Grape (Vitis vinifera L.) is among the most cultivated plants in the world. Its origin traces back to the Neolithic era, when the first human communities started to domesticate wild Vitis sylvestris L. grapes to produce wines. Domestication modified Vitis vinifera to assume characteristics imparted from the humans, selecting desired traits (e.g. specific aromas), and excluding the undesired ones. This process made this species very different from all the other wild grape species existing around the world, including its progenitor, Vitis sylvestris. Metabolomics is a field of the sciences that comparatively studies the whole metabolite set of two (or more) groups of samples, to point out the chemical diversity and infer on the variability in the metabolic pathways between the groups. Crude metabolomics observation can be often used for hypotheses generation, which need to be confirmed by further experiments. In my case, starting from the grape metabolome project (Mattivi et al. unpublished data), I had the opportunity to put hands on a huge dataset built on the berries of over 100 Vitis vinifera grape varieties, tens of grape interspecific hybrids and few wild grape species analyzed per four years; all included in a single experiment. Starting from this data handling, I designed specific experiments to confirm the hypotheses generated from the observation of the data, to improve compound identification, to give statistical meaning to the differences, to localize the metabolites in the berries and extrapolate further information on the variability existing among the grape genus. The hypotheses formulated were two: 1) several glyco-conjugated volatiles can be detected, identified and quantified in untargeted reverses-phase liquid chromatography-mass spectrometry; 2) The chemical difference between Vitis vinifera and wild grape berries is wider than reported in literature. Furthermore, handling a huge dataset of chemical standards injected under the same conditions of the sample set, I also formulated a third hypothesis: 3) metabolites with similar chemical structures are more likely to generate similar signals in LC-MS, therefore the combined use of the signals can predict the more likely chemical structure of unknown markers. In the first study (chapter 5), the signals putatively corresponding to glycoconjugated volatiles have been first enclosed in a specific portion of the temporal and spectrometric space of the LC-HRMS chromatograms, then they have been subjected to MS/MS analysis and lastly their putative identity have been confirmed through peak intensity correlation between the signals measured in LC-HRMS and GC-MS. In the second study (chapter 6), a multivariate regression model has been built between LC-HRMS signals and the substructures composing the molecular structure of the compounds and its accuracy and efficacy in substructure prediction have been demonstrated. In the third study (chapter 7), I comparatively studied some wild grapes versus some Vitis vinifera varieties separating the basic components of the grape berry (skin, flesh and seeds), with the aim to identify all the detected metabolites that differentiate the two groups, which determine a difference in quality between the wild versus domesticated grapes, especially regarding wine production.

In the recent years, the consumer choices have been focused on health-promoting plant-based food and their preferences are oriented towards regional foodstuff from local productions. Therefore, an important factor for vegetables grown Trentino-Alto Adige (Italy) is to point out the added value of alpine farming to evaluate the nutritional values of farming products. Omics technologies (e.g. genomics, transcriptomics, proteomics and metabolomics) are aimed at investigating the assessment of different pools of molecules and how they are translated into the structure, function, and dynamics of a biological system or systems in order to provide a comprehensive characterization of a specific organism. Research use the omics techniques to exhaustively understand the functionality of food components. Several sophisticated chromatographic methods, spectroscopic techniques and chemometric tools are applied to give an insight into a comprehensive overview of the intrinsic quality, typicality and regionality of specific plant-based foods in the present PhD thesis: apples and potatoes. The quality of these foods is evaluated by quantifying the secondary metabolites to investigate their nutraceutical values. The aim of this PhD project is to use several analytical techniques (LC-MS, UV-VIS) that are capable of comprehensively characterizing the food metabolome with particular emphasis on those components with high nutritional values. The data analysis and data handling of omics data requires advanced bioinformatic, statistical, and chemometric tools. Potatoes and apples are chosen as target matrices for these studies for their relevance in the local economy and for the peculiar chemical composition of particular interest for their health-promoting proprieties. The information is acquired using several sophisticated chromatographic and spectroscopic techniques, such as ultra-high performance liquid chromatography coupled with triple quadrupole mass spectrometry (UHPLC– MS/MS) and UV/VIS. It is integrated to chemometric approaches (principal component analysis (PCA), partial least square regression (PLS), and data fusion) to achieve a comprehensive targeted chemical characterization. The sampling procedures gathers, in the case of the potatoes study, reference cultivars that may be found in the common retailers of Trentino/Alto-Adige and different production areas, the apples of 22 cultivars were harvest from the fields of the Laimburg Research Centre (Vadena, Italy) to guaranty comparability of the obtained data. Our results may be used as solid foundation for a reliable evaluation of apples and potatoes healthy "potential" value based on cutting-edge techniques, which are capable of providing comprehensive data regarding the alpine food quality parameters with high efficiency and reliability