When microalgae are exposed to changing environmental conditions, e.g., light-dark cycles or oscillations in nutrient availability (CO2, nitrogen, phosphate or silicate) they respond with metabolic changes in the carbon allocation pattern. Short time regulations in the time range of few seconds to minutes can be mirrored best by mass spectroscopy based metabolomics. However, these snap shots do not reflect the alterations in the carbon flow to the cellular macromolecules like protein, carbohydrate or lipid. In this review it is shown how the combination of FTIR spectroscopy and Chla-in-vivo-fluorescence based electron transport rates can reveal changes in the metabolic flux rates of carbon during a shift of the environmental conditions. The review will demonstrate in which time range FTIR spectroscopy can deliver significant information and how FTIR spectroscopy data can synergistically support metabolome analysis by mass-spectroscopy.

Proteomics is the large-scale study of proteins, particularly their structures and functions. Proteomics has been utilized in medicine for investigation of disease mechanisms and biomarker discovery. Instrumental methods cover sample preparation, protein and peptide separation and mass spectrometry. At present, there is no proteomic method that can be used as universal for every sample. Analytical methods need to be adapted and optimized for certain samples. The aim of this work was to create methodic procedures and to interpret results of experimental and clinical research. The first part of the thesis includes experiments utilizing proteomics to study changes in the plasma proteome clinically relevant porcine model of sepsis-induced peritonitis. Proteomic analyzes were also starting methodological strategies in experiments aimed at kidney physiology and pathophysiology of acute kidney injury during sepsis. Renal biopsies were analyzed in order to study the time course of proteome changes caused by sepsis and surgery. The second part of the thesis contains experiments studying biocompatibility. A method for elution of proteins interacting with adsorbents used in extracorporeal liver support system and with hemodialyzer capillaries was prepared. Analysis of proteins adsorbed to polysulfone...

This diploma thesis deals with the research the effect of the application of selenium as a fertilizer in the substrate mycelium of oyster mushroom (Pleurotus ostreatus) on the growth of this element in the dry state mushroom. Utilization of the cumulative mushrooms characteristic, i.e. the ability to cumulate into them the substance from the enviroment. The purpose of this experiment is the possibility of using the enriched oyster mushroom (Pleurotus ostreatus) on selenium as a potential functional food. The theoretical is focused on explaining the various terms of fungus, its composition, characteristics and effects on the human body, focusing mainly on oyster mushroom ( Pleurotus ostreatus). There is paid more attention to selenium, its form, function and its effect on the human body. The practical part of the thesis includes experimental results arising from the cultivation of oyster mushroom (Pleurotus ostreatus) on substrate, which is enriched with pentahydrate sodium selenite (Na2SeO3.5H2O) in various concentrations. Single samples are determinend by using mass spectrometry with inductively coupled plasma (ICP-MS , inductively coupled plasma mass spectrometry) after decomposition of the sample in a microwave system. The results are according to the individual selenium contents in the dry matter of oyster mushroom (Pleurotus ostreatus) presented in the recommended daily doses (DDD) for possible use as functional foods. Part of this thesis is also to research the influence of the concentration of selenium on the growth of mycelia of oyster mushroom (Pleurotus ostreatus).

BOČKOVÁ, T. Analysis of selected foods by NIR, Master thesis, MENDELU in Brno, 2015, 72p. The aim of the thesis was to examine samples of regionally grown cereals, oilseeds and legumes using NIR analyzer DA 7200 and compare the results to the tables and chemical analysis. A total of 26 samples were used. For the whole, crushed and milled grains and seeds, according to the type of the sample, analysis of water, crude protein, crude fiber, crude fat and starch were made. The content of crude protein was verified by the chemical laboratory. NIR measurements showed discrepancies in the case of evaluation of individual substances for the whole, crushed and milled grains or seeds, although the same material was used and the measured values should be similar. We have detected for example crude protein content in Apache (Litava) wheat sample by NIRS analysis 129,3 +- 1,78 g.kg-1 for the whole grains, 116,5 +- 0,72 g.kg-1 for the crushed grains and 100,9 +- 2,71 g.kg-1 for the milled grains. The chemical analysis for the same sample showed the value of 120,8 g.kg-1. According to the literature, the crude protein content in wheat should be between 118 and 132,1 g.kg-1. When evaluating the characteristics of the whole, crushed and milled samples crude protein content reached 135,6 +- 8,78 g.kg-1 for the whole, 132,3 +- 9,97 g.kg-1 for the crushed and 130,5 +- 11,55 g.kg-1 for the milled samples. Given that the crude protein measurement results were in accordance with the chemical analyses and the tabular values, it is apparent that the NIR analyzer is working properly. The results of this thesis, however, bring the presumption that the device setting is now not suitable for multiple analyses of different materials.

Contamination of soils with heavy metals is one of the serious environmental problems threatening human being. Heavy metals are considered as the special hazard of soil pollutants because of the adverse effects on the plant growth, the amount, activity of useful microorganisms in soils and the quality of food. Regard to the persistent and toxicity, the heavy metals are toxic when we consider different kinds of pollutants in soils. In the soil, zinc (Zn), cadmium (Cd), lead (Pb) and mercury (Hg) toxicities frequently occur than the other metals because of their precipitation and sorption by the soil. It is a very dangerous situation because when these metals are taken up by plants, they can be transported to the food web and food chains. In the present study, the accumulation of four heavy metals (mercury, zinc, lead and cadmium) in the whole grain of spring accessions of emmer, einkorn and common spring wheat cultivars and potato (Solanum tuberosum) is reported. Heavy and essential elements were monitored in potato cultivars in the exact field experiments and in hydroponically grown plants. The elements were determined by methods FAAS, ET AAS, and AMA (Advance Mercury Analysis). Statistical analyses were performed using SPSS 9.0 with the Tukey HSD (Honestly Significant Difference) test (alpha equal to 0.05). In our study, the concentration of heavy metals decreased in the order zinc (Zn) > lead (Pb) > cadmium (Cd) > mercury (Hg) in the wheat grain. The comparison between three varieties of investigated wheat revealed that the emmer wheat was rich in zinc content (62.12 mg kg-1 dry matter), while the spring wheat had the lowest average concentration of zinc in the grain (40.99 mg kg-1 dry matter). Generally, the values of lead concentration in grain wheat varieties were low (ranging from 0.1268 mg kg-1 dry matter to 0.2950 mg kg-1 dry matter). The concentrations of mercury in four typical growth stages of wheat (boot stage 10, heading stage 10.2 1/4 of head emerged, leaf-stage 10.2 and stage ripening 11 according to Feekes) were also determined. It has been shown that the concentrations of mercury in different wheat varieties were absorbed differently at different growth stages of plant. Stage 10.2 and leaf stage 10.2 showed the high mercury content (0.0152 mg kg-1 dry matter and 0.0214 mg kg-1 dry matter, respectively). Among individual varieties significant differences were determined. Amounts of toxic and potentially toxic elements detected in investigated potato tubers are characterized by a large variability within investigated groups. Performing statistical analysis (one way ANOVA) showed that there were no significant differences between two investigated groups of samples (samples from Uhříněves and Valečov in the year 2013 and 2014) considering either one of investigated metals. Measurable levels of mercury were found in smallest amounts in all investigated potato samples comparing to other metals (Cd, Pb). Plant cells compared to animal cells are characterized by the formation of cell walls. Plasma membrane or cell membrane is a biological active membrane separating the interior of cell from the outside environment. An adjusted method for isolation of protoplasts was developed and adapted for isolation of protoplasts from plant material (potatoes). In our experiment, the plants were grown hydroponically in the Research Institute of Plant Crops Prague-Ruzyně. If we examine the plant membrane, one option is to remove the cell wall by means of special mixture enzymes. Protoplasts were released in the dark at 25 degrees of Celsius for 18 hours. The 70 and 90 microns sieve was used to filter and then centrifugation for 5 minutes at 100 x g. All the steps were carefully carried out to prevent the damage or breakage of protoplasts.

This diploma thesis is focused on the issue of Analysis of the elemental composition of selected electrical waste (Waste Electrical and Electronic Equipment). The main goal is to determine amount of rare metals contained in central processing unit (CPU). The literature search was formed from available literature with the purpose to characterize the legislative framework for waste electrical and electronic equipment and the issue of collection of the selected e-waste in the European Union, particularly in the Czech Republic. In the practical part was analyzed selected samples of central processing units produced in 2000-2009. With the help of X-ray fluorescence spectrometry method was found to vary the amount of each element during the development of these units. Based on the results of completed survey we can conclude that the investigated samples con-tain economically usable elements. In the conclusion was evaluated the method which was used to determine the elemental composition and results was compared with other authors. This serves to see whether rare metals of processor that could be potentially economically exploited.

Removal of lead from municipal wastewater using a constructed wetland with a horizontal subsurface flow was studied. Wastewater, wetland plant and sediment samples were analyzed using an AAS Thermo Scientific iCE 3500. Average concentrations of lead in inflow and outflow water in 2015 were 1.47 and 0.74 ?g/l, respectively. Average concentrations of lead in inflow and outflow water in 2016 were 0.75 and 0.38 ?g/l. The average efficiency of lead removal was 49.2 %. Lead concentrations in vegetation (Phragmites australis) varied in the range of 0.081-0.087 mg/kg and 0.48-0.17 mg/kg for the above and belowground biomass, respectively. Lead concentration in sediments were 9.79 and 4.86 mg/kg at distances of 1 and 10 m from inflow zone. Lead and other heavy metals were predominantly removed from wastewater at the initial part of the wetland bed.

This thesis deals with the application of the electrical impedance spectrometry (EIS) method and the implemented Z-meter III device, Z-meter IV device respectively, while observing the infiltration of simulated flushing water with the aim of assessing the possibility or the appropriateness of its use. The experiment was carried out in the Laboratory of Water Management Research.

DIPLOMA THESIS Purification of phlorizin from Malus domestica Borkh.by solid-phase extraction and semi-preparative high-performance liquid chromatography Eva Prachařová Charles University, Faculty of Pharmacy in Hradec Králové Department of Pharmaceutical Botany The aim of this diploma thesis was to find the best conditions for purification of a flavonoid extract from leaves of Malus domestica Borkh., and obtaining the purest fraction of phlorizin. Phlorizin may be used in the treatment of diabetes mellitus type 2 in the future, it has the ability to reduce glycemia by reducing the absorption of glucose in the small intestine and by increasing urinary glucose excretion. The first step was to find an SPE cartridge with a suitable sorbent and a suitable eluent for solid phase extraction. The DPA-6S cartridge and 100% methanol as an eluentwerefound to be the most suitable for SPE. The next step was to find the best possible conditions for semi-preparative HPLC using an ACE 5 C18 column (5 μm, C18, 150 x 10 mm i.d., 150 mm length). The mobile phase consisted of 1% (v/v) acetic acid in water (solvent A) and ethanol 100% (v/v) (solvent B), and a linear gradient elution was used (10-100% B), 0-60 min, the flow: 1mL/min. This method resulted in the 91.05% purity of phlorizin. Keywords: phlorizin, SPE,...

Roads are important infrastructure and are primary means of transportation. Control and maintenance of roads are substantial as the pavement surface deforms and deteriorates due to heavy load and influences of weather. Acquiring detailed information about the pavement condition is a prerequisite for proper planning of road pavement maintenance and rehabilitation. Many companies detect and localize the road pavement distresses manually, either by on-site inspection or by digitizing laser data and imagery captured by mobile mapping. The automation of road condition mapping using laser data and colour images is a challenge. Beyond that, the mapping of material properties of the road pavement surface with spectrometers has not yet been investigated. This study aims at automatic mapping of road surface condition including distress and material properties by integrating laser scanning, RGB imaging and spectrometry. All recorded data are geo-referenced by means of GNSS/ INS. Methods are developed for pavement distress detection that cope with a variety of different weather and asphalt conditions. Further objective is to analyse and map the material properties of the pavement surface using spectrometry data. No standard test data sets are available for benchmarking developments on road condition mapping. Therefore, all data have been recorded with a mobile mapping van which is set up for the purpose of this research. The concept for detecting and localizing the four main pavement distresses, i.e. ruts, potholes, cracks and patches is the following: ruts and potholes are detected using laser scanning data, cracks and patches using RGB images. For each of these pavement distresses, two or more methods are developed, implemented, compared to each other and evaluated to identify the most successful method. With respect to the material characteristics, spectrometer data of road sections are classified to indicate pavement quality. As a spectrometer registers almost a reflectivity curve in VIS, NIR and SWIR wavelength, indication of aging can be derived. After detection and localization of the pavement distresses and pavement quality classes, the road condition map is generated by overlaying all distresses and quality classes. As a preparatory step for rut and pothole detection, the road surface is extracted from mobile laser scanning data based on a height jump criterion. For the investigation on rut detection, all scanlines are processed. With an approach based on iterative 1D polynomial fitting, ruts are successfully detected. For streets with the width of 6 m to 10 m, a 6th order polynomial is found to be most suitable. By 1D cross-correlation, the centre of the rut is localized. An alternative method using local curvature shows a high sensitivity to the shape and width of a rut and is less successful. For pothole detection, the approach based on polynomial fitting generalized to two dimensions. As an alternative, a procedure using geodesic morphological reconstruction is investigated. Bivariate polynomial fitting encounters problems with overshoot at the boundary of the regions. The detection is very successful using geodesic morphology. For the detection of pavement cracks, three methods using rotation invariant kernels are investigated. Line Filter, High-pass Filter and Modified Local Binary Pattern kernels are implemented. A conceptual aspect of the procedure is to achieve a high degree of completeness. The most successful variant is the Line Filter for which the highest degree of completeness of 81.2 % is achieved. Two texture measures, the gradient magnitude and the local standard deviation are employed to detect pavement patches. As patches may differ with respect to homogeneity and may not always have a dark border with the intact pavement surface, the method using the local standard deviation is more suitable for detecting the patches. Linear discriminant analysis is utilized for asphalt pavement quality analysis and classification. Road pavement sections of ca. 4 m length are classified into two classes, namely: “Good” and “Bad” with the overall accuracy of 77.6 %. The experimental investigations show that the developed methods for automatic distress detection are very successful. By 1D polynomial fitting on laser scanlines, ruts are detected. In addition to ruts also pavement depressions like shoving can be revealed. The extraction of potholes is less demanding. As potholes appear relatively rare in the road networks of a city, the road segments which are affected by potholes are selected interactively. While crack detection by Line Filter works very well, the patch detection is more challenging as patches sometimes look very similar to the intact surface. The spectral classification of pavement sections contributes to road condition mapping as it gives hints on aging of the road pavement. / Straßen bilden die primären Transportwege für Personen und Güter und sind damit ein wichtiger Bestandteil der Infrastruktur. Der Aufwand für Instandhaltung und Wartung der Straßen ist erheblich, da sich die Fahrbahnoberfläche verformt und durch starke Belastung und Wettereinflüsse verschlechtert. Die Erfassung detaillierter Informationen über den Fahrbahnzustand ist Voraussetzung für eine sachgemäße Planung der Fahrbahnsanierung und -rehabilitation. Viele Unternehmen detektieren und lokalisieren die Fahrbahnschäden manuell entweder durch Vor-Ort-Inspektion oder durch Digitalisierung von Laserdaten und Bildern aus mobiler Datenerfassung. Eine Automatisierung der Straßenkartierung mit Laserdaten und Farbbildern steht noch in den Anfängen. Zudem werden bisher noch nicht die Alterungszustände der Asphaltdecke mit Hilfe der Spektrometrie bewertet. Diese Studie zielt auf den automatischen Prozess der Straßenzustandskartierung einschließlich der Straßenschäden und der Materialeigenschaften durch Integration von Laserscanning, RGB-Bilderfassung und Spektrometrie ab. Alle aufgezeichneten Daten werden mit GNSS / INS georeferenziert. Es werden Methoden für die Erkennung von Straßenschäden entwickelt, die sich an unterschiedliche Datenquellen bei unterschiedlichem Wetter- und Asphaltzustand anpassen können. Ein weiteres Ziel ist es, die Materialeigenschaften der Fahrbahnoberfläche mittels Spektrometrie-Daten zu analysieren und abzubilden. Derzeit gibt es keine standardisierten Testdatensätze für die Evaluierung von Verfahren zur Straßenzustandsbeschreibung. Deswegen wurden alle Daten, die in dieser Studie Verwendung finden, mit einem eigens für diesen Forschungszweck konfigurierten Messfahrzeug aufgezeichnet. Das Konzept für die Detektion und Lokalisierung der wichtigsten vier Arten von Straßenschäden, nämlich Spurrillen, Schlaglöcher, Risse und Flickstellen ist das folgende: Spurrillen und Schlaglöcher werden aus Laserdaten extrahiert, Risse und Flickstellen aus RGB- Bildern. Für jede dieser Straßenschäden werden mindestens zwei Methoden entwickelt, implementiert, miteinander verglichen und evaluiert um festzustellen, welche Methode die erfolgreichste ist. Im Hinblick auf die Materialeigenschaften werden Spektrometriedaten der Straßenabschnitte klassifiziert, um die Qualität des Straßenbelages zu bewerten. Da ein Spektrometer nahezu eine kontinuierliche Reflektivitätskurve im VIS-, NIR- und SWIR-Wellenlängenbereich aufzeichnet, können Merkmale der Asphaltalterung abgeleitet werden. Nach der Detektion und Lokalisierung der Straßenschäden und der Qualitätsklasse des Straßenbelages wird der übergreifende Straßenzustand mit Hilfe von Durchschlagsregeln als Kombination aller Zustandswerte und Qualitätsklassen ermittelt. In einem vorbereitenden Schritt für die Spurrillen- und Schlaglocherkennung wird die Straßenoberfläche aus mobilen Laserscanning-Daten basierend auf einem Höhensprung-Kriterium extrahiert. Für die Untersuchung zur Spurrillen-Erkennung werden alle Scanlinien verarbeitet. Mit einem Ansatz, der auf iterativer 1D-Polynomanpassung basiert, werden Spurrillen erfolgreich erkannt. Für eine Straßenbreite von 8-10m erweist sich ein Polynom sechsten Grades als am besten geeignet. Durch 1D-Kreuzkorrelation wird die Mitte der Spurrille erkannt. Eine alternative Methode, die die lokale Krümmung des Querprofils benutzt, erweist sich als empfindlich gegenüber Form und Breite einer Spurrille und ist weniger erfolgreich. Zur Schlaglocherkennung wird der Ansatz, der auf Polynomanpassung basiert, auf zwei Dimensionen verallgemeinert. Als Alternative wird eine Methode untersucht, die auf der Geodätischen Morphologischen Rekonstruktion beruht. Bivariate Polynomanpassung führt zu Überschwingen an den Rändern der Regionen. Die Detektion mit Hilfe der Geodätischen Morphologischen Rekonstruktion ist dagegen sehr erfolgreich. Zur Risserkennung werden drei Methoden untersucht, die rotationsinvariante Kerne verwenden. Linienfilter, Hochpassfilter und Lokale Binäre Muster werden implementiert. Ein Ziel des Konzeptes zur Risserkennung ist es, eine hohe Vollständigkeit zu erreichen. Die erfolgreichste Variante ist das Linienfilter, für das mit 81,2 % der höchste Grad an Vollständigkeit erzielt werden konnte. Zwei Texturmaße, nämlich der Betrag des Grauwert-Gradienten und die lokale Standardabweichung werden verwendet, um Flickstellen zu entdecken. Da Flickstellen hinsichtlich der Homogenität variieren können und nicht immer eine dunkle Grenze mit dem intakten Straßenbelag aufweisen, ist diejenige Methode, welche die lokale Standardabweichung benutzt, besser zur Erkennung von Flickstellen geeignet. Lineare Diskriminanzanalyse wird zur Analyse der Asphaltqualität und zur Klassifikation benutzt. Straßenabschnitte von ca. 4m Länge werden zwei Klassen („Gut“ und „Schlecht“) mit einer gesamten Accuracy von 77,6 % zugeordnet. Die experimentellen Untersuchungen zeigen, dass die entwickelten Methoden für die automatische Entdeckung von Straßenschäden sehr erfolgreich sind. Durch 1D Polynomanpassung an Laser-Scanlinien werden Spurrillen entdeckt. Zusätzlich zu Spurrillen werden auch Unebenheiten des Straßenbelages wie Aufschiebungen detektiert. Die Extraktion von Schlaglöchern ist weniger anspruchsvoll. Da Schlaglöcher relativ selten in den Straßennetzen von Städten auftreten, werden die Straßenabschnitte mit Schlaglöchern interaktiv ausgewählt. Während die Rissdetektion mit Linienfiltern sehr gut funktioniert, ist die Erkennung von Flickstellen eine größere Herausforderung, da Flickstellen manchmal der intakten Straßenoberfläche sehr ähnlich sehen. Die spektrale Klassifizierung der Straßenabschnitte trägt zur Straßenzustandsbewertung bei, indem sie Hinweise auf den Alterungszustand des Straßenbelages liefert.