910 resultados para Multiscale Texture
Resumo:
Transport of live aquatic organisms which is more than a century old, perhaps started in the 1870's (Norris et al, 1960). Live fish transportation is an essential practice in aquaculture particularly in rural areas of developing countries representing the only means of supplying fry to small scale aqua culturists (Taylor and Ross, 1988). Very often, large numbers of fry, fingerlings, juveniles and adult fish are being transported from the hatchery to fish farms, fish farms to market, processors and consumers. Live fish command large economic importance in the fresh fish market than dead and iced fish. Medina Pizzali (2001) observed that live fish in the Kolkata market was usually sold at higher prices than dead fish and most consumers were prepared to pay premium prices for live fish, which is considered as the best guarantee of freshness, quality, and intrinsic characteristics of its flesh (better texture and delicate flavour) in comparison with fresh/chilled seafood. Various government and private agencies undertake transport of live fish for commercial live fish market or for artificial propagation of game
Resumo:
Landwirtschaft spielt eine zentrale Rolle im Erdsystem. Sie trägt durch die Emission von CO2, CH4 und N2O zum Treibhauseffekt bei, kann Bodendegradation und Eutrophierung verursachen, regionale Wasserkreisläufe verändern und wird außerdem stark vom Klimawandel betroffen sein. Da all diese Prozesse durch die zugrunde liegenden Nährstoff- und Wasserflüsse eng miteinander verknüpft sind, sollten sie in einem konsistenten Modellansatz betrachtet werden. Dennoch haben Datenmangel und ungenügendes Prozessverständnis dies bis vor kurzem auf der globalen Skala verhindert. In dieser Arbeit wird die erste Version eines solchen konsistenten globalen Modellansatzes präsentiert, wobei der Schwerpunkt auf der Simulation landwirtschaftlicher Erträge und den resultierenden N2O-Emissionen liegt. Der Grund für diese Schwerpunktsetzung liegt darin, dass die korrekte Abbildung des Pflanzenwachstums eine essentielle Voraussetzung für die Simulation aller anderen Prozesse ist. Des weiteren sind aktuelle und potentielle landwirtschaftliche Erträge wichtige treibende Kräfte für Landnutzungsänderungen und werden stark vom Klimawandel betroffen sein. Den zweiten Schwerpunkt bildet die Abschätzung landwirtschaftlicher N2O-Emissionen, da bislang kein prozessbasiertes N2O-Modell auf der globalen Skala eingesetzt wurde. Als Grundlage für die globale Modellierung wurde das bestehende Agrarökosystemmodell Daycent gewählt. Neben der Schaffung der Simulationsumgebung wurden zunächst die benötigten globalen Datensätze für Bodenparameter, Klima und landwirtschaftliche Bewirtschaftung zusammengestellt. Da für Pflanzzeitpunkte bislang keine globale Datenbasis zur Verfügung steht, und diese sich mit dem Klimawandel ändern werden, wurde eine Routine zur Berechnung von Pflanzzeitpunkten entwickelt. Die Ergebnisse zeigen eine gute Übereinstimmung mit Anbaukalendern der FAO, die für einige Feldfrüchte und Länder verfügbar sind. Danach wurde das Daycent-Modell für die Ertragsberechnung von Weizen, Reis, Mais, Soja, Hirse, Hülsenfrüchten, Kartoffel, Cassava und Baumwolle parametrisiert und kalibriert. Die Simulationsergebnisse zeigen, dass Daycent die wichtigsten Klima-, Boden- und Bewirtschaftungseffekte auf die Ertragsbildung korrekt abbildet. Berechnete Länderdurchschnitte stimmen gut mit Daten der FAO überein (R2 = 0.66 für Weizen, Reis und Mais; R2 = 0.32 für Soja), und räumliche Ertragsmuster entsprechen weitgehend der beobachteten Verteilung von Feldfrüchten und subnationalen Statistiken. Vor der Modellierung landwirtschaftlicher N2O-Emissionen mit dem Daycent-Modell stand eine statistische Analyse von N2O-und NO-Emissionsmessungen aus natürlichen und landwirtschaftlichen Ökosystemen. Die als signifikant identifizierten Parameter für N2O (Düngemenge, Bodenkohlenstoffgehalt, Boden-pH, Textur, Feldfrucht, Düngersorte) und NO (Düngemenge, Bodenstickstoffgehalt, Klima) entsprechen weitgehend den Ergebnissen einer früheren Analyse. Für Emissionen aus Böden unter natürlicher Vegetation, für die es bislang keine solche statistische Untersuchung gab, haben Bodenkohlenstoffgehalt, Boden-pH, Lagerungsdichte, Drainierung und Vegetationstyp einen signifikanten Einfluss auf die N2O-Emissionen, während NO-Emissionen signifikant von Bodenkohlenstoffgehalt und Vegetationstyp abhängen. Basierend auf den daraus entwickelten statistischen Modellen betragen die globalen Emissionen aus Ackerböden 3.3 Tg N/y für N2O, und 1.4 Tg N/y für NO. Solche statistischen Modelle sind nützlich, um Abschätzungen und Unsicherheitsbereiche von N2O- und NO-Emissionen basierend auf einer Vielzahl von Messungen zu berechnen. Die Dynamik des Bodenstickstoffs, insbesondere beeinflusst durch Pflanzenwachstum, Klimawandel und Landnutzungsänderung, kann allerdings nur durch die Anwendung von prozessorientierten Modellen berücksichtigt werden. Zur Modellierung von N2O-Emissionen mit dem Daycent-Modell wurde zunächst dessen Spurengasmodul durch eine detailliertere Berechnung von Nitrifikation und Denitrifikation und die Berücksichtigung von Frost-Auftau-Emissionen weiterentwickelt. Diese überarbeitete Modellversion wurde dann an N2O-Emissionsmessungen unter verschiedenen Klimaten und Feldfrüchten getestet. Sowohl die Dynamik als auch die Gesamtsummen der N2O-Emissionen werden befriedigend abgebildet, wobei die Modelleffizienz für monatliche Mittelwerte zwischen 0.1 und 0.66 für die meisten Standorte liegt. Basierend auf der überarbeiteten Modellversion wurden die N2O-Emissionen für die zuvor parametrisierten Feldfrüchte berechnet. Emissionsraten und feldfruchtspezifische Unterschiede stimmen weitgehend mit Literaturangaben überein. Düngemittelinduzierte Emissionen, die momentan vom IPCC mit 1.25 +/- 1% der eingesetzten Düngemenge abgeschätzt werden, reichen von 0.77% (Reis) bis 2.76% (Mais). Die Summe der berechneten Emissionen aus landwirtschaftlichen Böden beträgt für die Mitte der 1990er Jahre 2.1 Tg N2O-N/y, was mit den Abschätzungen aus anderen Studien übereinstimmt.
Resumo:
Soil organic matter (SOM) vitally impacts all soil functions and plays a key role in the global carbon (C) cycle. More than 70% of the terrestric C stocks that participate in the active C cycle are stored in the soil. Therefore, quantitative knowledge of the rates of C incorporation into SOM fractions of different residence time is crucial to understand and predict the sequestration and stabilization of soil organic carbon (SOC). Consequently, there is a need of fractionation procedures that are capable of isolating functionally SOM fractions, i.e. fractions that are defined by their stability. The literature generally refers to three main mechanisms of SOM stabilization: protection of SOM from decomposition by (i) its structural composition, i.e. recalcitrance, (ii) spatial inaccessibility and/or (iii) interaction with soil minerals and metal ions. One of the difficulties in developing fractionation procedures for the isolation of functional SOM fractions is the marked heterogeneity of the soil environment with its various stabilization mechanisms – often several mechanisms operating simultaneously – in soils and soil horizons of different texture and mineralogy. The overall objective of the present thesis was to evaluate present fractionation techniques and to get a better understanding of the factors of SOM sequestration and stabilization. The first part of this study is attended to the structural composition of SOM. Using 13C cross-polarization magic-angle spinning (CPMAS) nuclear magnetic resonance (NMR) spectroscopy, (i) the effect of land use on SOM composition was investigated and (ii) examined whether SOM composition contributes to the different stability of SOM in density and aggregate fractions. The second part of the present work deals with the mineral-associated SOM fraction. The aim was (iii) to evaluate the suitability of chemical fractionation procedures used in the literature for the isolation of stable SOM pools (stepwise hydrolysis, treatments using oxidizing agents like Na2S2O8, H2O2, and NaOCl as well as demineralization of the residue obtained by the NaOCl treatment using HF (NaOCl+HF)) by pool sizes, 13C and 14C data. Further, (iv) the isolated SOM fractions were compared to the inert organic matter (IOM) pool obtained for the investigated soils using the Rothamsted Carbon Model and isotope data in order to see whether the tested chemical fractionation methods produce SOM fractions capable to represent this pool. Besides chemical fractionation, (v) the suitability of thermal oxidation at different temperatures for obtaining stable SOC pools was evaluated. Finally, (vi) the short-term aggregate dynamics and the factors that impact macroaggregate formation and C stabilization were investigated by means of an incubation study using treatments with and without application of 15N labeled maize straw of different degradability (leaves and coarse roots). All treatments were conducted with and without the addition of fungicide. Two study sites with different soil properties and land managements were chosen for these investigations. The first one, located at Rotthalmünster, is a Stagnic Luvisol (silty loam) under different land use regimes. The Ah horizons of a spruce forest and continuous grassland and the Ap and E horizons of two plots with arable crops (continuous maize and wheat cropping) were examined. The soil of the second study site, located at Halle, is a Haplic Phaeozem (loamy sand) where the Ap horizons of two plots with arable crops (continuous maize and rye cropping) were investigated. Both study sites had a C3-/C4-vegetational change on the maize plot for the purpose of tracing the incorporation of the younger, maize-derived C into different SOM fractions and the calculation of apparent C turnover times of these. The Halle site is located near a train station and industrial areas, which caused a contamination with high amounts of fossil C. The investigation of aggregate and density fractions by 13C CPMAS NMR spectroscopy revealed that density fractionation isolated SOM fractions of different composition. The consumption of a considerable part (10–20%) of the easily available O-alkyl-C and the selective preservation of the more recalcitrant alkyl-C when passing from litter to the different particulate organic matter (POM) fractions suggest that density fractionation was able to isolate SOM fractions with different degrees of decomposition. The spectra of the aggregate fractions resembled those of the mineral-associated SOM fraction obtained by density fractionation and no considerable differences were observed between aggregate size classes. Comparison of plant litter, density and aggregate size fractions from soil under different land use showed that the type of land use markedly influenced the composition of SOM. While SOM of the acid forest soil was characterized by a large content (> 50%) of POM, which contained high amounts of spruce-litter derived alkyl-C, the organic matter in the biologically more active grassland and arable soils was dominated by mineral-associated SOM (> 95%). This SOM fraction comprised greater proportions of aryl- and carbonyl-C and is considered to contain a higher amount of microbially-derived organic substances. Land use can alter both, structure and stability of SOM fractions. All applied chemical treatments induced considerable SOC losses (> 70–95% of mineral-associated SOM) in the investigated soils. The proportion of residual C after chemical fractionation was largest in the arable Ap and E horizons and increased with decreasing C content in the initial SOC after stepwise hydrolysis as well as after the oxidative treatments with H2O2 and Na2S2O8. This can be expected for a functional stable pool of SOM, because it is assumed that the more easily available part of SOC is consumed first if C inputs decrease. All chemical treatments led to a preferential loss of the younger, maize-derived SOC, but this was most pronounced after the treatments with Na2S2O8 and H2O2. After all chemical fractionations, the mean 14C ages of SOC were higher than in the mineral-associated SOM fraction for both study sites and increased in the order: NaOCl < NaOCl+HF ≤ stepwise hydrolysis << H2O2 ≈ Na2S2O8. The results suggest that all treatments were capable of isolating a more stable SOM fraction, but the treatments with H2O2 and Na2S2O8 were the most efficient ones. However, none of the chemical fractionation methods was able to fit the IOM pool calculated using the Rothamsted Carbon Model and isotope data. In the evaluation of thermal oxidation for obtaining stable C fractions, SOC losses increased with temperature from 24–48% (200°C) to 100% (500°C). In the Halle maize Ap horizon, losses of the young, maize-derived C were considerably higher than losses of the older C3-derived C, leading to an increase in the apparent C turnover time from 220 years in mineral-associated SOC to 1158 years after thermal oxidation at 300°C. Most likely, the preferential loss of maize-derived C in the Halle soil was caused by the presence of the high amounts of fossil C mentioned above, which make up a relatively large thermally stable C3-C pool in this soil. This agrees with lower overall SOC losses for the Halle Ap horizon compared to the Rotthalmünster Ap horizon. In the Rotthalmünster soil only slightly more maize-derived than C3-derived SOC was removed by thermal oxidation. Apparent C turnover times increased slightly from 58 years in mineral-associated SOC to 77 years after thermal oxidation at 300°C in the Rotthalmünster Ap and from 151 to 247 years in the Rotthalmünster E horizon. This led to the conclusion that thermal oxidation of SOM was not capable of isolating SOM fractions of considerably higher stability. The incubation experiment showed that macroaggregates develop rapidly after the addition of easily available plant residues. Within the first four weeks of incubation, the maximum aggregation was reached in all treatments without addition of fungicide. The formation of water-stable macroaggregates was related to the size of the microbial biomass pool and its activity. Furthermore, fungi were found to be crucial for the development of soil macroaggregates as the formation of water-stable macroaggregates was significantly delayed in the fungicide treated soils. The C concentration in the obtained aggregate fractions decreased with decreasing aggregate size class, which is in line with the aggregate hierarchy postulated by several authors for soils with SOM as the major binding agent. Macroaggregation involved incorporation of large amounts maize-derived organic matter, but macroaggregates did not play the most important role in the stabilization of maize-derived SOM, because of their relatively low amount (less than 10% of the soil mass). Furthermore, the maize-derived organic matter was quickly incorporated into all aggregate size classes. The microaggregate fraction stored the largest quantities of maize-derived C and N – up to 70% of the residual maize-C and -N were stored in this fraction.
Resumo:
Die Qualität ökologischer Produkte wird über den Prozess und nicht am Produkt selbst bestimmt. Die zunehmende Nachfrage nach ökologischen Produkten fordert Methoden, die den Prozess am Produkt zeigen (Authentizitätsprüfung). Eine Literaturstudie für die vorliegende Habilitationsschrift ergab, dass ganzheitliche Verfahren sich dazu besonders eignen. Zu solchen ganzheitlichen Verfahren gehört die Biokristallisation. Bei diesem Verfahren kristallisiert eine Mischung aus Probe und CuCl2 auf einer Glasplatte zu einem Bild, das sowohl visuell, als auch computergestützt ausgewertet werden kann. Es wurden zunächst alle Schritte im Labor dokumentiert und entsprechende Standardarbeitsanweisungen erstellt. Mit einem eigens entwickelten Computerprogramm werden die Bedingungen während der Probenaufbereitung und Kristallisation für jede Probe und jedes Bild erfasst. Mit einer Texturanalyse können auch die für diese Arbeiten erstellte große Menge an Bildern ausgewertet und die Ergebnisse statistisch bearbeitet werden. Damit ist es möglich das Verfahren und Methoden für Weizen- und Möhrenproben zu charakterisieren. Es wurden verschiedene Einflussgrößen untersucht. Das Verfahren ist besonders gegenüber Änderungen in der Probenvorbereitung (z.B. Vermahlung, Mischungsverhältnis) empfindlich. Es wurde sowohl die Methodenstreuung, als auch der Anteil einzelner Schritte an der Gesamtstreuung für Weizen-, Möhren- und Apfelproben ermittelt. Die Verdampfung und Kristallisation hat den größten Anteil an der Gesamtstreuung. Die Durchführung eines Laboreignungstests zeigte, dass die so dokumentierten und charakterisierten Methoden in anderen Laboratorien erfolgreich eingesetzt werden können. Das Verfahren wurde für die nominale Unterscheidung von Weizen-, Möhren- und Apfelproben aus unterschiedlichem Anbau und Verarbeitungsschritten eingesetzt. Weizen-, Möhren- und Apfelproben aus definiertem Anbau können signifikant unterschieden werden. Weizen-, Möhren- und Apfelproben vom Erzeuger (Markt) konnten im Paarvergleich (ökologisch, konventionell) teilweise signifikant getrennt werden. Das Verfahren ist auch für die Charakterisierung von verarbeiteten Proben einsetzbar. Es konnte der Einfluss von Saftherstellung, Erwärmung und Alterung signifikant gezeigt werden. Darüber hinaus lässt sich das Verfahren auf weitere Probenarten anwenden. Das Verfahren arbeitet ganzheitlich, d.h. es werden keine Einzelstoffe analytisch bestimmt, sondern als Ergebnis wird ein Bild erhalten. Die Textur- und Struktureigenschaften dieses Bildes können mit standardisierten Methoden ausgewertet werden.
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Zur Abbildung heterogener Standorteigenschaften und Ertragspotenziale werden zunehmend flächenhafte Daten nachgefragt. Insbesondere für Grünland, das häufig durch ausgeprägte Standortheterogenität gekennzeichnet ist, ergeben sich hohe Anforderungen an die Wiedergabequalität, denn die realen Verhältnisse sollen in praktikabler Weise möglichst exakt abgebildet werden. Außerdem können flächenhafte Daten genutzt werden, um Zusammenhänge zwischen teilflächenspezifischen Standorteigenschaften und Grünlandaspekten detaillierter zu analysieren und bisher nicht erkannte Wechselbeziehungen nachzuweisen. Für mitteleuropäisches Grünland lagen zu Beginn dieser Arbeit derartige räumliche Untersuchungen nicht oder nur in Teilaspekten vor. Diese Arbeit befasste sich mit der Analyse von Wirkungsbeziehungen zwischen Standort- und Grünlandmerkmalen auf einer im Nordhessischen Hügelland (Deutschland) weitgehend praxisüblicher bewirtschafteten 20 ha großen Weidefläche. Erhoben wurden als Standortfaktoren die Geländemorphologie, die Bodentextur, die Grundnährstoffgehalten sowie als Parameter des Grünlandbestandes die botanische Zusammensetzung, der Ertrag und die Qualitätsparameter. Sie wurden sowohl in einem 50 m-Raster ganzflächig, als auch auf drei 50x50 m großen Teilflächen in erhöhter Beprobungsdichte (6,25 m-Rasterweite) aufgenommen. Die relevanten Fragestellungen zielen auf die räumliche und zeitliche Variabilität von Grünlandbestandesparametern innerhalb von Grünlandflächen sowie deren Abhängigkeit von den Standortfaktoren. Ein weiterer Schwerpunkt war die Überprüfung der Frage, ob die reale Variabilität der Zielvariablen durch die Interpolierung der punktuell erfassten Daten wiedergegeben werden kann. Die Beziehungen zwischen Standort- und Grünlandmerkmalen wurden mit monokausalen und multivariaten Ansätzen untersucht. Die Ergebnisse ließen, unabhängig vom Jahreseinfluss, bereits bestimmte Zusammenhänge zwischen botanischer Zusammensetzung und Standort, auch auf dem untersuchten kleinen Maßstab innerhalb der Grünlandfläche, finden. Demzufolge können unterschiedliche Areale abgegrenzt und charakterisiert werden, die als Grundlage für Empfehlungen zur Ausweisung von Arealen zur teilspezifischen Bewirtschaftung erarbeitet wurden. Die Validierung der interpolierten Daten zeigte, dass die 50-m Rasterbeprobung nur eine begrenzte Wiedergabe der räumlichen Variabilität ermöglicht. Inwieweit derartige Beziehungen quantitativ genauer beschreibbar sind, bleibt auf Grund der verbliebenen unerklärten Varianz im Datensatz dieser Studie offen.
Resumo:
The use of renewable primary products as co-substrate or single substrate for biogas production has increased consistently over the last few years. Maize silage is the preferential energy crop used for fermentation due to its high methane (CH4) yield per hectare. Equally, the by-product, namely biogas slurry (BS), is used with increasing frequency as organic fertilizer to return nutrients to the soil and to maintain or increase the organic matter stocks and soil fertility. Studies concerning the application of energy crop-derived BS on the carbon (C) and nitrogen (N) mineralization dynamics are scarce. Thus, this thesis focused on the following objectives: I) The determination of the effects caused by rainfall patterns on the C and N dynamics from two contrasting organic fertilizers, namely BS from maize silage and composted cattle manure (CM), by monitoring emissions of nitrous oxide (N2O), carbon dioxide (CO2) and CH4 as well as leaching losses of C and N. II) The investigation of the impact of differences in soil moisture content after the application of BS and temperature on gaseous emissions (CO2, N2O and CH4) and leaching of C and N compounds. III) A comparison of BS properties obtained from biogas plants with different substrate inputs and operating parameters and their effect on C and N dynamics after application to differently textured soils with varying application rates and water contents. For the objectives I) and II) two experiments (experiment I and II) using undisturbed soil cores of a Haplic Luvisol were carried out. Objective III) was studied on a third experiment (experiment III) with disturbed soil samples. During experiment I three rainfall patterns were implemented including constant irrigation, continuous irrigation with periodic heavy rainfall events, and partial drying with rewetting periods. Biogas slurry and CM were applied at a rate of 100 kg N ha-1. During experiment II constant irrigation and an irrigation pattern with partial drying with rewetting periods were carried out at 13.5°C and 23.5°C. The application of BS took place either directly before a rewetting period or one week after the rewetting period stopped. Experiment III included two soils of different texture which were mixed with ten BS’s originating from ten different biogas plants. Treatments included low, medium and high BS-N application rates and water contents ranging from 50% to 100% of water holding capacity (WHC). Experiment I and II showed that after the application of BS cumulative N2O emissions were 4 times (162 mg N2O-N m-2) higher compared to the application of CM caused by a higher content of mineral N (Nmin) in the form of ammonium (NH4+) in the BS. The cumulative emissions of CO2, however, were on the same level for both fertilizers indicating similar amounts of readily available C after composting and fermentation of organic material. Leaching losses occurred predominantly in the mineral form of nitrate (NO3-) and were higher in BS amended soils (9 mg NO3--N m-2) compared to CM amended soils (5 mg NO3--N m-2). The rainfall pattern in experiment I and II merely affected the temporal production of C and N emissions resulting in reduced CO2 and enhanced N2O emissions during stronger irrigation events, but showed no effect on the cumulative emissions. Overall, a significant increase of CH4 consumption under inconstant irrigation was found. The time of fertilization had no effect on the overall C and N dynamics. Increasing temperature from 13.5°C to 23.5°C enhanced the CO2 and N2O emissions by a factor of 1.7 and 3.7, respectively. Due to the increased microbial activity with increasing temperature soil respiration was enhanced. This led to decreasing oxygen (O2) contents which in turn promoted denitrification in soil due to the extension of anaerobic microsites. Leaching losses of NO3- were also significantly affected by increasing temperature whereas the consumption of CH4 was not affected. The third experiment showed that the input materials of biogas plants affected the properties of the resulting BS. In particular the contents of DM and NH4+ were determined by the amount of added plant biomass and excrement-based biomass, respectively. Correlations between BS properties and CO2 or N2O emissions were not detected. Solely the ammonia (NH3) emissions showed a positive correlation with NH4+ content in BS as well as a negative correlation with the total C (Ct) content. The BS-N application rates affected the relative CO2 emissions (% of C supplied with BS) when applied to silty soil as well as the relative N2O emissions (% of N supplied with BS) when applied to sandy soil. The impacts on the C and N dynamics induced by BS application were exceeded by the differences induced by soil texture. Presumably, due to the higher clay content in silty soils, organic matter was stabilized by organo-mineral interactions and NH4+ was adsorbed at the cation exchange sites. Different water contents induced highest CO2 emissions and therefore optimal conditions for microbial activity at 75% of WHC in both soils. Cumulative nitrification was also highest at 75% and 50% of WHC whereas the relative N2O emissions increased with water content and showed higher N2O losses in sandy soils. In summary it can be stated that the findings of the present thesis confirmed the high fertilizer value of BS’s, caused by high concentrations of NH4+ and labile organic compounds such as readily available carbon. These attributes of BS’s are to a great extent independent of the input materials of biogas plants. However, considerably gaseous and leaching losses of N may occur especially at high moisture contents. The emissions of N2O after field application corresponded with those of animal slurries.
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An improved understanding of soil organic carbon (Corg) dynamics in interaction with the mechanisms of soil structure formation is important in terms of sustainable agriculture and reduction of environmental costs of agricultural ecosystems. However, information on physical and chemical processes influencing formation and stabilization of water stable aggregates in association with Corg sequestration is scarce. Long term soil experiments are important in evaluating open questions about management induced effects on soil Corg dynamics in interaction with soil structure formation. The objectives of the present thesis were: (i) to determine the long term impacts of different tillage treatments on the interaction between macro aggregation (>250 µm) and light fraction (LF) distribution and on C sequestration in plots differing in soil texture and climatic conditions. (ii) to determine the impact of different tillage treatments on temporal changes in the size distribution of water stable aggregates and on macro aggregate turnover. (iii) to evaluate the macro aggregate rebuilding in soils with varying initial Corg contents, organic matter (OM) amendments and clay contents in a short term incubation experiment. Soil samples were taken in 0-5 cm, 5-25 cm and 25-40 cm depth from up to four commercially used fields located in arable loess regions of eastern and southern Germany after 18-25 years of different tillage treatments with almost identical experimental setups per site. At each site, one large field with spatially homogenous soil properties was divided into three plots. One of the following three tillage treatments was carried in each plot: (i) Conventional tillage (CT) with annual mouldboard ploughing to 25-30 cm (ii) mulch tillage (MT) with a cultivator or disc harrow 10-15 cm deep, and (iii) no tillage (NT) with direct drilling. The crop rotation at each site consisted of sugar beet (Beta vulgaris L.) - winter wheat (Triticum aestivum L.) - winter wheat. Crop residues were left on the field and crop management was carried out following the regional standards of agricultural practice. To investigate the above mentioned research objectives, three experiments were conducted: Experiment (i) was performed with soils sampled from four sites in April 2010 (wheat stand). Experiment (ii) was conducted with soils sampled from three sites in April 2010, September 2011 (after harvest or sugar beet stand), November 2011 (after tillage) and April 2012 (bare soil or wheat stand). An incubation study (experiment (iii)) was performed with soil sampled from one site in April 2010. Based on the aforementioned research objectives and experiments the main findings were: (i) Consistent results were found between the four long term tillage fields, varying in texture and climatic conditions. Correlation analysis of the yields of macro aggregate against the yields of free LF ( ≤1.8 g cm-3) and occluded LF, respectively, suggested that the effective litter translocation in higher soil depths and higher litter input under CT and MT compensated in the long term the higher physical impact by tillage equipment than under NT. The Corg stocks (kg Corg m−2) in 522 kg soil, based on the equivalent soil mass approach (CT: 0–40 cm, MT: 0–38 cm, NT: 0–36 cm) increased in the order CT (5.2) = NT (5.2) < MT (5.7). Significantly (p ≤ 0.05) highest Corg stocks under MT were probably a result of high crop yields in combination with reduced physical tillage impact and effective litter incorporation, resulting in a Corg sequestration rate of 31 g C-2 m-2 yr-1. (ii) Significantly higher yields of macro aggregates (g kg-2 soil) under NT (732-777) and MT (680-726) than under CT (542-631) were generally restricted to the 0-5 cm sampling depth for all sampling dates. Temporal changes on aggregate size distribution were only small and no tillage induced net effect was detectable. Thus, we assume that the physical impact by tillage equipment was only small or the impact was compensated by a higher soil mixing and effective litter translocation into higher soil depths under CT, which probably resulted in a high re aggregation. (iii) The short term incubation study showed that macro aggregate yields (g kg-2 soil) were higher after 28 days in soils receiving OM (121.4-363.0) than in the control soils (22.0-52.0), accompanied by higher contents of microbial biomass carbon and ergosterol. Highest soil respiration rates after OM amendments within the first three days of incubation indicated that macro aggregate formation is a fast process. Most of the rebuilt macro aggregates were formed within the first seven days of incubation (42-75%). Nevertheless, it was ongoing throughout the entire 28 days of incubation, which was indicated by higher soil respiration rates at the end of the incubation period in OM amended soils than in the control soils. At the same time, decreasing carbon contents within macro aggregates over time indicated that newly occluded OM within the rebuilt macro aggregates served as Corg source for microbial biomass. The different clay contents played only minor role in macro aggregate formation under the particular conditions of the incubation study. Overall, no net changes on macro aggregation were identified in the short term. Furthermore, no indications for an effective Corg sequestration on the long term under NT in comparison to CT were found. The interaction of soil disturbance, litter distribution and the fast re aggregation suggested that a distinct steady state per tillage treatment in terms of soil aggregation was established. However, continuous application of MT with a combination of reduced physical tillage impact and effective litter incorporation may offer some potential in improving the soil structure and may therefore prevent incorporated LF from rapid decomposition and result in a higher C sequestration on the long term.
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Mesh generation is an important step inmany numerical methods.We present the “HierarchicalGraphMeshing” (HGM)method as a novel approach to mesh generation, based on algebraic graph theory.The HGM method can be used to systematically construct configurations exhibiting multiple hierarchies and complex symmetry characteristics. The hierarchical description of structures provided by the HGM method can be exploited to increase the efficiency of multiscale and multigrid methods. In this paper, the HGMmethod is employed for the systematic construction of super carbon nanotubes of arbitrary order, which present a pertinent example of structurally and geometrically complex, yet highly regular, structures. The HGMalgorithm is computationally efficient and exhibits good scaling characteristics. In particular, it scales linearly for super carbon nanotube structures and is working much faster than geometry-based methods employing neighborhood search algorithms. Its modular character makes it conducive to automatization. For the generation of a mesh, the information about the geometry of the structure in a given configuration is added in a way that relates geometric symmetries to structural symmetries. The intrinsically hierarchic description of the resulting mesh greatly reduces the effort of determining mesh hierarchies for multigrid and multiscale applications and helps to exploit symmetry-related methods in the mechanical analysis of complex structures.
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We investigate the properties of feedforward neural networks trained with Hebbian learning algorithms. A new unsupervised algorithm is proposed which produces statistically uncorrelated outputs. The algorithm causes the weights of the network to converge to the eigenvectors of the input correlation with largest eigenvalues. The algorithm is closely related to the technique of Self-supervised Backpropagation, as well as other algorithms for unsupervised learning. Applications of the algorithm to texture processing, image coding, and stereo depth edge detection are given. We show that the algorithm can lead to the development of filters qualitatively similar to those found in primate visual cortex.
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A new formulation for recovering the structure and motion parameters of a moving patch using both motion and shading information is presented. It is based on a new differential constraint equation (FICE) that links the spatiotemporal gradients of irradiance to the motion and structure parameters and the temporal variations of the surface shading. The FICE separates the contribution to the irradiance spatiotemporal gradients of the gradients due to texture from those due to shading and allows the FICE to be used for textured and textureless surface. The new approach, combining motion and shading information, leads directly to two different contributions: it can compensate for the effects of shading variations in recovering the shape and motion; and it can exploit the shading/illumination effects to recover motion and shape when they cannot be recovered without it. The FICE formulation is also extended to multiple frames.
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A key problem in object recognition is selection, namely, the problem of identifying regions in an image within which to start the recognition process, ideally by isolating regions that are likely to come from a single object. Such a selection mechanism has been found to be crucial in reducing the combinatorial search involved in the matching stage of object recognition. Even though selection is of help in recognition, it has largely remained unsolved because of the difficulty in isolating regions belonging to objects under complex imaging conditions involving occlusions, changing illumination, and object appearances. This thesis presents a novel approach to the selection problem by proposing a computational model of visual attentional selection as a paradigm for selection in recognition. In particular, it proposes two modes of attentional selection, namely, attracted and pay attention modes as being appropriate for data and model-driven selection in recognition. An implementation of this model has led to new ways of extracting color, texture and line group information in images, and their subsequent use in isolating areas of the scene likely to contain the model object. Among the specific results in this thesis are: a method of specifying color by perceptual color categories for fast color region segmentation and color-based localization of objects, and a result showing that the recognition of texture patterns on model objects is possible under changes in orientation and occlusions without detailed segmentation. The thesis also presents an evaluation of the proposed model by integrating with a 3D from 2D object recognition system and recording the improvement in performance. These results indicate that attentional selection can significantly overcome the computational bottleneck in object recognition, both due to a reduction in the number of features, and due to a reduction in the number of matches during recognition using the information derived during selection. Finally, these studies have revealed a surprising use of selection, namely, in the partial solution of the pose of a 3D object.
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A method is presented for the visual analysis of objects by computer. It is particularly well suited for opaque objects with smoothly curved surfaces. The method extracts information about the object's surface properties, including measures of its specularity, texture, and regularity. It also aids in determining the object's shape. The application of this method to a simple recognition task ??e recognition of fruit ?? discussed. The results on a more complex smoothly curved object, a human face, are also considered.
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This paper describes a general, trainable architecture for object detection that has previously been applied to face and peoplesdetection with a new application to car detection in static images. Our technique is a learning based approach that uses a set of labeled training data from which an implicit model of an object class -- here, cars -- is learned. Instead of pixel representations that may be noisy and therefore not provide a compact representation for learning, our training images are transformed from pixel space to that of Haar wavelets that respond to local, oriented, multiscale intensity differences. These feature vectors are then used to train a support vector machine classifier. The detection of cars in images is an important step in applications such as traffic monitoring, driver assistance systems, and surveillance, among others. We show several examples of car detection on out-of-sample images and show an ROC curve that highlights the performance of our system.
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Stimuli outside classical receptive fields have been shown to exert significant influence over the activities of neurons in primary visual cortexWe propose that contextual influences are used for pre-attentive visual segmentation, in a new framework called segmentation without classification. This means that segmentation of an image into regions occurs without classification of features within a region or comparison of features between regions. This segmentation framework is simpler than previous computational approaches, making it implementable by V1 mechanisms, though higher leve l visual mechanisms are needed to refine its output. However, it easily handles a class of segmentation problems that are tricky in conventional methods. The cortex computes global region boundaries by detecting the breakdown of homogeneity or translation invariance in the input, using local intra-cortical interactions mediated by the horizontal connections. The difference between contextual influences near and far from region boundaries makes neural activities near region boundaries higher than elsewhere, making boundaries more salient for perceptual pop-out. This proposal is implemented in a biologically based model of V1, and demonstrated using examples of texture segmentation and figure-ground segregation. The model performs segmentation in exactly the same neural circuit that solves the dual problem of the enhancement of contours, as is suggested by experimental observations. Its behavior is compared with psychophysical and physiological data on segmentation, contour enhancement, and contextual influences. We discuss the implications of segmentation without classification and the predictions of our V1 model, and relate it to other phenomena such as asymmetry in visual search.
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Stimuli outside classical receptive fields significantly influence the neurons' activities in primary visual cortex. We propose that such contextual influences are used to segment regions by detecting the breakdown of homogeneity or translation invariance in the input, thus computing global region boundaries using local interactions. This is implemented in a biologically based model of V1, and demonstrated in examples of texture segmentation and figure-ground segregation. By contrast with traditional approaches, segmentation occurs without classification or comparison of features within or between regions and is performed by exactly the same neural circuit responsible for the dual problem of the grouping and enhancement of contours.