Integrative Inferences on Pattern Geometries of Grapes Grown under Water Stress and Their Resulting Wines.

Multiple datasets of two consecutive vintages of replicated grape and wines from six different deficit irrigation regimes are characterized and compared. The process consists of four temporal-ordered signature phases: harvest field data, juice composition, wine composition before bottling and bottled wine. A new computing paradigm and an integrative inferential platform are developed for discovering phase-to-phase pattern geometries for such characterization and comparison purposes.

Unravelling the geometry of data matrices: effects of water stress regimes on winemaking.

A new method is proposed for unravelling the patterns between a set of experiments and the features that characterize those experiments. The aims are to extract these patterns in the form of a coupling between the rows and columns of the corresponding data matrix and to use this geometry as a support for model testing. These aims are reached through two key steps, namely application of an iterative geometric approach to couple the metric spaces associated with the rows and columns, and use of statistical physics to generate matrices that mimic the original data while maintaining their inherent structure, thereby providing the basis for hypothesis testing and statistical inference.