic groups (GEN-GEO). The aim of this research was to investigate VOCs in 50 red grapevine varieties belonging to different GEN-GEO groups. The study included varieties from groups C2 (Italy and France), C7 (Croatia), and C8 (Spain and Portugal). The analysis of VOCs was performed by SPME-Arrow-GC/MS directly from grape skins. The analyzed VOCs included aldehydes, ketones, acids, alcohols, monoterpenes, and sesquiterpenes. The most abundant VOCs were aldehydes and alcohols, while the most numerous were sesquiterpenes. The most abundant compounds, aldehydes and alcohols, were found to be (E)-2-hexenal, hexenal, (E)-2-hexen-1-ol, and 1-hexanol. Using discriminant analysis, the GEN-GEO groups were separated based on their volatile profile. Some of the individual compounds contributing to the discrimination were found in relatively small amounts, such as benzoic acid, (E,E)-2,4-hexadienal, 4-pentenal, and nonanoic acid. The groups were also discriminated by their overall volatile profile: group C2 was characterized by a higher content of aldehydes and alcohols, and group C8 was characterized by a higher content of sesquiterpenes and acids. Group C7 was characterized by all low amount of all classes of VOCs.

In the era of sustainable grapevine production, there is a growing demand to define differences between Vitis vinifera varieties in susceptibility to downy mildew. Croatia, as a country with a long tradition of grapevine cultivation, preserves a large number of native grapevine varieties. A leaf disc bioassay has been conducted on 25 of them to define their response to downy mildew, according to the International Organisation of Vine and Wine (OIV) descriptor 452-1, together with the stress response of the leaf discs using chlorophyll fluorescence and multispectral imaging with 11 parameters included. Time points of measurement were as follows: before treatment (T₀), one day post-inoculation (dpi) (T₁), two dpi (T₂), three dpi (T₃), four dpi (T₄), six dpi (T₅), and eight dpi (T₆). Visible changes in form of developed Plasmopara viticola (P. viticola) sporulation were evaluated on the seventh day upon inoculation. Results show that methods applied here distinguish varieties of different responses to downy mildew. Based on the results obtained, a phenotyping model in the absence of the pathogen is proposed, which is required to confirm by conducting more extensive research.