Volatile organic compounds (VOCs) are the key aroma producers in fruits and sensory quality of fruits is widely determined by qualitative and quantitative composition of VOCs. The aroma of grape is a complex of hundreds of VOCs belonging to different chemical classes like alcohols, esters, acids, terpenes, aldehydes, furanones, pyrazines, isoprenoids and many more. VOCs play important role as they determine the flavor of grapes and wine made from it. The objective of this thesis is to study of VOCs through development of different mass spectrometry based analytical methodologies and its applications for the comprehensive investigation and construction of database of the VOCs in grapes. First part of the study was dedicated to generation of the comprehensive database of grape VOCs through the screening of multiple grape varieties (n=124) representing different species, color and origin. The experiment was carried out using headspace solid-phase microextraction (HS-SPME) and gas chromatography mass spectrometry (GC-MS) based approach and according to metabolomics protocols. A customized dataset of reference standards (>350) was generated and, an automated pipeline for data analysis was created in collaboration with data management group of the institute. The results showed annotation of “level 1†of 117 VOCs in grape. The established database in this experiment will represent the significant portion of the future Grape Metabolome database. The second part of the study was dedicated to study the differential behavior of volatile organic compounds and their glycosylated precursors qualitatively and semi quantitatively. Volatile secondary metabolites also exist in the form of nonvolatile and odorless glycosylated precursors in grape and studies have confirmed that concentration of these precursors can be much higher than its free counterparts. The elevated concentrations of volatiles in glycosylated forms can significantly affect the wine aroma because of possible chemical modifications throughout the process of fermentation and wine ageing. In addition, the investigation of the biosynthesis and accumulation of VOCs in the fruit tissues requires the consideration of both the free and bound forms. To study the phenomenon an experiment was carried using solid phase extraction (SPE) of the free and glycosylated precursors; with enzymatic hydrolysis aglycone part of the precursors was released followed by subsequent GC-MS analysis. Over 10 different selected grape varieties were analyzed. Sixty-six significant different aroma compounds in grapes (pre and post hydrolysis) were identified. Identification was done based on several parameters like retention time, retention index and MS spectral database. The multivariate statistical analysis by two-way hierarchical clustering with heat map visualization showed distribution of the compounds within different varieties before and after hydrolysis. In the third part of the study, we performed experiments dedicated to training and applications of atmospheric pressure gas chromatography mass spectrometry (APGC-MS). The experiment was carried out at the Department of Biological Sciences, University of North Texas, under the supervision of Prof. Vladimir Shulaev. We have established the metabolomics protocol for the analysis of fruit volatiles using APGC-MS with an optimized GC and MS conditions and created novel library of the fruit volatile compounds using APGC-MS system. Six different grape varieties were analyzed as a case study and experimental results showed APGC-MS as a valuable solution for metabolomics analysis. The data processing and statistical evaluation was done using XCMS and progenesis QI© software. Moreover, observations based on injections of pure reference standards showed high abundance of molecular ions with minimal fragmentation at low collision energy that is typically missing in traditional vacuum source GC-MS. Moreover, the use of elevated collision energy data resulted in a spectrum similar to the traditional EI data.

Cell membrane is the biological barrier serving as both territorial defense and the communication hinge for the interior of cell from its surroundings. As building blocks of cellular membranes and also precursor for second messengers, a variety of lipids play essential roles in cellular membrane dynamics as well as important functions such as cell proliferation, apoptosis, signal transduction and membrane trafficking modulation. Lipidomics, representing the systematic and integrative studies of diversified lipids (lipidome) in a biological system, is an emerging yet rapid developing field and hence requires advanced and complementary analytical techniques as well as multiple statistical tools. Our development of reliable analytical methodology (the advanced Mass Spectrometric and high-resolution NMR techniques) and application of multiple statitistical approaches (multivariate data analysis and univariate t-test) enable us to achieve these comprehensive understandings. We have investigated, first of all, the effects induced by hypoxia on cervical cancer derived cells (HeLa cells) to see how and how much the changes in phospholipids profile are able to get light into the targeted biological problem (hypoxia) and provide a preliminary insight into the underlying mechanisms. We found that hypoxia stimulation dramatically reduced the total amount of cellular phosphoinositols (PI) but prominently increased the amount of lyso phosphocholines (lyso-PC) and lyso phosphoethanolamines (lyso-PE). Moreover, our studies suggested the polyunsaturated phospholipids species as stronger biomarkers upon hypoxia treatment. The evaluation of changes in the average unsaturation index (UI) of the membrane lipids acyl chains revealed that UI slightly increased in several lipid classes, thus affecting membrane fluidity and further membrane-dependent functions. The plausible mechanisms by HeLa cells to adapt to hypoxia conditions are briefly reported as well. We have also conducted the comparative lipidomic studies of urothelial cancer cell line RT4 (a model system of a benign tumor) and T24 (a model system of a metastatic tumor) aiming to reveal probable roles and relevant differential changes of membrane lipids with respect to urinary bladder metastasis progress. Significant changes of lipids metabolism were found to correlate with urothelial nonmetastatic and metastatic cell models. The most remarkable finding was that the malignant cell type (T24) showed a strong decrease of ether PC species complemented by a sharp increase of the length and the average unsaturation number of lipids acyl chains. Ceramide-based sphinglipids also showed altered profiles in these two cell types. Such analyses suggest a certain significant re-organization of cellular membrane in malignant cell transformation, involving variations in compositional lipid structures and possible signaling transduction pathways. Observations of such reduction of the 1-alkyl PC species and the chain shortening of lipid species might serve as a tool in urinary bladder cancer intervention.

This PhD project arises from the growing awareness of food quality and safety on the part of citizens and institutions. The increase in the population to feed, the lengthening of the production and distribution chains and the socio-economic risks of a poor diet make it crucial to monitor the quality of food from the producer to the consumer. Traditional methods (sensory panels and laboratory analytical techniques) are too expensive and above all slow to evaluate the quality of fresh foods that deteriorate over the course of a few hours. In this context, it is crucial to develop monitoring devices that are cheap, rapid and non-invasive, in order to be able to evaluate the quality of food products extensively and constantly. Solid-state gas sensors are an ideal candidate, as they are inherently non-invasive and inexpensive. In this context, the project focused on chemoresistive sensors based on semiconductor metal oxides, which are among the simplest and most performing, and have the advantage of being sensitive to almost all gases and VOCs. Initially, nanostructures of different materials (n- and p-type semiconductors) and of different morphologies (nanowires and nanosheets) were studied in order to investigate the performance of individual sensors. In this way, some devices have been optimized with respect to the detection of possible biomarkers of the degradation of specific foods. The sensors have demonstrated a rapid response (from a few seconds to a minute), an intense response and above all a very low detection limit (less than 1ppmv, in some cases a few tens of ppbv), important for agri-food applications. This approach is the simplest since it requires a single sensor that is selective towards a certain molecule (ammonia, ethylene...) which can be considered the only important information parameter in a certain application. In most cases, however, the gaseous emission of a food is composed of a large quantity of volatile compounds, and the low selectivity of resistive sensors makes it difficult to discriminate the molecules most informative regarding the degradation process. For this reason, in the second part of the PhD we used the sensors developed up to then to create electronic noses. Exploiting the dimensions of nanostructures, we have developed a new concept of thermal electronic nose, i.e. with sensors of the same material, but within a thermal gradient. In this way, by exploiting multivariate statistical analysis and machine learning techniques, the devices acquired a greater ability to discriminate and quantify the different gases. The electronic noses have shown that they can perfectly recognize the different gases tested (100%) and estimate their concentration with an error of a few ppmv. Measurements in the laboratory are very useful for testing the performance parameters of sensors and electronic noses, as they make it possible to evaluate the correctness of the classification and the error in estimating the concentration of any gas. On the other hand, measuring the emissions of fresh food is different, as the concentrations are not known, and therefore a different approach is needed. The final stage of the project involved using electronic noses to assess the freshness of certain agri-food products. As the developed sensors were particularly sensitive to ammonia, it was decided to study the degradation of meat and fish, where this gas is an important marker. The electronic noses have been able to accurately recognize the meat from the fish (> 95%), and evaluate the state of degradation by giving a very accurate estimate of the microbial count (>95%), responding in a very short time (tens of seconds). The miniaturized electronic noses developed during this PhD project have therefore successfully demonstrated to be a rapid and non-invasive cross-sectional tool for assessing the freshness of agri-food products.

GC×GC is an efficient tool for the analysis of volatile compound. However, improvements are still required on VOC extraction, GC×GC setup and data processing. Different sample preparation techniques and GC×GC setup were compared based on the literature study and experimental results. Each VOC extraction technology has its own drawbacks and needs new developments. There wasn’t an ideal sample preparation technique to recover all the VOCs from the beverage sample. Furthermore, the VOCs recovered by different techniques were very different. The discussion of the pros and cons of the different techniques in our study can serve as a guide for the further development and improvement of these techniques. Combining the results from different sample preparation techniques is necessary to achieve a higher coverage of global VOC profiling. For the known fermentative aromatic compounds, the best coverage can be reached by using SPME together with SPE for beer, and VALLME for wine and cider. A fine GC×GC method development involves modulator selection, column combination and parameter optimization. Thermal modulator provides high detection sensitivity and allow exceptional trace analysis. Since the analytes coverage is the most important factor of in beverage VOC profiling, thermal modulation is a better choice. In fermented beverages, there are more polar compounds than non-polar compounds. The most suitable column combination is polar-semipolar. Same column diameters shall be used to minimize the column overloading. GC×GC parameters must be optimized. These parameters interact with each other therefore statistical prediction model is required. Response surface model is capable of doing this job while using a small number of experimental tests. The nearest neighbor distance was a suitable measurement for peak dispersion. Column and detector saturations are unavoidable if the metabolic sample is measured at one dilution level, incorrect peak deconvolution and mass spectrum construction may happen. Data processing results can be improved by a two-stage data processing strategy that will incorporate a targeted data processing and cleaning approach upstream of the “standard” untargeted analysis. Our experiments show a significant improvement in annotation and quantification results for targeted compounds causing instrumental saturation. After subtracting the saturate signal of targeted compounds, the MS construction was improved for co-eluted compounds. Incomplete signal subtraction may occur. It leads to the detection of false positive peaks or to interferences with the construction of mass spectra of co-diluted peaks. High-resolution MS libraries and more accurate peak area detection methods should be tested for further improvement.

Mass spectrometry imaging (MSI) is a MS-based technique. It provides a way of ascertaining both spatial distribution and relative abundance of a large variety of analytes from various biological sample surfaces. MSI is able to generate distribution maps of multiple analytes simultaneously without any labeling and does not require a prior knowledge of the target analytes, thus it has become an attractive molecular histology tool. MSI has been widely used in medicine and pharmaceutical fields, while its application in plants is recent although information regarding the spatial organization of metabolic processes in plants is of great value for understanding biological questions such as plant development, plant environment interactions, gene function and regulatory processes. The application of MSI to these studies, however, is not straightforward due to the inherent complexity of the technique. In this thesis, the issues of plant sample preparation, surface properties heterogeneity, fast MSI analysis for spatially resolved population studies and data analysis are addressed. More specifically, two MSI approaches, namely matrix assisted laser desorption ionization (MALDI) imaging and desorption electrospray ionization (DESI) imaging, have been evaluated and compared by mapping the localization of a range of secondary and primary metabolites in apple and grapes, respectively. The work based on MALDI has been focused on the optimization of sample preparation for apple tissues to preserve the true quantitative localization of metabolites and on the development of specific data analysis tool to enhance the chemical identification in untargeted MSI (chapter 3). MALDI imaging allows high-spatial localization analysis of metabolites, but it is not suitable for applications where rapid and high throughput analysis is required when the absolute quantitative information is not necessary as in the case of screening a large number of lines in genomic or plant breeding programs. DESI imaging, in contrast, is suitable for high throughput applications with the potential of obtaining statistically robust results. However, DESI is still in its infancy and there are several fundamental aspects which have to be investigated before using it as a reliable technique in extensive imaging applications. With this in mind, we investigated how DESI imaging can be used to map the distribution of the major organic acids in different grapevine tissue parts, aiming at statistically comparing their distribution differences among various grapevine tissues and gaining insights into their metabolic pathways in grapevine. Our study demonstrated that this class of molecules can be successfully detected in grapevine stem sections, but the surface property differences within the structurally heterogeneous grapevine tissues can strongly affect their semi-quantitative detection in DESI, thereby masking their true distribution. Then we decided to investigate this phenomenon in details, in a series of dedicated imaging studies, and the results have been presented in chapter 4. At the same time, during DESI experiments we have observed the production of the dianions of small dicarboxylates acids. We further studied the mechanism of formation of such species in the ion source proposing the use of doubly charged anions as a possible proxy to visualize the distributions of organic acid salts directly in plant tissues (chapter 5). The structural organization of the PhD thesis is as below: Chapter one and Chapter two describe the general MSI principle, compare the most widely used MSI ion sources, and discuss the current status in MSI data pre-processing and statistical methods. Due to the importance of sample preparation in MSI, sample handling for plant samples is independently reviewed in chapter two, with all the essential steps being fully discussed. The first two chapters describe the comprehensive picture regarding to MSI in plants. Chapter three presents high spatial and high mass resolution MALDI imaging of flavonols and dihydrochalcones in apple. Besides its importance in plant research, our results demonstrate that how data analysis as such Intensity Correlation Analysis could benefit untargeted MSI analysis. Chapter four discusses how sample surface property differences in a structurally/biologically heterogeneous sample affect the quantitative mapping of analytes in the DESI imaging of organic acids in grapevine tissue sections. Chapter five discusses the mechanism of formation of dicarboxylate dianions in DESI and ESI Chapter six summarizes the work in the thesis and discusses the future perspectives.

Resveratrol is a polyphenolic compound produced by various plants and present in dietary sources such as red wine. In recent years, its beneficial effects for human health, including protection from heart diseases and cancer prevention, have attracted increasing interest. Resveratrol acts both as an antioxidant and a prooxidant agent when works in vivo with Cu(II) ions occurring naturally in living organisms. The aim of this work is to study the gas phase reactivity of resveratrol in presence of copper and iron ions, in order to more insights on the role of copper in the proposed biological mechanism. By electrospray ionization (ESI) mass spectrometry we have produced and detected some resveratrol-copper complexes by using a resveratrol/CuSO4 solution in acetonitrile/water, and their most stable structures have been calculated at the B3LYP/6-311G(d) level of theory. The formation of dehydrodimer product was also detected in ESI-MS/MS experiments and its structure assigned with evidences for isomeric compounds from copper and iron reactions with resveratrol. Density Functional Theory (DFT) calculations have been carried out to elucidate reaction mechanisms. Finally, the crucial role of the para-OH group in resveratrol structure has been demonstrated by investigating reactions with copper sulfate of synthetic analogues, bearing different number and position of OH groups.

No description available.

Grapevine (Vitis spp.) is one of the most widely cultivated perennial fruit crops in the world and its economic relevance is mainly related to wine production. In recent years, the increased frequency of extreme phenomena such as heat waves has been acknowledged as one of the most significant climate variables negatively affecting grape yield and berry composition, with consequences also on wine quality. Thus, studying the physiological, metabolic and genetic factors that are involved in grapevine response to high temperatures is essential to improve the knowledge of mechanisms underlying thermotolerance, aiming to support plant breeding innovation and the development of new management strategies in viticulture. In this work, a segregating population obtained from the crossing of ‘Rhine Riesling’ and ‘Cabernet Sauvignon’ was studied in the field with a multidisciplinary approach. The progeny (around 120 genotypes) was evaluated for phenological traits affected by changing temperatures, in particular bud burst, flowering and véraison, while physiological response to heat stress was assessed in various hot summer days by measuring chlorophyll fluorescence kinetics and stomatal conductance. Measures were collected in the early morning as control and in the afternoon during hot hours. Phenotypic data were then used in combination with a high-density linkage map (average distance between adjacent markers 0.78 cM), previously developed using genotypic information from 139 individuals, to perform QTL analysis. Based on physiological responses to high temperatures, selected individuals showing contrasting behaviour, together with parental lines, were further studied in controlled conditions. In the field, in fact, plants may be subjected to combined stresses and changes in environmental conditions may heavily influence plants response. With the experiment in controlled condition, on the other hand, plants were stressed at higher temperatures, compared to the ones registered in the field, by maintaining all the other sources of variability constant. In the growth chamber plants were studied for their physiological response to heat stress by using the same approach adopted in the field. To better understand mechanisms involved in grapevine adaptation to heat stress conditions, individuals with contrasting behaviour were studied also for their metabolome modifications, both in the field and in controlled conditions. Volatile organic compounds (VOCs) were investigated with an untargeted approach applying conventional methods of analysis. Accumulation of VOCs in grapevine leaves was analysed using gas chromatography coupled with mass spectrometry (GC-MS) after a pre-concentration with a solid-phase micro-extraction (SPME) approach. On the other hand, VOCs emission during stress was investigated in controlled conditions thanks to the use of the Closed-Loop Stripping Analysis (CLSA) which allows the collection of VOCs directly emitted by plants. Analysis was then performed with GC-MS. Metabolic alterations of non-volatile compounds were examined with an untargeted analysis using high-performance liquid chromatography coupled with a high-resolution mass spectrometer equipped with an electrospray soft ionization (HPLC-HR-ESI-MS). In this work a metabolomic workflow was developed, starting from sample collection and extraction to sample analysis and data interpretation. The analytical method developed allowed the preliminary evaluation of leaf metabolome alterations due to stress factors. In fact, the use of a weak cation-exchange mixed mode column, in combination with a data dependent acquisition mode, allowed a first wide screening of both primary and secondary metabolites resulting in a good compromise for metabolic fingerprinting. QTL analysis on the segregating population allowed the identification of several QTLs, related to both phenological and physiological traits, with the discovery of interesting putative candidate genes for grapevine resilience to changing temperatures. This is the first time that a similar approach has been applied to a perennial fruit crop by analysing chlorophyll fluorescence and leaf transpiration traits related to heat stress. On the other hand, the multidisciplinary approach allowed the fine characterization of Rhine Riesling and Cabernet Sauvignon response to high temperatures, both in controlled and field conditions, a tentative classification of ‘tolerant’ and ‘susceptible’ progeny individuals and the identification of metabolic pathways altered during heat stress in the susceptible plants. Together with the implementation of a novel metabolomic workflow based on HPLC-HR-ESI-MS, this work represents a novelty in studies on grapevine response to changing temperatures, as it considered not only the berry metabolism but the resilience of the plants itself, paving the way for future studies on thermotolerance.

In a worldwide context where the community has to make giant leaps forward to contain the catastrophic consequences of climate change, we need to face the discordant “How do we power our economies?” with green and circular solutions instead of hiding behind the hypocrisy of fossil fuels. Biomass, renewable, abundant, and cheap, can trigger a shift towards a zero-carbon emission economy, in which it substitutes fossil fuels for the production of energy and materials. Among the strategies to valorize biomass, hydrothermal processes are green pathways for producing biofuels and bio-based materials. However, research has yet to fill several gaps to make these processes ready for industrial scaling and spreading. Therefore, along with this Ph.D. thesis, we provide new insights into hydrothermal processes, touching several scientific areas: from in-depth research around the thermochemical fundamentals to the engineering of new sustainable and biorefinery concepts. Through fundamental research, we try to answer “What’s happening during hydrothermal processes?” facing the enormous complexity of the process by investigating chemical pathways, kinetics, and thermodynamics. Facing sustainability, we explored the coupling of hydrothermal conversion with concentrated solar energy to develop a zero-energy process and the integration of hydrothermal carbonization with subsequent treatments to valorize by-products.

The present work regards the development of a methodology for the study of atmospheric particulate matter (PM) which is alternative to instrumental measurements. The methodology developed exploits the surfaces already present in the field as samplers of PM. In particular, conifer needles and building facades are employed to investigate different temporal ranges: conifer needles potentially retain particles circulating in the atmosphere from the recent past up to now, while building facades could retain particles from an older period up to know. The field of application of the approach developed are the situations in which a wide territory must be monitored, eventually including remote locations, or information on past pollution scenario must be reconstructed in the absence of monitoring stations. For instance, the evaluation of the improved efficiency of off-gas abatement systems of industrial plants is a typical case of application. These pollution sources affect large areas and might have been active before regulation on air quality required constant monitoring of their emissions. Typically in such a case the methodology could assist in evaluating how large was in the past and it is nowadays the area of impact of the plant. In general, such an approach could be valuable whenever relying on instrumental measurements is cost and time consuming in terms of installing a large network of monitoring stations to study the dispersion of pollutants from a single or few sources. To have a detailed description of the spatial distribution of pollutant particles, they are studied individually with subsequent higher magnification. Where no traces of a source are detected by scanning electron microscopy coupled with energy dispersive x-ray spectroscopy (SEM-EDXS), the samples are analyzed with the higher resolution of transmission electron microscopy coupled with energy dispersive x-ray spectroscopy (TEM-EDXS) and selected area electron diffraction (SAED) in order to make sure that no smaller particles, able to travel farther from their source, are present at a certain site. All data provided by electron microscopy analysis of particles collected by conifer needles are placed in the context of elemental concentrations measured by inductively coupled plasma atomic emission spectroscopy (ICP-AES), which is a bulk analytical technique. The same is not possible for the data on single particles present on building facades given the inorganic matrix of the substrate, especially in the case of metal oxide paints, which does not allow the bulk measurement. Both the preparation of the samples for bulk analytical techniques and single particle analysis by electron microscopy were optimized. For method development and evaluation, the analytical protocol was applied to estimate spatial and temporal trends of accumulation of inorganic pollutants that can be related with changes in the emissions of atmospheric pollutants by an electric arc furnace (EAF) steelmaking plant located in a test site. The benefits of combining the single particle and bulk analytical techniques emerged especially for the discrimination of the emissions from different sources.