Grape variety identification and detection of terroir effects from satellite images

Cis-acting regulatory elements are DNA sequences that can be bound by transcription factors to regulate the expression of genes in a condition-dependent and tissue-specific way. It is nowadays possible to search for DNA motives and sequences that a given transcription factor is binding or at least can, but it is still hard to have a glance at all the transcription factors that are contemporaneously located at the same locus. Inspired by an existing technique that uses the CRISPR-Cas system in mammal cells, we are trying to develop a protocol to study such regulation in Vitis vinifera. Using the highly sequence-specific binding capacity of a catalytically inactive Cas9 protein (dCas9), our idea is to set up a system to target a desired sequence and precipitate all the crosslinked proteins and distantly interacting chromatin at this locus and analyze them.

Since the emergence of phylloxera, grafting has been the most used propagation method in viticulture. Despite all the improvement measures implemented in the nurseries, it is frequent that graft success rates vary depending on the nursery process and scion/rootstock combinations. The reasons behind this unsatisfactory behaviour are still unknown and can be diverse, although carbohydrate reserves might be hypothesised to be crucial, since callus, root, and new tissue formation will be built based on them. In order to identify the effect of carbohydrates on grafting success, nine combinations were established based on the starch content in grapevine scionwoods (cv. Tempranillo clone VN69) and rootstocks cuttings (110 Richter clone 237) used for grafting: Low (L), Medium (M), High (H).

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.

Wine perception results from the interaction between the wine and its intrinsic and extrinsic characteristics and the experience [1], background and beliefs of the consumer [2,3]. Among all of the factors affecting wine perception, in this study we focused on culture and cognitive processes, working under the hypothesis that higher familiarity with wines would induce higher perceived quality. Furthermore, we hypothesised that culture would influence the verbalisation of wine properties associated with the different experiences of consumers from different cultures.

Weeds are undesirable plants in agroecosystems as they compete with the crop for essential resources such as light, water and nutrients, compromising the final yield and its quality.