Hyperspectral imaging and Raman spectroscopy, nondestructive methods to assess wine grape composition

Long-term studies on grapevine phenology have clearly demonstrated that global warming is affecting phenological events, leading to an anticipation in their timing, and negatively impacting grape yield and berry quality. Therefore, dissecting the genetic determinants involved in the plant regulation of the phenological stages of budburst, flowering, veraison and ripening can improve our knowledge of the underlying mechanisms and support plant breeding programs and the advancement of vineyard management strategies.
We report here the results of a QTL mapping experiment conducted on three segregating populations obtained from the crossing of ‘Cabernet Sauvignon’ and ‘Corvina’, ‘Corvina’ and the hybrid ‘Solaris’ and ‘Rhine Riesling’ and ‘Cabernet Sauvignon’.

Far from complicated discussions on the relevant way to define « terroir », this article deals with the social perception that French young adults (aged from 18 to 30) have of this concept and the way it can help them to become wine consumers.

Currently, to consistently ensure the maintenance of a wine-style while benefiting from the utmost rigor made possible by the winemaking process, the composition of the wine blend is made using sensory control. This is performed after the wine is made with no real possibility of deterministic intervention.

The barrel-making process is widely recognized as a crucial practice that affects the composition of barrel-aged wine. After the drying process, the staves are considered ready for barrel assembly, which includes the processes of bending and toasting the barrel structure. Toasting is considered one of the most critical stages in determining the physical and chemical composition of the staves, which can influence the chemical and sensory composition of the wine aged in barrels made from them [1].

Grapevine yield and fruit quality are two major drivers of input allocation and, ultimately, revenue for grape producers. Because yield and fruit quality vary substantially from year-to-year and within a single block, opportunities exist for optimization via precision management activities that could lead to more profitable and sustainable grape production. Here, we review recent advances in the techniques and technology used to measure, estimate, and forecast grapevine yield and fruit quality. First, we discuss direct “measurement” of yield and quality (i.e. ground-truth data generation), with an emphasis on potential for scalability and automation. Second, we discuss technology and techniques that do not directly measure yield and quality, but use correlated measurements for their estimation.