Coping with extreme climatic events: some lessons from recent work on grapevine under heat peak

The bunch rot induced by Botrytis cinerea is an important disease of grapevine that causes a diminution of grape quality and a considerable yield loss leading to an economic loss

The two most deadly viruses infecting and threatening the productivity of grapevines worldwide are leafroll and red blotch viruses. There is no cure for viral diseases other than roguing the symptomatic vines and replacing them with certified vines derived from clean, virus-tested stocks.
Given that phloem plays a central role in virus infection, this study aimed to purge the virus by girdling the phloem of leafroll-infected vines at different phenological stages of infected grapevines. Phloem-girdling was performed on canes at veraison to varying regions between the proximal and distal clusters.

Vinification by carbonic maceration (CM) is based in the anaerobic fermentative metabolism also called intracellular fermentation (IF).

Climate change impacts grape production worldwide and in California drought and salinity became increasingly challenging for grape growers to maintain sustainable production and fruit quality.

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.