Flor yeast diversity and dynamics in biologically aged wines

The need to rationalize agricultural inputs has recently increased interest in assessing vineyard variability in order to implement variable rate input applications, so-called ‘precision viticulture’. In many viticultural areas globally, precision viticulture is already widely used such as for selective harvesting and variable rate application (VRA) of inputs such as irrigation and/or fertilizer. Robust VRA relies on having a geostatistically accurate map (of one or more vineyard attributes) requiring high sampling densities, which can be cost- and time-prohibitive to obtain. Previous work on spatial interpolation using kriging have upscaled ground-based measurements, but such upscaling strategies are applicable only when vineyard conditions are spatially continuous and satisfies the assumption of second-order stationary processes. Alternatively, mixed models that combine kriging and auxiliary information, such as the regression kriging (RK) method, are more instructive for spatial predictions. In order to improve prediction accuracies, it is therefore necessary to incorporate additional information to achieve accurate spatial patterns with low error.

Climate change, with rise in temperatures, is leading to an advance in the dates of phenological stages, with a loss in quality of the grape final product. Therefore, the understanding of the genetic determinants driving the phenological stages of flowering, veraison and the interval between them, represents a target for the development of grapevine’s cultivar adapted to the changing environment.
Here we conducted a GWA study to identify SNPs significantly associated to flowering time, veraison time and to the interval among them. A germplasm collection (CREA-VE in Susegana, Treviso, Italy) including 649 grapevine’s cultivar representing 365 unique genotypes was considered.

It is fundamental for wineries to know the potential yield of their vineyards as soon as possible for future planning of winery logistics. As such, non-invasive image-based methods are being investigated for early yield prediction. Many of these techniques have limitations that make it difficult to implement for practical use commercially. The aim of this study was to assess whether yield can be estimated using images taken in-field with a smartphone at different phenological stages.

The complexity of the wine matrix makes the monitoring of the winemaking process crucial. Fourier Transform Infrared Spectroscopy (FTIR) along with chemometrics is considered an effective analytical tool combining good accuracy, robustness, high sample throughput, and “green character”. Portable and non-portable FTIR devices are already used by the wine industry for routine analysis. However, the analytical calibrations need to be enriched, and some others are still waiting to be thoroughly developed.

The importance of polyphenols, which are present in many vegetables and grapes too, is well-know and documented. Specific research works about the red grape