5 resultados para maize production areas of highly variable rainfall

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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In the present work qualitative aspects of products that fall outside the classic Italian of food production view will be investigated, except for the apricot, a fruit, however, less studied by the methods considered here. The development of computer systems and the advanced software systems dedicated for statistical processing of data, has permitted the application of advanced technologies including the analysis of niche products. The near-infrared spectroscopic analysis was applied to the chemical industry for over twenty years and, subsequently, was applied in food industry with great success for non-destructive in line and off-line analysis. The work that will be presented below range from the use of spectroscopy for the determination of some rheological indices of ice cream applications to the characterization of the main quality indices of apricots, fresh dates, determination of the production areas of pistachio. Next to the spectroscopy will be illustrated different methods of multivariate analysis for spectra interpretation or for the construction of qualitative models of estimation. The thesis is divided into four separate studies that consider the same number of products. Each one of it is introduced by its own premise and ended with its own bibliography. This studies are preceded by a general discussion on the state of art and the basics of NIR spectroscopy.

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Researches performed during the PhD course intended to assess innovative applications of near-infrared spectroscopy in reflectance (NIR) in the production chain of beer. The purpose is to measure by NIR the "malting quality" (MQ) parameter of barley, to monitor the malting process and to know if a certain type of barley is suitable for the production of beer and spirits. Moreover, NIR will be applied to monitor the brewing process. First of all, it was possible to check the quality of the raw materials like barley, maize and barley malt using a rapid, non-destructive and reliable method, with a low error of prediction. The more interesting result obtained at this level was that the repeatability of the NIR calibration models developed was comparable with the one of the reference method. Moreover, about malt, new kinds of validation were used in order to estimate the real predictive power of the proposed calibration models and to understand the long-term effects. Furthermore, the precision of all the calibration models developed for malt evaluation was estimated and statistically compared with the reference methods, with good results. Then, new calibration models were developed for monitoring the malting process, measuring the moisture content and other malt quality parameters during germination. Moreover it was possible to obtain by NIR an estimate of the "malting quality" (MQ) of barley and to predict whether if its germination will be rapid and uniform and if a certain type of barley is suitable for the production of beer and spirits. Finally, the NIR technique was applied to monitor the brewing process, using correlations between NIR spectra of beer and analytical parameters, and to assess beer quality. These innovative results are potentially very useful for the actors involved in the beer production chain, especially the calibration models suitable for the control of the malting process and for the assessment of the “malting quality” of barley, which need to be deepened in future studies.

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Root-yield-1.06 is a major QTL affecting root system architecture (RSA) and other agronomic traits in maize. The effect of this QTL has been evaluated with the development of near isogenic lines (NILs) differing at the QTL position. The objective of this study was to fine map qroot-yield-1.06 by marker-assisted searching for chromosome recombinants in the QTL interval and concurrent root phenotyping in both controlled and field conditions, through successive generations. Complementary approaches such as QTL meta-analysis and RNA-seq were deployed in order to help prioritizing candidate genes within the QTL target region. Using a selected group of genotypes, field based root analysis by ‘shovelomics’ enabled to accurately collect RSA information of adult maize plants. Shovelomics combined with software-assisted root imaging analysis proved to be an informative and relatively highly automated phenotyping protocol. A QTL interval mapping was conducted using a segregating population at the seedling stage grown in controlled environment. Results enabled to narrow down the QTL interval and to identify new polymorphic markers for MAS in field experiments. A collection of homozygous recombinant NILs was developed by screening segregating populations with markers flanking qroot-yield-1.06. A first set of lines from this collection was phenotyped based on the adapted shovelomics protocol. QTL analysis based on these data highlighted an interval of 1.3 Mb as completely linked with the target QTL but, a larger safer interval of 4.1 Mb was selected for further investigations. QTL meta-analysis allows to synthetize information on root QTLs and two mQTLs were identified in the qroot-yield-1.06 interval. Trascriptomics analysis based on RNA-seq data of the two contrasting QTL-NILs, confirmed alternative haplotypes at chromosome bin 1.06. qroot-yield-1.06 has now been delimited to a 4.1-Mb interval, and thanks to the availability of additional untested homozygous recombinant NILs, the potentially achievable mapping resolution at qroot-yield-1.06 is c. 50 kb.

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Against a backdrop of rapidly increasing worldwide population and growing energy demand, the development of renewable energy technologies has become of primary importance in the effort to reduce greenhouse gas emissions. However, it is often technically and economically infeasible to transport discontinuous renewable electricity for long distances to the shore. Another shortcoming of non-programmable renewable power is its integration into the onshore grid without affecting the dispatching process. On the other hand, the offshore oil & gas industry is striving to reduce overall carbon footprint from onsite power generators and limiting large expenses associated to carrying electricity from remote offshore facilities. Furthermore, the increased complexity and expansion towards challenging areas of offshore hydrocarbons operations call for higher attention to safety and environmental protection issues from major accident hazards. Innovative hybrid energy systems, as Power-to-Gas (P2G), Power-to-Liquid (P2L) and Gas-to-Power (G2P) options, implemented at offshore locations, would offer the opportunity to overcome challenges of both renewable and oil & gas sectors. This study aims at the development of systematic methodologies based on proper sustainability and safety performance indicators supporting the choice of P2G, P2L and G2P hybrid energy options for offshore green projects in early design phases. An in-depth analysis of the different offshore hybrid strategies was performed. The literature reviews on existing methods proposing metrics to assess sustainability of hybrid energy systems, inherent safety of process routes in conceptual design stage and environmental protection of installations from oil and chemical accidental spills were carried out. To fill the gaps, a suite of specific decision-making methodologies was developed, based on representative multi-criteria indicators addressing technical, economic, environmental and societal aspects of alternative options. A set of five case-studies was defined, covering different offshore scenarios of concern, to provide an assessment of the effectiveness and value of the developed tools.

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Power-to-Gas storage systems have the potential to address grid-stability issues that arise when an increasing share of power is generated from sources that have a highly variable output. Although the proof-of-concept of these has been promising, the behaviour of the processes in off-design conditions is not easily predictable. The primary aim of this PhD project was to evaluate the performance of an original Power-to-Gas system, made up of innovative components. To achieve this, a numerical model has been developed to simulate the characteristics and the behaviour of the several components when the whole system is coupled with a renewable source. The developed model has been applied to a large variety of scenarios, evaluating the performance of the considered process and exploiting a limited amount of experimental data. The model has been then used to compare different Power-to-Gas concepts, in a real scenario of functioning. Several goals have been achieved. In the concept phase, the possibility to thermally integrate the high temperature components has been demonstrated. Then, the parameters that affect the energy performance of a Power-to-Gas system coupled with a renewable source have been identified, providing general recommendations on the design of hybrid systems; these parameters are: 1) the ratio between the storage system size and the renewable generator size; 2) the type of coupled renewable source; 3) the related production profile. Finally, from the results of the comparative analysis, it is highlighted that configurations with a highly oversized renewable source with respect to the storage system show the maximum achievable profit.