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Das Ziel dieser Dissertation war es zu untersuchen, ob es möglich ist, die Körperzusammensetzung von Zuchttieren bei 100 kg Körpergewicht zu einem früheren Termin bzw. bei einem niedrigeren Körpergewicht genau vorherzusagen. Dazu wurden die Tiere bei 80 kg und bei 100 kg mittels Magnetresonanztomographie (MRT) und Dualenergie-Röntgenabsorptiometrie (DXA) analysiert. Insgesamt gingen 117 Zuchttiere, darunter 22 intakte Eber und 95 Sauen in die Untersuchung ein. Jedes Tier wurde zweimal mittels MRT und DXA untersucht. Am ersten Untersuchungstermin wogen die Tiere durchschnittlich 84,5 kg, bei der zweiten Untersuchung im Durchschnitt 102 kg. In dieser Arbeit wurden verschiedene reinrassige Linien und deren Kreuzungen verwendet. Die Rassenverteilung war dabei wie folgt: Deutsche Landrasse (n = 19), Deutsches Edelschwein (n = 7), Large Black (n = 18), Schwäbisch Hällisches Landschwein (n = 3), Piétrain (n = 4), Duroc (n = 3) und ihre verschiedenen Kreuzungen (n = 63). Für die Untersuchungen wurden die Tiere mittels Azaperon (2mg/kg) und Ketamin (40mg/kg) sediert. Anschließend wurden die Tiere mittels MRT untersucht. Verwendet wurde ein Siemens Magnetom Open, mit einer Feldstärke von 0,2 Tesla. Die Lenden- sowie die Oberschenkel- und Glutealregion wurden bei jedem Schwein als Untersuchungsregionen herangezogen. Hierzu wurde eine T1-gewichtete Spinechosequenz verwendet. Die Schichtdicke betrug 15 mm und der Distanzfaktor 3,75 mm (=0,25). Für die Lendenregion wurde eine axiale Schnittrichtung verwendet, für die Oberschenkel- und Glutealregion eine coronare. Ausgewertet wurden die MR-Bilder mit Hilfe der Able 3D-Doctor 3.0 Software (Lexington, MA, USA). In der Lendenregion wurden fünf Schnittbilder in caudale Richtung, beginnend an der letzten Rippe, auf das Volumen des Musculus longissimus dorsi und dessen Speckauflage ausgewertet. Für die Oberschenkel- und Glutealregion wurde ein halbautomatisches Auswertungsverfahren gewählt, mit dem vier Schnittbilder in ventrale Richtung ausgewertet wurden, beginnend auf Höhe des Acetabulums. Für Referenzmessungen mittels Dualenergie-Röntgenabsorptiometrie (DXA) wurde ein GE Lunar DPX IQ-Scanner als quantitatives Analyseverfahren eingesetzt. Jedes Schwein wurde nach der MRT-Untersuchung mittels DXA (Modus “Ganzkörper Adult Normal”) untersucht. Die Daten wurden mittels „Proc Reg“ der Statistik-Software SAS 9.2 ausgewertet. Das Volumen des Musculus longissimus dorsi bei 80 kg zeigt eine hohe Beziehung zum Volumen des Musculus longissimus dorsi bei 100 kg (R2 = 0,86; RMSE = 82021 mm3). Bei der Gegenüberstellung der Volumina des Musculus longissimus dorsi bei 80 kg und bei 100 kg allein für die Eber ergibt sich das höchste Bestimmtheitsmaß mit R2 = 0,97 (RMSE = 35340 mm3). Ein ebenso hohes Bestimmtheitsmaß erreicht die Beziehung zwischen dem Volumen der Fettauflage (über dem Musculus longissimus dorsi) bei 80 kg und bei 100 kg allein für die Eber (R2 = 0,97, RMSE = 23757 mm3). Für die Speckauflage aller Tiere bei 80 kg und bei 100 kg resultiert ein Regressionskoeffizient von R2 = 0,91 (RMSE = 41781 mm3). Für die Oberschenkel- und Glutealregion ergeben sich geringere Beziehungen. So kann für die Muskelvolumina bei 80 kg und bei 100 kg ein Regressionskoeffizient von R2 = 0,79 (RMSE = 292079 mm3) erreicht werden. Für die entsprechenden Fettvolumina der Oberschenkel- und Glutealregion liegt das Bestimmtheitsmaß bei R2 = 0,44 (RMSE = 137143 mm3). Im Rahmen einer multiplen Regressionsanalyse kann ein Bestimmtheitsmaß von R2 = 0,82 (RMSE = 3,31 %) erreicht werden, indem das Volumen des Musculus longissimus dorsi und das Volumen der Speckauflage jeweils bei 80 kg als Variablen eingesetzt werden, um das DXA-Gesamtkörperfett (%) bei 100 kg als Referenzwert zu bestimmen. Zudem wurde eine statistische Auswertung verschiedener Einflussfaktoren anhand einer Mischmodell-Analyse mittels REML (restricted maximum likelihood) durchgeführt (p < 0,05). Die Ergebnisse zeigen, dass signifikante Rassen- bzw. Kreuzungsgruppenunterschiede bezogen auf die MRT-Muskel- und Fettvolumina in den untersuchten Regionen, sowie für die DXA-Ergebnisse vorliegen. Eher extensiv genutzte Rassen bzw. Kreuzungsgruppen weisen ein signifikant höheres MRT-Fettvolumen bei erwartungsgemäß signifikant geringem MRT-Muskelvolumen auf. Dabei weisen sie korrespondierend die geringsten DXA-Magerweichgewebewerte und die höchsten DXA-Gesamtkörperfettgehalte auf. Auffällig ist zudem, dass die weniger bemuskelten Rassen bzw. Kreuzungsgruppen über eine höhere Knochenmineraldichte verfügen. Diese Ergebnisse zeigen, dass - obwohl rassespezifische Unterschiede existieren - eine Vorhersage der Körperzusammensetzung (z.B.: DXA-Fettgehalt %) bei 100 kg durch die Untersuchung mittels MRT bei 80 kg möglich ist. Die MRT bietet die Möglichkeit Schlachtkörpermerkmale an potentiellen Zuchttieren in vivo zu erfassen, ohne auf Nachkommenschaftsergebnisse aus der Prüfschlachtung angewiesen zu sein. Somit kann die Schlachtleistung an jedem potentiellen Zuchttier selbst als Eigenleistungsprüfung erhoben werden, was die Kosten der Leistungsprüfanstalten und die für die Versuchsschlachtungen deutlich reduziert. Zudem kann aufgrund der anzunehmend hohen Heritabilitäten das Generationsintervall sowohl für den potentiellen Zuchteber als auch für die potentielle Zuchtsau deutlich reduziert werden, ohne an Genauigkeit zu verlieren.

The objective of this study was to evaluate the measurement of whole body composition by dual-energy X-ray absorptiometry (DXA) in turkeys (post mortem). In total, 130 turkeys (1.3 – 24.1 kg) of two genotypes BUT Big6 and Kelly Bronze were scanned at 4 different ages by using DXA with a LUNAR DPX-IQ densitometer. Whole body scans were performed and analyzed twice using Pediatrie Small (Reference Mode) for all animals. Additionally, Pediatric Medium, Pediatric Large, Small Animal Medium, or Small Animal Small modes were used on a smaller number of animals. DXA measurements provided readings of fat mass, lean mass, bone mineral mass, and bone mineral density. The turkeys were frozen (-18 °C) and analyzed in a plastic bag. The body weight of Big6 (15.7 kg) in week 18 is already similar to the body weight of Kelly Bronze (16.3 kg) four (4) weeks later. After week 18, the DXA FAT (%) values were smaller (week 18: 12.6; week 24: 7.7 %) but the values for DXA LEAN (%) were higher (84.8 / 89.7 %) in Big6 than in Kelly Bronze (13.3 / 11.5 or 84.4 / 85.9 % respectively). The body weight can be predicted with a high precision (R² = 1; RMSE = 21 in g) and a high accuracy (R² = 0,996; RMSE = 351 in g) by DXA. These results indicate a good suitability of DXA to estimate the carcass composition of turkeys in vivo. But the results should be validated by chemical analysis or dissection.

Abstract The shear viscosity, density, thermal expansivity and specific heat capacity are important factors controlling the morphology, rheology, and texture of volcanic flows and deposits. These physical properties of silicate melts largely depend on chemical composition, water content, crystal content, bubble content and stress applied to the melt. Recently, it has been recognized that the applied stress plays an important role in the so called “glass transition” area of silicate melts. This kinetic boundary between brittle and ductile behavior affects the eruptive style. Thorough knowledge of the physical processes that occur at this brittle/ductile transition can affect the decision making of governments during volcanic crises and help to reduce and/or avoid loss of life and assets. Scientific knowledge from this research can be directly applied to the geomaterial industry. In addition, natural magmatic rocks are the major raw material in the production of microfibres and continuous fibres. Compared to normal glass fibres, rock fibres have a remarkable high temperature endurance, acid and alkali resistance and anti-heat impact. Rock products can be used as substitutes for metal and timber. They are likely to become more widely used in the near future. Further use for natural magmatic rocks include crushed stone, concrete aggregate, railroad ballast, production of high quality textile fibres, floor tiles, acid-resistant equipment for heavy industrial use, rockwool, basalt pipers, basalt reinforcement bars, basalt fibre roofing felt (ruberoid), basalt laminate (used as a protective coating), heat-insulating basalt fibre materials and glass wool (fibre glass). Since Bottinga and Weill (1970) first suggested that the density of melts in two or three component systems could be used to determine partial molar volumes of oxide components in silicate liquids, several models based upon this approach have been proposed in the Earth sciences literature. Considering that knowledge the densities of 8 Zn-bearing silicate melts have been determined, in equilibrium with air, in the temperature range of 1363 to 1850 K. The compositional joins investigated [sodium disilicate (NS2)- ZnO; anorthite-diopside 1 atm eutectic (AnDi)-ZnO; and diopside-petedunnite] were chosen based on the pre-existing experimental density data set, on their petrological relevance, and in order to provide a test for significant compositionally induced variations in the structural role of ZnO. The ZnO concentrations investigated range up to 25 mol% for sodium disilicate, 20 mol% for the anorthite-diopside 1 atm eutectic, and 25 mol% for petedunnite. Molar volumes and expansivities have been derived for all melts. The molar volumes of the liquids decrease with increasing ZnO content. The partial molar volume of ZnO derived from the volumetric measurements for each binary system is the same within error. A multicomponent fit to the volumetric data for all compositions yields a value of 13.59(0.55) cm3/mol at 1500 K. I find, no volumetric evidence for compositionally induced coordination number variations for ZnO in alkali-bearing vs. alkali-free silicate melts nor for Al-free vs. Al-bearing silicate melts. The partial molar volume of ZnO determined here may be incorporated into existing multicomponent models for the prediction of silicate melt volume. High temperature density determinations on ZnO-bearing silicate melts indicate that a single value for the partial molar volume of ZnO is sufficient to describe the volumetric properties of this component in silicate melts. The presence of alkalies and Al does not appear to influence the partial molar volume of ZnO within the temperature range investigated here. There is no volumetric evidence across this temperature range presented for composition to influence the coordination polyhedron of ZnO in silicate melts. The next physical property to be studied was thermal expansivity. Ten compositions from within the anorthite-wollastonite-gehlenite (An-Wo-Geh) compatibility triangle were investigated. Due to the lack of information about the thermal expansivities at supercooled liquid temperatures this study focused on the measurement of thermal expansivity using a combination of calorimetric and dilatometric methods. The volumes at room temperature were derived from densities measured using the Archimedean buoyancy method. For each sample density was measured at 298 K using glass that had a cooling-heating history of 10-10 K min-1. The thermal expansion coefficient of the glass from 298 K to the glass transition interval was measured by a dilatometer and the heat capacity was measured using a differential scanning calorimeter from 298 to 1135 K. The thermal expansion coefficient and the heat flow were determined at a heating rate of 10 K min-1 on glasses that were previously cooled at 10 K min-1. Supercooled liquid density, molar volume and molar thermal expansivities were indirectly determined by combining differential scanning calorimetric and dilatometric measurements assuming that the kinetics of enthalpy and shear relaxation are equivalent. The data obtained on the supercooled liquids were compared to high-temperature predictions from the models of Lange and Carmichael (1987), Courtial and Dingwell (1995) and Lange (1997). The best linear fit combines the supercooled liquid data presented in this study and the high temperature data calculated using the Courtial and Dingwell (1995) model. This dilatometric/calorimetric method of determining supercooled liquid molar thermal expansivity greatly increases the temperature range accessible for thermal expansion. It represents a substantial increase in precision and understanding of the thermodynamics of calcium aluminosilicate melts. This enhanced precision demonstrates clearly the temperature independence of the melt expansions in the An-Wo-Geh system. This contrasts strongly with observations for neighboring system such as Anorthite-Diopside and raises the question of the compositional/structural origins of the temperature dependence of thermal expansivity in multicomponent silicate melts. In addition, the partial molar volumes and the thermal expansivities of 10 samples from within the An-Wo-Geh compatibility triangle have been determined. They have been incorporated into existing multicomponent models in order to predict silicate melt volume. The resulting supercooled liquid volumes near glass transition temperatures (1135 - 1200 K) and at superliquidus temperature were combined to yield temperature independent thermal expansivities over the entire temperature range. In light of results presented in this study, together with the published data, it seems that binary and ternary systems have temperature independent thermal expansivities from the supercooled liquid to the superliquidus temperature at 1 atmosphere. By combining the high temperature densitometry data (i.e., above liquidus) from the literature with volume and expansivity data obtained at Tsc, a wide temperature range is covered. There is no volumetric evidence across this temperature range for temperature independent thermal expansivities in the An-Wo-Geh compatibility triangle. Furthemore, the thermal expansivities of three multicomponent glasses and liquids have been obtained over a large temperature interval (298 - 1803 K) which involved combining the results of low and high temperature measurements. The sample compositions investigated were derived from three natural lavas; Vesuvius 1631 eruption, Etna 1992 eruption and an Oligocene-Miocene lava flow from Slapany in the Bohemian massif. The original rocks are tephri-phonolite, trachybasalt and basanite, respectively. This is the first time this calorimetric/dilatometric method has ever been applied to natural magmatic melts. The low temperature volumes were derived from measurements of the glass density of each sample after cooling at 5 K.min-1 at 298 K, followed by measurements of the glass thermal expansion coefficient from 298 K to the samples´ respective glass transition interval. Supercooled liquid volumes and molar thermal expansivities were determined by combining scanning calorimetric and dilatometric measurements, assuming that the kinetics of enthalpy and shear relaxation are equivalent (Webb, 1992). High temperature densities were measured using Pt double bob Archimedean densitometry. In addition, the oxidation state of iron was analyzed using a wet chemistry method. Small amounts of samples were taken from the liquids using a “dip” technique at regular temperature steps during high temperature densitometry. The measured high temperature densities have been compared with predicted densities across the same temperature interval calculated using the multicomponent density models of Lange and Carmichael (1987) and Lange (1997). The resulting data for liquid volumes near glass transition temperatures (993 - 1010 K) and at super-liquidus temperatures (1512 - 1803 K) are combined to yield temperature dependant thermal expansivities over the entire supercooled and stable liquid range. These results confirm the observation of Knoche et al. (1992a); Knoche et al. (1992b); Toplis and Richet (2000); Liu and Lange (2001); Gottsmann and Dingwell (2002) of the temperature dependence of thermal expansivity. The molar volumes indicate, in general, a significant negative temperature dependence of the expansivity. The thermal molar expansivity of the glasses increase from SiO2-poor (basalt-basanite composition) to relatively SiO2-rich melts (tephri-phonolite composition). The thermal molar expansivity at supercooled liquid temperatures increases in the same manner as the glasses. In contrast, the thermal molar expansivity of the superliquidus liquid decrease from SiO2-poor to relatively SiO2-rich melts. Non-linear dependency of molar volume has been observed for all studied samples above the glass transition area. Molar volume from just above the glass transition area to about 1873 K can be predicted by a non-linear logarithmic curve. This study examined the expansivities and molar volumes of relatively basic compositions. Extending such a study to more SiO2-rich, but still geologically relevant, compositions remains a challenge, because the high viscosities of such melts preclude the use of immersion techniques. This problem can be solved using a high temperature densitometry where the volume is measured on levitated sample. I would like to urge studies of this sort in the future. Results from such studies should provide important information regarding a number of geological processes, which occur in such extremely high viscous liquids. A new viscosity measurement for melts spanning a wide range of anhydrous compositions including: rhyolite, trachyte, moldavite, andesite, latite, pantellerite, basalt and basanite are discussed in the last chapters. Micropenetration and concentric cylinder viscometry measurements cover a viscosity range of 10-1 to 1012 Pas and a temperature range from 973 to 1923 K. These new measurements, combined with other published data, provide a high-quality database comprising ~800 experimental data on 44 well -characterized melt compositions. This database is used to recalibrate the model proposed by Giordano and Dingwell [Giordano, D., Dingwell, D. B., 2003a. Non-Arrhenian multicomponent melt viscosity: a model. Earth Planet. Sci. Lett. 208, 337–349] for predicting the viscosity of natural silicate melts. The recalibration shows that: a) the viscosity (η)–temperature relationship of natural silicate liquids is very well represented by the VFT equation [log η=A+B/ (T−C)] over the full range of viscosity considered here, b) the use of a constant high-T limiting value of melt viscosity (e.g., A) is fully consistent with the experimental data. There are 3 different compositional suites (peralkaline, metaluminous and peraluminous) that exhibit different patterns in viscosity, the viscosity of metaluminous liquids is well described by a simple mathematical expression involving the compositional parameter (SM) but the compositional dependence of viscosity for peralkaline and peraluminous melts is not fully controlled by SM. For these extreme compositions we refitted the model using a temperature-dependent parameter based on the excess of alkalies relative to alumina (e.g., AE/SM). The recalibrated model reproduces the entire database to within 5% relative error. On the basis of this extended database the T-variation of the viscous response of strong and fragile liquids within a wide range of compositions shows three clearly contrasting compositional suites (peralkaline, metaluminous and peraluminous). As a result, I present an extended model to calculate the viscosity of silicate melts over a wide range of temperatures and compositions. This model constitutes a significant improvement with respect to the Giordano and Dingwell (2003a) study in that: 1) The number of experimental determinations over which the model is calibrated is larger. 2) The range of investigated compositions is larger. 3) The investigated temperature range is larger. 4) The assumption is made that at infinite temperature, the viscosity of silicate melts converges to a common, but unknown value of the pre-exponential factor (A=−4.07, Equation (7.1)). In particular the compositional range involves a large number of viscosity determinations for peralkaline and peraluminous compositions in a temperature interval between 949 and 2653 K. Furthermore, it is shown that the assumption of a common value of the pre-exponential parameter A produces an equally good representation of the experimental data as that produced by each melt having its own specific A-value. This optimization also induces a strong coupling between data sets that stabilizes the range of solutions and allows the different rheological behaviour of extreme compositions (peralkaline and peraluminous vs. metaluminous) to be discriminated. It was demonstrated that, although the parameter SM (Giordano and Dingwell, 2003a) can be used to model compositional controls on the viscosities of metaluminous liquids, it does not capture the viscosity of peralkaline and peraluminous liquids. The differences in the rheological behaviour of these extreme compositions reflect important differences in the structural configuration of metaluminous, peralkaline and peraluminous melts. Subsequently, a second regression of the experimental data was performed involving a second compositional parameter (AE) that accounts for the excess of alkali oxides over the alumina. Incorporating this temperature-dependent compositional parameter (i.e., AE) into the SM-based model (Equation 7.7) appears to account for the anomalous rheological behaviour of peralkaline and peraluminous liquids. The resulting model reproduces the entire experimental database to within an average RMSE of 0.45 log units. The model presented here is recommended for the estimation of the viscosity of anhydrous multicomponent silicate melts of volcanic interest.