Wheat and low-input agriculture: agronomic, nutritional and nutraceutical implications

Recently, the increasing interest in organic food products and environmental friendly practices has emphasized the importance of selecting crop varieties suitable for the low-input systems. Additionally, in recent years the relationship between diet and human health has gained much attention among consumers, favoring the investigations on food nutraceutical properties. Among cereals, wheat plays an important role in human nutrition around the world and contributes to the daily intake of essential nutrients such as starch and protein. Moreover, whole grain contains several bioactive compounds that confer to wheat-derived products unique nutraceutical properties (dietary fibre, antioxidants). The present research provided interesting insights for the selection of wheat genotypes suitable for low-input systems and the development of specific breeding programs dedicated to organic farming. The investigation involved 5 old not dwarf genotypes (Andriolo, Frassineto, Gentil rosso, Inallettabile, Verna) and 1 modern dwarf variety (Palesio), grown under biodynamic management, over two consecutive growing seasons (2009/2010, 2010/2011). Results evidenced that under low-input farming some investigated old wheat genotypes (Frassineto, Inallettabile) were comparable to the modern cultivar in terms of whole agronomic performance. As regards the nutritional and nutraceutical properties, some old genotypes (Andriolo, Gentil rosso, Verna) emerged for their relevant content of several investigated phytochemicals (such as insoluble dietary fibre, polyphenols, flavonoids, in vitro antioxidant activity) and nutrients (protein, lipid, minerals). Despite of the low technological features, the six wheat varieties grown under low-input management may efficiently provide raw material for the preparation of traditionally processed bread with valuable sensory and nutritional properties. Results highlighted that old wheat varieties have peculiar phytochemical composition and may be a valuable source of nutraceutical compounds. Some of the genetic material involved in the present study may be used in breeding programs aimed at selecting varieties suitable for low-input farming and rich in health-promoting compounds.

Multiple stellar populations in globular clusters with photometry and low resolution spectroscopy

Our view of Globular Clusters has deeply changed in the last decade. Modern spectroscopic and photometric data have conclusively established that globulars are neither coeval nor monometallic, reopening the issue of the formation of such systems. Their formation is now schematized as a two-step process, during which the polluted matter from the more massive stars of a first generation gives birth, in the cluster innermost regions, to a second generation of stars with the characteristic signature of fully CNO-processed matter. To date, star-to-star variations in abundances of the light elements (C, N, O, Na) have been observed in stars of all evolutionary phases in all properly studied Galactic globular clusters. Multiple or broad evolutionary sequences have also been observed in nearly all the clusters that have been observed with good signal-to-noise in the appropriate photometric bands. The body of evidence suggests that spreads in light-element abundances can be fairly well traced by photometric indices including near ultraviolet passbands, as CNO abundance variations affect mainly wavelengths shorter than ~400 nm owing to the rise of some NH and CN molecular absorption bands. Here, we exploit this property of near ultraviolet photometry to trace internal chemical variations and combined it with low resolution spectroscopy aimed to derive carbon and nitrogen abundances in order to maximize the information on the multiple populations. This approach has been proven to be very effective in (i) detecting multiple population, (ii) characterizing their global properties (i.e., relative fraction of stars, location in the color-magnitude diagram, spatial distribution, and trends with cluster parameters) and (iii) precisely tagging their chemical properties (i.e., extension of the C-N anticorrelation, bimodalities in the N content).

Towards cheaper, safer and low environmental impact materials for energy storage devices: natural resources-derived carbon based electrodes and aqueous electrolytes for supercapacitors

The growing market of electrical cars, portable electronics, photovoltaic systems..etc. requires the development of efficient, low-cost, and low environmental impact energy storage devices (ESDs) including batteries and supercapacitors.. Due to their extended charge-discharge cycle, high specific capacitance, and power capabilities supercapacitors are considered among the most attractive ESDs. Over the last decade, research and development in supercapacitor technology have accelerated: thousands of articles have been published in the literature describing the electrochemical properties of the electrode materials and electrolyte in addition to separators and current collectors. Carbon-based supercapacitor electrodes materials have gained increasing attention due to their high specific surface area, good electrical conductivity, and excellent stability in harsh environments, as well as other characteristics. Recently, there has been a surge of interest in activated carbon derived from low-cost abundant sources such as biomass for supercapacitor electrode materials. Also, particular attention was given to a major challenging issue concerning the substitution of organic solutions currently used as electrolytes due to their highest electrochemical stability window even though their high cost, toxicity, and flammability. In this regard, the main objective of this thesis is to investigate the performances of supercapacitors using low cost abundant safe, and low environmental impact materials for electrodes and electrolytes. Several prototypes were constructed and tested using natural resources through optimization of the preparation of appropriate carbon electrodes using agriculture by-products waste or coal (i.e. Argan shell or Anthracite from Jerrada). Such electrodes were tested using several electrolyte formulations (aqueous and water in salt electrolytes) beneficing their non-flammability, lower cost, and environmental impact; the characteristics that provide a promising opportunity to design safer, inexpensive, and environmentally friendly devices compared to organic electrolytes.

Efficient and low-computational predictive models for spectral sensors

Spectral sensors are a wide class of devices that are extremely useful for detecting essential information of the environment and materials with high degree of selectivity. Recently, they have achieved high degrees of integration and low implementation cost to be suited for fast, small, and non-invasive monitoring systems. However, the useful information is hidden in spectra and it is difficult to decode. So, mathematical algorithms are needed to infer the value of the variables of interest from the acquired data. Between the different families of predictive modeling, Principal Component Analysis and the techniques stemmed from it can provide very good performances, as well as small computational and memory requirements. For these reasons, they allow the implementation of the prediction even in embedded and autonomous devices. In this thesis, I will present 4 practical applications of these algorithms to the prediction of different variables: moisture of soil, moisture of concrete, freshness of anchovies/sardines, and concentration of gasses. In all of these cases, the workflow will be the same. Initially, an acquisition campaign was performed to acquire both spectra and the variables of interest from samples. Then these data are used as input for the creation of the prediction models, to solve both classification and regression problems. From these models, an array of calibration coefficients is derived and used for the implementation of the prediction in an embedded system. The presented results will show that this workflow was successfully applied to very different scientific fields, obtaining autonomous and non-invasive devices able to predict the value of physical parameters of choice from new spectral acquisitions.

Distributed and synchronized measurements for the wide-area observation of electric power systems in distorted and low-inertia conditions

With the aim of heading towards a more sustainable future, there has been a noticeable increase in the installation of Renewable Energy Sources (RES) in power systems in the latest years. Besides the evident environmental benefits, RES pose several technological challenges in terms of scheduling, operation, and control of transmission and distribution power networks. Therefore, it raised the necessity of developing smart grids, relying on suitable distributed measurement infrastructure, for instance, based on Phasor Measurement Units (PMUs). Not only are such devices able to estimate a phasor, but they can also provide time information which is essential for real-time monitoring. This Thesis falls within this context by analyzing the uncertainty requirements of PMUs in distribution and transmission applications. Concerning the latter, the reliability of PMU measurements during severe power system events is examined, whereas for the first, typical configurations of distribution networks are studied for the development of target uncertainties. The second part of the Thesis, instead, is dedicated to the application of PMUs in low-inertia power grids. The replacement of traditional synchronous machines with inertia-less RES is progressively reducing the overall system inertia, resulting in faster and more severe events. In this scenario, PMUs may play a vital role in spite of the fact that no standard requirements nor target uncertainties are yet available. This Thesis deeply investigates PMU-based applications, by proposing a new inertia index relying only on local measurements and evaluating their reliability in low-inertia scenarios. It also develops possible uncertainty intervals based on the electrical instrumentation currently used in power systems and assesses the interoperability with other devices before and after contingency events.

Modelling of ORC components and systems for low-medium temperature heat recovery applications with reduced environmental impact

Although its great potential as low to medium temperature waste heat recovery (WHR) solution, the ORC technology presents open challenges that still prevent its diffusion in the market, which are different depending on the application and the size at stake. Focusing on the micro range power size and low temperature heat sources, the ORC technology is still not mature due to the lack of appropriate machines and working fluids. Considering instead the medium to large size, the technology is already available but the investment is still risky. The intention of this thesis is to address some of the topical themes in the ORC field, paying special attention in the development of reliable models based on realistic data and accounting for the off-design performance of the ORC system and of each of its components. Concerning the “Micro-generation” application, this work: i) explores the modelling methodology, the performance and the optimal parameters of reciprocating piston expanders; ii) investigates the performance of such expander and of the whole micro-ORC system when using Hydrofluorocarbons as working fluid or their new low GWP alternatives and mixtures; iii) analyzes the innovative ORC reversible architecture (conceived for the energy storage), its optimal regulation strategy and its potential when inserted in typical small industrial frameworks. Regarding the “Industrial WHR” sector, this thesis examines the WHR opportunity of ORCs, with a focus on the natural gas compressor stations application. This work provides information about all the possible parameters that can influence the optimal sizing, the performance and thus the feasibility of installing an ORC system. New WHR configurations are explored: i) a first one, relying on the replacement of a compressor prime mover with an ORC; ii) a second one, which consists in the use of a supercritical CO2 cycle as heat recovery system.

Microenvironment and therapeutic modulation of myelofibrosis in an experimental mouse model.

Primary myelofibrosis(PMF) is the most severe form of Philadelphia-negative myeloproliferative neoplasms(MPNs), characterized by splenomegaly, extramedullary hematopoiesis and bone marrow(BM) fibrosis, with disease progression to leukemia and low survival. The best therapy currently available includes treatment with a JAK inhibitor(Ruxolitinib), which only ameliorates symptoms. Unfortunately, the pathogenesis of the disease is still poorly understood. It has been hypothesized that its progression may be determined by the presence of inflammatory cytokines produced by the bone marrow microenvironment that promote fibrosis. The three aims of this PhD thesis, using the Gata1low mouse model of myelofibrosis, were: 1. Investigate the presence of different cytokines in the bone marrow microenvironment; 2. Test the efficacy of treatment with Reparixin, a CXCR1/2 receptor inhibitor; 3. Test the efficacy of treatment with RB40.34 (P-selectin inhibitor), alone and in combination with Ruxolitinib. In the first study, we demonstrated by immunohistochemistry(IHC) the presence in the BM of Gata1low mice of elevated levels of CXCL1, and its receptors CXCR1/2, and TGF-β1. Particularly, the cells with higher expression of these cytokines were the megakaryocytes. In the second study, we found that treatment with Reparixin in Gata1low mice showed dose-dependent efficacy in reducing bone marrow and splenic fibrosis. Furthermore, by IHC analysis we demonstrated that the treatment induced a decrease in the expression of TGF-β1. In the third study, we found that treatment with RB40.34 in combination with Ruxolitinib normalizes the phenotype of Gata1low mice, reducing fibrosis and the content of TGF-β and CXCL1 in the bone marrow, and restoring the architecture of hematopoiesis in the bone marrow and spleen. In summary, these data provide preclinical evidence that treatment with Reparixin and RB40.34 in combination with Ruxolitinib are effective on reversing the myelofibrotic trait in the Gata1low mouse model and encourage clinical trials to validate these compounds in human patients with PMF.