Browsing by Subject "Modellierung"

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Die Abscheidefunktion von Hordenschüttler und Reinigungsanlage in Mähdreschern
(1993) Böttinger, Stefan
Das Durchsatzoptimum von Mähdreschern wird bei dem maximalen Gutdurchsatz mit noch akzeptablen Kornverlusten der Trennelemente Hordenschüttler und Reinigungsanlage erreicht. Dem Mähdrescher-Fahrer müssen Hilfsmittel für das Erkennen des Durchsatzoptimums zur Verfügung gestellt werden, da es in Abhängigkeit der Stoffeigenschaften des Erntegutes stark schwankt. Es werden physikalische Modelle für die Trennprozesse im Mähdrescher aufgestellt und die mathematische Beschreibung der Kornabscheidung über der Länge der Trennelemente daraus abgeleitet. Aus Messwerten der Kornabscheidung an verschiedenen Stellen eines Trennelementes werde aktuelle Parameter der Abscheidefunktion bestimmt und verschiedenen Prozesskenngrößen berechnet. Die Korrelation zwischen den berechneten Prozesskenngrößen und dem Betriebsverhalten der Trennelemente wird im labor- und Feldversuch experimentell untersucht.
Adaptation of herd simulation models to predict the efficiency of the use of resources in tropical ruminant production systems
(2020) Bateki Adjogo, Christian; Dickhöfer, Uta
Agricultural systems in the (Sub-)Tropics are under increasing pressure to produce more food and satisfy the growing demand of a rapidly growing and more affluent human population for agricultural products. With growing rates of urbanization in these regions and the associated dietary changes, the demand for calories from animal-based foods like milk, meat, and eggs could increase by 74 to 114 % between 2010 and 2050. Ruminant livestock have the potential to contribute to satisfying the demand for animal-based foods in the (Sub-)Tropics, but also raise considerable environmental concerns, amongst others due to their emissions. The use of simulation models is a holistic approach to identify how to sustainably harness the potential of ruminants for animal-based food production in the (Sub-)Tropics. Although several ruminant herd models are relevant for studying tropical ruminant production systems, most of them were developed using data that quantify and characterize biological processes of ruminants in temperate regions. Therefore, the present thesis identified and adapted an existing ruminant livestock herd model to adequately predict resource use and the potential outputs from production systems in the (Sub-)Tropics. The present thesis showed that state-of-the-art ruminant livestock herd models used to simulate tropical production systems need further development to enable them to address the modelling needs identified. Instead of developing new models to address these modelling needs, existing simulation models could be adapted using the increasingly available data that quantify and characterize biological processes in ruminants in these regions. This approach will ensure that not only the direction of change for different management strategies will be identified for tropical ruminant production systems, but also the correct magnitude of resources use and productive and reproductive performance.
Agro-economic policy analysis with the regional production model ACRE : a case study for Baden-Wuerttemberg
(2011) Henseler, Martin; Dabbert, Stephan
Since its introduction the Common Agricultural Policy (CAP) of the European Union (EU) has undergone several reforms in order to adapt policy instruments and enable the agricultural sector to fulfil multiple functions with respect to economic, supply and environmental objectives. In the German federal state Baden-Wuerttemberg agricultural production is characterized by regional heterogeneity. Therefore it is important to estimate the impacts resulting from changes in the CAP at a detailed regional level. In this study the agricultural policy model ACRE (Agro-eConomic pRoduction model at rEgional level) has been used to simulate different policy scenarios and to analyze regional economic, production and environmental impacts. In particular the study aims to address the following research questions: What are the regional impacts of different policy measures in the German federal state Baden-Wuerttemberg with respect to economic, production and environmental objectives? How suitable are the simulated policy measures for achieving the policy objectives of the CAP 2003 reform, as well as the objectives of subsidy reduction, promotion of energy crop production, reduction of environmental pollution and promotion of agro-environmental measures? How suitable is the regional supply model ACRE as a tool for policy analysis and policy decision support? In order to address the research questions, ACRE has been updated, adapted and extended to simulate agricultural production in the federal state Baden-Wuerttemberg at NUTS3 level. The policy scenarios simulated in this study are defined to cover recent discussions on the future development of the CAP and their results are analysed according to a regional framework for NUTS3 counties, farm types and the complete model region. The simulation of the reference year (REF) implies the policy reform Agenda 2000 in the simulation year 2000. Thus, REF represents the observed situation of regional agricultural production on whose statistical data ACRE is calibrated. The scenario CAP2003 simulates the policy measures of the CAP 2003 reform in the simulation year 2015. Assumptions of increased yields and prices as well as harmonized direct payments for arable land and grassland result in an increase in income as well as in an increase of subsidy volume. In the entire model region Baden-Wuerttemberg cereal production increases while the production of fattening bulls and pigs decreases. Increases in crop production intensity result in an increase in environmental pollution. The scenario CAP2003 is used as the baseline scenario to compare the results of simulated policy scenarios which are delineated in the following paragraphs only with the most important results for the complete model region Baden-Wuerttemberg. In two subsidy reduction scenarios the simulated policy instruments aim to reduce subsidy volume by reducing Pillar 1 payments by 60% and by shifting 70% of the money from Pillar 1 to Pillar 2 respectively. Both scenarios result in the positive impact of a decrease in subsidy volume, but show a negative impact, especially an increase of abandoned land. In two energy crop scenarios the production of energy maize is simulated under the assumption that different situations in energy policy and energy markets result in different competitiveness between production of energy maize and food. In both scenarios energy crop production partially replaces cereal production, although the extent varies according to the high or small level of competitiveness between production of energy maize and food. Impacts on agricultural income and subsidies are small while increased environmental pressure is expected in the event of a significant expansion in energy crop production. Two nitrogen reduction scenarios simulate policy measures according to the water framework directive (WFD) and the OSPAR convention. The scenario according to the WFD (limitation of organic nitrogen input to a maximum of 170kg nitrogen per hectare) does not result in any impacts. In contrast, the scenario according to the OSPAR convention (reduction of nitrogen input quantities by 10%) results in a decrease in environmental pollution and is accompanied by a reduction of income and reduction of agricultural production under land abandonment. In the scenario of mandatory agri-environmental measures (AEM) it is assumed that the area with applied AEM is extended. The increase of AEM area results in a decrease in cereal production and a reduction of environmental pollution, while income decreases only slightly. Two combined scenarios simulate a mix of different policy and market situations which provoke an intensive and an extensive agricultural production. The results of these scenarios illustrate the interaction of the single policy measures. The measures of subsidy reduction have similar reducing impacts on income and subsidy volume in both scenarios. In the intensive production scenario high competitive energy crop production and a less restrictive nitrogen restriction result in a compensation effect of land abandonment by extension of energy crop area. In the extensive production scenarios, less competitive energy crop production and a high restrictive nitrogen constraint result in reduced agricultural production, increased land abandonment and reduced environmental pressure. In order to evaluate the impact of the simulated policy measures on the achievement of policy objectives the results of all scenarios are compared and ranked according to their impact on the policy objectives. The analyses of the model results show impacts of policy measures which are likely to be expected. However, the analyses at NUTS3 as well as farm types' level reveal that the impacts of the policy measures can be regionally quite different. Thus the detailed regional model results clearly show that (and where) the implementation of agricultural policy measures requires a regional specific evaluation and monitoring. In order to discuss the study with regard to the methods applied and the outcome, a final strengths and weaknesses analysis was conducted. The analysis highlights the strengths of the study (e.g. the model validation, the regional analysis of different policy scenarios, the possibility of cooperation with regional stakeholders). The validation and the results of the study also show that ACRE is a suitable tool for regional agricultural policy analysis and policy decision support. Supplementary work could help to overcome single shortcomings and caveats and to further develop the model. However, ACRE can already be used now as a useful tool for the regional agricultural policy analysis of the CAP in Baden-Wuerttemberg.
An expert system for planning and designing dairy farms in hot climates
(2008) Samer Mohamed, Mohamed; Jungbluth, Thomas
Planning and designing dairy farm facilities is a sophisticated work where a multitude of procedures should be carried out which requires time and efforts; moreover, making mistakes is also possible. Therefore, it is necessary to develop computer tools that have the ability to pre-process the data so as to produce value-added information, in order to accelerate analyses and to improve decision-making. Eleven simulation models were developed to plan and design several dairy farm facilities. Subsequently, an electronic spark map (decision tree) was developed for each simulation model, and then the simulation models were integrated into the relevant spark maps. Afterwards, C# language (C Sharp), which is an object-oriented programming language, was used to develop an expert system via the simulation models and the electronic spark maps. The developed expert system is able to plan and design several dairy farm facilities, e.g. housing system (corrals system), shade structure and roof material, concrete base, cooling system, milking parlor, forage storage, and manure handling system. Subsequently, it plans the farmstead layout, and it leads to implement the technologies, equipments, and machines required for performing several farm operations. Furthermore, it studies water and electricity requirements of the planned dairy farm and the available sources on site. Moreover, it calculates the capital investment and the fixed, variable, and total costs. Data of 6 dairy farms were used to carry out the expert system validation and evaluation. The differences between the actual and calculated values were determined and the standard deviations were calculated. The coefficients of variation range between 3% and 7%. The required input data are 358 thereof a multitude will be recommended by the expert system itself; consequently, it computes and displays 372 output data with the ability of saving and retrieving data. Besides, the system?s accuracy had been calculated using the actual and calculated values of the different outputs and it was found 98.6%. However, the system?s syntax includes 22106 lines. It can be concluded that the developed expert system can be used successfully for planning and designing dairy cow farms in hot climates.
Assessing alternative options to improve farming systems and to promote the adoption of low-carbon agriculture in Mato Grosso, Brazil
(2018) Carauta, Marcelo; Berger, Thomas
Currently, our society faces a significant challenge to eradicate hunger and poverty while preserving natural resources and reducing greenhouse gas (GHG) emissions. In this context, Brazil plays an important role since it is one of the most significant players in global food production and hosts a variety of ecosystems and a significant share of the Earths biodiversity. The federal state of Mato Grosso (MT) is located at the most dynamic agricultural frontier in the Cerrado-Amazon transition zone and leads the national production of grain, fiber, and meat. The need to balance agricultural production and environmental protection shifted the focus of Brazilian land-use policy toward sustainable agriculture. The federal government pledged to reduce its GHG emissions and implemented policies to enforce it. Brazils low-carbon agricultural plan offers credit with low-interest rate to farmers who want to implement sustainable agriculture practices. These include the restoration of degraded pasture, adoption of integrated systems, no-till agriculture, biological nitrogen fixation, commercial forests, treatment of animal wastes, and climate change adaptation. The present thesis contributed to the CARBIOCIAL project (“Carbon-optimized land management strategies for southern Amazonia”), a German-Brazilian cooperation to investigate viable carbon-optimized land management strategies maintaining ecosystem services under changing climate conditions in the Southern Amazon. In this context, this thesis examines options to improve farming systems in MT and evaluates policy measures that could promote the adoption of low-carbon agricultural systems. The work is divided into three parts: The first part is subdivided into three chapters (chapters 1, 2 and 3) and offers an overview on land use change in Brazil and explores land use decisions of farmers in MT, where highly dynamic double-crop systems currently prevail. The second part is subdivided into two chapters (chapters 4 and 5) and is dedicated to evaluating alternative options to improve farming systems in MT. The third part is subdivided into three chapters (chapters 6, 7 and 8) and investigates factors that may influence farmers to adopt IAPS, evaluates policy measures to promote the adoption of low-carbon agricultural systems, and provides a detailed quantification of individual GHG emissions of a large variety of agricultural practices and the aggregate emissions resulting from their current use in MT. To this end, this thesis develops an Integrated Assessment (IA) approach that simulates farm-level decision-making and agricultural land use change. It introduces a novel approach to evaluate the full distribution of GHG emissions related to the agricultural land-use change in MT. Our IA approach integrates three software packages: MPMAS (Mathematical Programming-based Multi-Agent Systems), MONICA (Model for Nitrogen and Carbon in Agro-ecosystems) and CANDY (Carbon and Nitrogen Dynamics). Data to parameterize the model was gathered from several sources, such as field experiments, statistical offices, farm level surveys from private consultancies, life-cycle inventory databases, extension services, expert interviews, and literature. This thesis presents the first extensive study on crop yield response in MT by simulating yields in response to different climatic conditions, soil types, sowing dates, crop rotation schemes, fertilization amounts, and macro-regions. The simulation results show that biophysical constraints still play a crucial role on yield gaps in MT whereas socio-economic constraints have a slight yield-increasing effect. This thesis further examines alternative ways to improve the farming systems in MT by investigating the role of sunflower adoption in increasing farm income. We have found a substantial potential for sunflower cultivation in MT with positive impacts on both farm and regional level. Additionally, we identified bottlenecks for sunflower diffusion such as the distance from farm gate to processing facility. Regarding Brazilian agricultural policy, we have found that the Brazilian low-carbon agricultural program contributed to the adoption of integrated systems. However, we observed different adoption rates through macro-regions and types of integrated systems. Furthermore, our simulations additionally show that the ABC program also contributed to the adoption of less GHG-emitting practices, but its performance is subjected to agent expectations on prices and yields
Bedeutung der Stickstoffumsetzung und externer Stickstoffquellen für die Entwicklung von FFH-Mähwiesen in Baden-Württemberg
(2023) Kukowski, Sina Louise; Streck, Thilo
1. AIM AND OBJECTIVES OF THE STUDY. The condition of the species-rich lowland hay meadows (habitat type 6510) in Germany is increasingly deteriorating. One cause of the deterioration is the supply of reactive nitrogen (N). To counteract the ongoing deterioration, it is necessary to understand the relationships between external N inputs via the atmosphere and fertilization, internal N turnover in the soil, plant uptake and growth, as well as possible links to the conservation degree of this habitat type. The overall objective of this dissertation is therefore to contribute to a better process-based understanding of the complete N cycle of Fauna-Flora-Habitat (FFH) meadows. 2. MATERIAL & METHODS. The interdisciplinary structure of this thesis includes different approaches to study inputs, turnover and outputs of N. With respect to N input via the airborne pathway, the focus was primarily placed on the hitherto poorly studied relationships between ammonia concentration and specific N-sensitive species groups in FFH lowland hay meadows. These relations were analyzed by means of generalized mixed models (GLM) based on nationwide data. In addition, further site-specific factors with a significant influence on the conservation degree of FFH meadows were identified using GLM. For the quantification of soil-borne N turnover processes, an empirical approach was chosen, including the determination of gross N turnover rates using the 15N isotope dilution method. To record these N dynamics, an intensive monitoring of gross and net N fluxes (mineralization, nitrification, ammonium consumption, nitrate consumption) in soils from different primary substrate and with different meadow conservation degree was carried out in 2016 and 2017. The results were merged using a process-based agroecosystem model (EXPERT-N), which was adjusted for habitat type 6510 to the collected data. The adapted model was applied to other sites of habitat type 6510 distributed throughout the state of Baden-Württemberg, which served to investigate spatial and temporal patterns of relevant nitrogen fluxes over an extended time period (1996 until 2012) and had been characterized in terms of soil and vegetation. 3. RESULTS. The nationwide data show a statistically significant decrease of habitat-typical low-nutrient indicator species and an increase of N indicator species with increasing atmospheric ammonia concentration on lowland hay meadows in Baden-Württemberg. Whether this is an effect of the atmospheric ammonia concentration or whether differences in agricultural land use structure play the decisive role could not be clarified with the available data. The intensive monitoring on selected FFH lowland hay meadows showed that soil-borne gross nitrification rates on soils from calcareous parent substrate (high pH) differed significantly from those from decalcified substrate (low pH). Both gross mineralization and gross nitrification were characterized by high temporal variability at all sites, which could not be explained by measurements of soil temperature and soil water content. Determination of net N turnover rates showed almost no variability and could not be used to draw conclusions about actual gross turnover rates in soil. The N-turnover model adapted for habitat type 6510 was able to represent spatial and temporal patterns over an extensive period of time. Simulation results showed high spatial and temporal variability for most N cycle variables. Soil organic N mineralization has a critical influence on the amount of plant-available N and thus has a direct impact on yield and N removal. On high clay-content soils and sites with high organic matter content, the model overestimated mineralization. External N inputs, such as moderate organic fertilization or atmospheric N deposition, were less crucial for yield. Additional N input is always a driving factor for N turnover in soil in the short term. With already high turnover levels, N turnover continues to increase and thus the risk of nutrient imbalances also increases. In the long term, the decisive factor for the N balance of FFH lowland hay meadows is whether N supply exceeds removal, whether the mineralizable organic N pools are thus increased, or whether a balance between supply and removal can be achieved. If soil internal N turnover is high, as it was the case on most of the simulated sites, a longer depletion phase should be applied before. In summary, this dissertation provides insight into the complexity of N cycling of FFH meadows. Using various approaches (statistical analyses, field trials, process-based modelling), it contributes to a better understanding of site-specific N turnover and the role of external N sources for the development of this ecosystem.
Combining remote sensing and crop modeling techniques to derive a nitrogen fertilizer application strategy
(2020) Röll, Georg; Graeff-Hönninger, Simone
The crucial question in this thesis was how can remote sensing data and crop models be used to derive a N fertilizer strategy that is capable to lower the environmental side effects of N fertilizer application. This raised the following detailed objectives: The first objective (i) how N content determination via spectral reflectance is influenced by different leaves and positions on the leaf was investigated in Publication I. Different wheat plants were cultivated under different N levels and under drought stress in two hydroponic greenhouse trials. Spectral reflectance measurements were taken from three leaves and at three positions on the leaf for each plant. In total, 16 vegetation indices broadly used in the literature were calculated based on the spectral reflectance for each combination of leaf and position. The plant N content was determined by lab analyses. Neither the position on the leaf nor leaf number had an impact on the accuracy of plant N determination via spectral reflectance measurements. Therefore measurements taken at the canopy level seem to be a valid approach. However, if other stress symptoms like drought or disease infection occur, a differentiation between leaves and positions on the leaf might play a more crucial role. Publication II dealt with the second objective on (ii), how to incorporate leaf disease into the DSSAT wheat model to enable the simulation of the impact of leaf disease on yield. An integration of sensor information in crop growth models requires the update of model state variables. A model extension was developed by adding a pest damage module to the existing wheat model. The approach was tested on a two-year dataset from Argentina with different wheat cultivars and on a one-year dataset from Germany with different inoculum levels of septoria tritici blotch (STB). After the integration of disease infection, the accuracy of the simulated yield and leaf area index (LAI) was improved. The Root mean squared error (RMSE) values for yield (1144 kg ha−1) and LAI (1.19 m2 m−2) were reduced by half (499 kg ha−1) for yield and LAI (0.69 m2 m−2). A sensitivity analysis also showed a strong responsiveness of the model by the integration of different STB disease infection scenarios. Increasing the modeling accuracy even further a MM approach seems to be suitable. Assembling more models increases the complexity of the simulation and the involved calibration procedure especially if the user is not familiar with all models. To avoid these conflicts, Publication III evaluated the third objective (iii) if an automatic calibration procedure in a MM approach for winter wheat can eliminate the subjectivity factor in model calibration. The model calibration was performed on a 4-yr N wheat fertilizer trial in southwest Germany. The evaluation mean showed satisfying results for the calibration (d-Index 0.93) and evaluation dataset (d-Index 0.81). This lead to the fourth (iv) objective to use a MM approach to improve the overall modeling accuracy. The evaluation of a fertilizer trial showed an improved modeling accuracy in most cases, especially in the drought season 2018. Based on the combination of a MM approach and the incorporation of sensor data, a Nitrogen Application Prescription System (NAPS) was developed. The initial NAPS setup requires long term recorded data (yield, weather, and soil) to ensure proper MM calibration. After calibration, the current growing season conditions are required (weather, management information) until the N application date. Afterward, the NAPS incorporates remote sensing information and generated weather for running future N application scenarios. The selection of the proper amount of N is determined by economic and ecological criteria. Furthermore, in order to account for differences in in-field variabilities and to deliver a N prescription site-specifically, the NAPS concept has to be applied on a geospatial scale by adjusting soil parameters spatially. The NAPS concept has the potential to adjust the N application more economically and ecologically by using current sensor data, historical yield records, and future weather prediction to derive a more precise N application strategy. Finally, this concept exhibits the potential for reconciliation of the issue of an economic, agricultural production without harming the environment.
Constraints on microbial pesticide degradation in soils
(2023) Wirsching, Johannes; Kandeler, Ellen
Pesticides are an essential component of intensified agriculture and have contributed significantly to the increase in food production observed in recent decades. Since 1960, pesticide use has increased by a factor of fifteen to twenty, representing a market value of $40 billion in 2016. Soil monitoring campaigns to track pesticide contamination of croplands across Europe are quantifying pesticide residues whose residence times in soils exceed expected values. Diffuse contamination by pesticide residues raises concerns about soil functions, soil biodiversity, and food safety, as well as the transport of contaminants by wind and water to surface waters or to adjacent, organically managed croplands. Data on the frequency of occurrence and concentrations of pesticide residues in soil demonstrate a discrepancy between the determination of persistence and subsequent approval and their actual fate in soil. This raises the question of whether degradability of individual organic compounds has been adequately studied. Microbiological degradation is the most important process for reducing pesticide loads in soils. A reliable estimate of pesticide residence time requires an expanded understanding of the factors limiting microbial degradation. Degradation of anthropogenic organic chemicals in soils occurs much more slowly than would be expected based on their physicochemical properties. While processes that determine the fate of pesticides in soil have often been studied at different spatial and temporal scales, reasons for discrepancies between the observed complete degradation of pesticides under laboratory conditions and their persistence in the field remain unclear. This thesis addresses this challenge by focusing on the central question of why inherently biodegradable compounds in soils display increased persistence under field conditions. Organic contaminants in low but detectable and environmentally significant concentrations could remain in the soil once available concentrations fall below a threshold where bioenergetic growth restrictions come into play. In addition, potential microbial and biophysical limitations and environmental factors such as soil temperature and soil moisture are often examined separately in current degradation studies. Combinations of temperature and soil moisture changes associated with different concentration levels have been less well examined, resulting in an incomplete understanding of the degradation process. Another key factor in the demonstrated discrepancy between predicted and actual persistence in the field could be due to laboratory experiments that cannot account for field-scale processes. Therefore, degradation rates determined in laboratory experiments cannot be confidently extrapolated to the field scale. . This thesis identified further important regulatory mechanisms for microbially mediated pesticide degradation. The previously unknown concentration-dependent degradation dynamics and the concentration-dependent influence of limiting environmental conditions on microbial degradation emphasize the importance of studies using a realistic concentration range. Evidence of deep transport of a highly sorptive pesticide such as glyphosate primarily via preferential flow pathways into the subsoil with lower degradation dynamics underscores the need to include processes that can only be verified in field studies as part of risk assessments. The results of this thesis suggest that the biodegradation rates of pesticides are not homogeneous at field scales and may account in part for the discrepancy between complete degradation of pesticides under laboratory conditions and their persistence in the field. Laboratory studies in which soil samples are pooled and mixed to obtain a single "representative" sample can provide a simplified understanding of the process, but the complexity, particularly that of soil heterogeneity, of pesticide distribution and microbial degradation associated with prevailing climatic conditions, requires calibration of previously used methods in field studies and possibly at landscape, watershed, or regional scales. The scale-dependent degradation aspect will become even more important in the future; as soil properties and processes that control the toxicological aspects of contaminants include temperature and moisture, and changes associated with climate change will lead to an increase in extreme precipitation, longer dry periods, and soil erosion.
Costs and benefits of ammonia and particulate matter emission abatement and interactions with greenhouse gas emissions in German agriculture
(2017) Wagner, Susanne; Zeddies, Jürgen
In the past decades, agricultural and particularly livestock production have increased with population growth and increasing demand for food, especially for livestock products, at global level. This trend is expected to continue in the coming decades and may even be fortified by an increasing demand for non-food biomass in an economy based on renewable biological resources. Agriculture influences also the state of the environment. Agriculture has been associated with expansion into natural ecosystems, adversely affecting biodiversity and has a large share in the global emissions of greenhouse gases and ammonia (NH3) and in the release and formation of primary and secondary fine particulate matter (PM2.5). NH3 emissions can lead to a loss of biodiversity in nitrogen-limited terrestrial ecosystems and can form secondary PM2.5 in the atmosphere. PM2.5 emissions may affect human health by causing respiratory and cardiovascular diseases and a reduction in life expectancy. As NH3 and PM emissions partly originate from the same production activities as greenhouse gases, interactions between NH3 and PM emission abatement and greenhouse gas emissions may exist. Emissions can be reduced by technical measures or by shifts towards a diet low in animal-based food products, because plant-based food products cause fewer emissions than animal-based food products. In Germany, agriculture contributes about 95% of the total NH3 emissions and 5% to primary PM2.5 and 8% to greenhouse gas emissions. Because of the environmental impacts and subsequent governmental regulations, there is a need to reduce emissions of NH3, PM2.5 and of greenhouse gas emissions significantly. The main objective of this thesis research was to increase the understanding of the full effects of NH3 and PM emission abatement in agriculture. Particularly, it aimed to quantify and compare farmers’ costs and society’s benefits of reducing NH3 and PM emissions in agriculture in Germany while considering interactions with greenhouse gas emissions and to identify cost-efficient NH3 and PM emission abatement measures. Both technical NH3 and PM emission abatement measures and a diet shift were examined with respect to the abatement costs and the benefits in terms of avoided damage costs of impacts on human health, terrestrial biodiversity and the climate. The analysis combined agricultural emission modelling and integrated environmental impact assessment, applying the impact-pathway approach, complemented by literature analysis. The abatement potentials ranged from 2 to 45% for NH3 emissions, from 0 to 38% for PM2.5 emissions and from 0to 49% for greenhouse gas emissions. The abatement potentials of a diet shift exceeded those of technical abatement measures. All air pollutant abatement measures affected greenhouse gases, in most cases synergistically. The average abatement costs ranged from 2.7 to 25.6 EUR per kilogramme NH3 reduced, from 7.5 to 31.2 EUR per kilogramme PM2.5 reduced and 0.01 to 0.03 EUR per kilogramme greenhouse gas emissions reduced. The average benefits were 24.5 EUR per kilogramme NH3 reduced and 68.3 EUR per kilogramme PM2.5 reduced. The benefits of reduced health damage costs were higher than those of reduced biodiversity loss, resulting in higher benefits of PM2.5 reduction. The benefits of the reduction of greenhouse gas emissions were 0.09 EUR per kilogramme. In conclusion, synergies with greenhouse gas mitigation reduced the abatement costs per unit of emission type, increased the benefits and improved the cost-efficiency of air pollutant abatement measures. This finding indicates that air pollutant abatement and greenhouse gas mitigation should be analysed together and that environmental policy design should consider interactions. The abatement potentials of technical measures were limited and should be complemented by changes in food consumption patterns to meet politically agreed emission reduction targets. Besides emission reductions, diets with low consumption of animal-based food provided land for alternative uses such as food production, lignocellulosic biomass production or biodiversity conservation that have the potential to reduce pressure on land from increasing demand for food by a globally growing population or for lignocellulosic biomass in an economy based on renewable biological resources.
Designing, modeling, and evaluation of improved cropping strategies and multi-level interactions in intercropping systems in the North China Plain
(2010) Knörzer, Heike; Claupein, Wilhelm
Adjusting cropping systems in order to increase their efficiency is a global issue. High yield and sustainability are the catchphrases of production in the 21st century, and agricultural production has to solve the balancing act between ecology and economy. Therefore, the requests for farmers, consultants and researchers are rising, and production modes are changing. Nevertheless, solutions have to be detected spatially explicit and locally adapted and accepted in order to be implemented successfully. Taking the North China Plain as an example, the productivity of arable land needs to be further increased by applying strategies to reduce or avoid negative environmental effects. Further yield increases are not possible by increasing input factors like N-fertilizer or irrigation water as N-fertilizer rates are extremely high and irrigation water is limited. However, yield increases might be possible by developing improved cropping strategies operated by cropping designs. Taking modeling and simulation tools into account back up the acceleration of research attainments and the understanding of cropping systems. The present thesis embraces the designing and modeling of such a potential cropping system, to wit strip intercropping. Thus, the main goals of the study were to analyze, design, evaluate, and in the end model intercropping. Intercropping systems are complex systems which strongly need to be designed and evaluated carefully in order to fulfill the premises of ecological and economical efficiency as well as sustainability. Multi-level interactions have to be weighted and taken into regard for evaluating datasets applicative for modeling and simulating intercropping. The main results of the study indicated, that traditional cropping systems like intercropping are widespread in China, where approximately one third of arable land is under intercropping. Reviewing cereal intercropping systems in China, the four agro-ecological regions ?Northeast and North?, the ?Northwest?, the ?Yellow-Huai River Valley? and the ?Southwest? could be classified, distinguished and described. Intercropping offers a great variation of species combination, benefits as well as challenges for cropping systems design and farmers. Carefully balanced between facilitation and competition, intercropping bears the potential of increased yield and yield stability, income security, resource use efficiency and biodiversity. Intercropping gives evidence about traditional cropping systems with the potential for future production systems under the paradigm of sustainability. Further, results from conducted field experiments indicated that border effects are the key component of intercropping performance. Nevertheless, analyzing strip intercropping statistically has peculiarities as they lack in randomization because the cropping system imposes alternating strips. Thus, spatial variability and its effect on yield were regarded differently within a geo-statistical analysis. In addition to the geo-statistical analysis, the crop growth modeling approach paid tribute to monocropping effects as well as to field border effects occurring in strip intercropping systems. Further on a model-based approach was tested to quantify multi-level interactions with special regard to changing microclimatic conditions and to optimize intercropping systems from an agronomical point of view. In comparison to other interspecific competition modeling approaches, a shading algorithm was evaluated and implemented into the process-oriented crop growth model DSSAT in order to simulate competition for solar radiation. More common in modeling mixed intercropping, a modified Beer?s law subroutine has been used instead, e.g. in APSIM. APSIM and DSSAT were compared by modeling the conducted field trials. As a result, the Beer?s law approach was not capable to model strip intercropping. In contrast, the modeling with a changed DSSAT model showed that applying a simple shading algorithm that estimated the proportion of shading in comparison to the monocropping situation and in dependency from neighboring plant height seems to be a promising approach. The results indicated that competition for solar radiation in those systems is a driving force for crop productivity but neither the most dominant nor the one and only. Resource distribution and allocation in space and time seems to be more important than the total amount of resources. Those effects have to be taken into account when simulating interspecific competition.
Developing a biodiversity evaluation tool and scenario design methods for the Greater Mekong Subregion
(2011) Cotter, Marc; Sauerborn, Joachim
The Xishuangbanna Prefecture in Yunnan Province (PR China) is facing increasing conflicts between rural development and nature conservation because of an ongoing expansion and commercialization of farming. The rapid development of large-scale farming and the improvement of infrastructure throughout the region are posing serious threats to the conservation of endemic species of flora and fauna, while also offering possibilities for enhancing the livelihood of rural populations to an extend never seen before. The expansion of rubber (Hevea brasiliensis Willd Ex A. Juss) has caused a reduction and fragmentation of natural and secondary forest cover, thereby decreasing structural and species diversity as well as the loss of valuable ecosystem services. The establishment of intensified agriculture, especially plantations on sloping terrain, often leads to an increased erosion risk, nutrient run-off and sedimentation in water courses. Thus, large scale deforestation is not just a problem for nature conservation but also one for the rural economies. Rural development and simultaneous environment conservation often face trade-offs, especially in regions that host an exceptionally high biodiversity, such as many tropical areas. In order to adequately consider and evaluate these interactions, tools and methods have to be developed that allow decision makers to assess the impacts of different management and infrastructure options on the environment. The aim of the work presented in this thesis was to analyze and evaluate the effect of large-scale rubber cultivation on local and regional biodiversity by developing methods to integrate field studies from various disciplines into a comprehensive assessment model. This model was then used to highlight key aspects of anthropogenic influence on the plant species composition within the research area and to identify possible impacts of alternative land use decisions. Furthermore, the development of an interdisciplinary approach to scientific scenario design methods has been supplemented with a study on the acceptance of 3D-visualization as communication tool for land use planning in the background of nature conservation sciences. In order to achieve this, an overview of the agronomical and ecological aspects of rubber cultivation was provided. Literature sources referring to the impact of different cultivation systems on natural biodiversity were discussed and an introduction to the effect of rubber cultivation on Ecosystem Services was given. A method for projection of regionally adapted carbon capture properties of rubber cultivation under suboptimal growth conditions was presented and a comparative assessment of greenhouse gas emissions during the establishment of rubber plantations in regard to the preexisting vegetation was made. A biodiversity evaluation tool based on the combination of approaches from landscape ecology and empirical data within a Geographic Information System was developed. Detailed data on plant species diversity and distribution were combined with quality criteria like endemism or invasiveness to form spatially explicit biodiversity indices for different land use types in various elevation classes. Up-scaling in accordance to the land use distribution observed allowed the estimation of overall plant diversity and the evaluation of the effect of possible future land use scenarios. Habitat characteristics and spatial distribution were included into the analysis of the land use map derived from remote sensing information to allow for the assessment of fragmentation and landscape matrix structure. The methodology was tested with an array of possible present and future land use maps. It was possible not only to evaluate the different land use classes within and their distribution throughout the research area, but we were also able to compare distinct sub-regions based on topography or administrative status. The challenges stakeholders and nature conservation face in the different elevation zones of Nabanhe were highlighted and related to the findings of our partner workgroups from economy and social sciences. The feasibility of this approach to administration staff with limited experience in ecological modeling was one of the main goals in designing the methods. Given a reasonable data set on species diversity and distribution within any given tropical research area, this approach will enable planners and nature park administration to quickly project possible consequences on species diversity indices deriving from land use change within their respective research area. Using this approach, the importance of natural tropical forests for the maintenance of species diversity in tropical cultivated landscapes was highlighted. With the information gained from constructing this evaluation tool, the design and development process for a land use scenario based on the integration of multidisciplinary assessments and iterative scenario refinement with repeated stakeholder inclusion was promoted. By combining stricter conservation rules with alternative sources of income for the rural population in order to offer an alternative to monoculture rubber farming, the economic models and the land use allocation model predicted a stop in rubber and agriculture related deforestation, and the establishment of a considerable amount of reforested area. This was achieved by introducing an innovative land use type that is closely related to traditional local home garden agroforestry systems. By coupling reforestation efforts with the economic gain derived from intercropping Traditional Chinese Medicinal plants into degraded secondary forests, this scenario was, at least theoretically, able to remove deforestation pressure from the natural forest types and to offer an economic alternative to rubber cultivation. The methods used for this assignment can serve as guideline for future projects that want to implement scenario design procedures based on the combination of social sciences, economics, ecology and landscape planning. The acceptance and comprehensibility of computer based 3D visualization models for the communication of possible future land use scenarios was also tested. Two alternative scenarios were visualized and compared to the status quo, with questionnaires and guided interviews covering the acceptability and adaptability of such techniques for professionals from various fields of nature conservation. This thesis presents an overview over agronomic, economic and ecological aspects of rubber cultivation and highlights its implications on biodiversity and nature conservation. The methods discussed here can serve as a guideline for the integration of ecological indicators in land use planning and decision making processes. Although the concepts and topics introduced herein are closely interlinked within the framework of the Living Landscapes China (LILAC) research project, the methods and approaches can easily be applied to other areas in the Greater Mekong Subregion and beyond, be it the expansion of oil palm plantations in the Malayan Archipelago or the fragmentation of forests due to increased population pressure in Central Africa. Nature conservation is facing similar problems all over the developing world, and adaptable approaches such as the ones presented here are needed to support decision making processes in order to secure the preservation and long-term survival of the worlds? diversity in species and natural habitats.
Development of a generic, model-based approach to optimize light distribution and productivity in strip-intercropping systems
(2014) Munz, Sebastian; Claupein, Wilhelm
Due to a growing world population, an extension of bioenergy production and the larger proportion of meat and dairy products in the human diet, with the latter particularly in India and China, the demand for agricultural products will further increase. Under decreasing resources and negative environmental impacts related to past intensification, more sustainable agricultural production systems need to be developed in order to meet the future demand for agricultural products. China, as the most populous nation with an enormous economic growth since the end of the 1970’s, plays a major role in global agricultural production. On a national level, agricultural production has to be increased by 35% during the next 20 years. However, land and water resources in China are very limited. With this in mind, the Sino-German International Research Training Group (IRTG) entitled ‘Modeling Material Flows and Production Systems for Sustainable Resource Use in Intensified Crop Production in the North China Plain’ was initiated by the Deutsche Forschungs-Gemeinschaft (DFG) and the Chinese Ministry of Education (MOE). The present doctoral thesis was embedded in the IRTG and focused, in particular, on exploring combinations of different crops produced on the same land at the same time, known as intercropping. In general, the higher productivity in intercropping, compared with monocropping, arises from the complementary use of resources (radiation, water, and nutrients) over space and time by crops that differ in physiology, morphology and phenology. The decisive question is how to optimize intercropping systems over space and time. To address this question, the present doctoral thesis combined field experiments with modeling approaches with the following aims: (i) to investigate the light availability on high temporal and spatial resolutions; (ii) to develop and validate a model that simulates the light availability for the smaller crop and accounts for the major aspects of cropping design; (iii) to determine the effect of the modified light availability on growth of maize and the smaller, shaded crop; (iv) to evaluate the plant growth model CROPGRO for its ability to simulate growth of the smaller, shaded crop; (v) to investigate the interactions between maize cultivar, cropping design and local growth conditions; and, (vi) to identify promising cropping designs and detect future research needs to increase the productivity of strip-intercropping systems. For this purpose, field experiments comprising of strip-intercropping with maize (Zea mays L.) and smaller vegetables, including bush bean (Phaseolus vulgaris L. var. nana), were carried out over three growing seasons from 2010-2012 in southwestern Germany and in the North China Plain. Growing the crops in strips facilitates mechanized management, addressing the ongoing decrease of intercropping in China due to labor scarcity in rural areas. The crop combination of maize, a tall C4-crop with erectophile leaves, and bush bean, a small, N-fixating C3-crop with a more horizontal leaf orientation, was chosen due to the large potential for a complementary resource use. Special emphasis was given on the competition for light as it plays a major role in this cropping system due to the large height differences between the crops. In this context, measurements of the photosynthetically active radiation (PAR) were conducted on high spatial (individual rows across the strip) and temporal resolutions (five-minute intervals) at the top of the bush bean canopy over a two-month co-growing period with maize. The collected data formed the basis of the simulation study towards investigating competition for light and its influence on plant growth with modeling approaches. Experimental results showed that maize yields increased in the border rows of the strip due to a higher lateral incoming radiation in years with a sufficient water supply. On average, maize yields calculated for strips consisting of 18 to four rows increased by 3 to 12% and 5 to 24% at the German and Chinese sites, respectively. Analysis of yield components revealed that yield increases in the border rows of the maize strip were mainly determined by a larger number of kernels per plant. On the other hand, shading by the taller adjacent maize induced considerable shade adaptations of bush bean, such as larger canopy dimensions and a substantially increased leaf area index due to thinner, larger leaves. These shade adaptations increased light interception, and indicated that bush bean could tolerate shading up to 30%, resulting in a total and pod dry matter similar to that of monocropped bush bean. These results suggested that there is a good potential for utilizing bush bean in strip-intercropping systems in combination with taller crops. However, higher shade levels (>40%) resulted in considerable decreases of total and pod dry matter. The high temporal and spatial resolution of the PAR measurements clearly revealed a highly heterogeneous diurnal distribution of PAR across the bush bean strip. The developed light model simulated this heterogeneity with a high accuracy under both clear and cloudy conditions. Comparison of simulated and observed hourly values of PAR across several rows within the strip of bush bean showed a root mean square error (RMSE) ranging between 47 and 87 μmol m-2 s-1 and a percent bias (PBIAS) ranging between -3.4 and 10.0%. Furthermore, the model reasonably captured the influence of different widths of the bush bean strip, strip orientations and maize canopy architecture (height, leaf area index, and leaf angle distributions). Simulations run for different latitudes and sky conditions, including different strips widths, maize canopy heights and leaf area indices (LAI), indicate that: (i) increasing the strip width might only reduce shading in the border rows of the smaller crop at lower latitudes under a high fraction of direct radiation; (ii) at higher latitudes, the selection of a maize cultivar with reduced height and LAI are suitable options to increase the light availability for the smaller crop. The present doctoral thesis presents the first approach to use the monocrop plant growth model CROPGRO to simulate growth of a legume crop grown in an intercropping system. The CROPGRO model was chosen because it provides an hourly simulation of leaf-level photosynthesis, and algorithms that account for the effects of radiation intensity on canopy dimensions and specific leaf area. CROPGRO, calibrated on data of monocropped bush bean, captured, quite well, the effects of the strongly reduced radiation on leaf area, and total and pod dry matter in the most shaded bush bean row. This indicated the models’ applicability on other intercropping systems exhibiting high levels of shading. Under a lower level of shading, cultivar and ecotype parameters had to be calibrated individually for a respective row within the bush bean strip to achieve a high accuracy of the simulations. Model simulations aided in explaining the effects arising from different shares of direct and diffuse radiation on canopy photosynthesis. This is a very important point to be further explored as diffuse radiation remains a part of light distribution and photosynthesis hardly studied in general; and, in particular, becomes more important with the increasing impact of shading. The simulation of the light availability, plant growth and yield formation within the strip of maize can be handled in a similar way as described for the smaller crop, bush bean. Modifications of the light model and a suitable plant growth model are presented and discussed. In conclusion, the main outcomes of this thesis indicate that the selection of cultivars adapted to the modified light environment have the largest potential to increase the productivity of strip-intercropped maize and bush bean. The most important characteristics of suitable maize cultivars include: (i) a high potential of kernel set; (ii) a higher water stress tolerance; and, (iii) reduced canopy height and LAI. The importance given to each of the components would subsequently be determined by the local weather and management conditions and the shade tolerance of the neighboring crop. On the other hand, to optimize yields of the smaller shaded crop, we present two options: (i) to modify the co-growing period of the intercrops temporarily to alleviate light competition during shade-sensitive growth stages; and, (ii) to modify the cropping design spatially and/or select different maize cultivars to reduce shading to the tolerated degree during the respective growth stage of the smaller crop. When the shade tolerance during the respective growth stages is determined, the light model developed can be used to optimize the cropping system temporarily and spatially. In this thesis, a promising approach, which combines a specific light partitioning model with process-oriented monocropping plant growth models, was developed. All models included in the approach can be applied at any location, and their generic nature also facilitates the integration of other crops. These attributes present a highly valuable contribution to intercropping research as their future optimization will depend strongly on the efficiency of the research efforts given: (i) the complexity of the underlying processes that determine the productivity; and, (ii) the minor share of time and money invested in intercropping research. Intercropping research has to prevent reinventing the wheel by identifying aspects in common with and already studied in monocropping systems and focus on aspects particularly inherent to intercropping systems.
Development of management strategies to control soil erosion in field grown vegetables with a focus on white cabbage (Brassica oleracea convar. capitata var. alba L.)
(2014) Übelhör, Annegret; Claupein, Wilhelm
Soil erosion by wind and water is a widely recognized problem throughout the world. Field grown vegetables, such as white cabbage (Brassica oleracea convar. capitata var. alba L.), are particularly endangered by soil erosion because of high disturbance tillage, including deep inversion tillage by the mouldboard plough. Furthermore, wide row spacing and late soil covering by leaves intensify the problem. In light of this, field experiments were conducted from 2011 to 2013 in southwest Germany to investigate, develop and adapt soil erosion control strategies, in particular for field grown vegetables, with white cabbage as a model crop. Focus was placed first, on the use of row covers (fleece and nets), which are usually used as frost protection or for pest control in organic farming, and second, on the development and adoption of strip-tillage for field grown vegetables, which combine the benefits from conventional tillage (high yields) and no-tillage (erosion control). Artificial rainfall simulations demonstrated a high erosion control by row covers. Soil loss under fleece cover was reduced on average by 76% and under net cover by 48% compared to the uncovered control treatment. In 2012, fresh matter head yield was significantly higher under fleece (80 t ha-1) than control treatment (66 t ha1). The opposite was found in 2013, with highest yield under the non-covered control (64 t ha-1) and lowest under fleece cover (53 t ha-1). A higher prevalence of diseases under row covers compared to the control was only found in 2012 with Sclerotinia sclerotiorum on 4% of cabbage heads under fleece cover. Soil loss under strip-tillage during artificial rainfall simulations in 2011 was reduced by an average of 80% compared to conventional tillage (512 g m-2). In 2012, soil losses were reduced by an average of 90% under non-intensive strip-tillage and by 48% under intensive strip-tillage compared to conventional tillage (210 g m-2). The fresh matter head yield in 2011 and 2013 under strip-tillage (58 t ha-1 and 57 t ha-1, respectively) was similar to conventional tillage (59 t ha-1 and 58 t ha-1, respectively). In 2012, cabbage yield was significantly higher under strip-tillage (74 t ha-1) than under conventional tillage (65 t ha-1). The intensive strip-tillage treatments with broadcast and band-placed nitrogen fertilization did not show a yield increase. Yield potential under band-placed fertilized strip-tillage was, at 67 t ha 1 (2012) and 50 t ha-1 (2013), the lowest within the strip-tillage treatments. The CROPGRO cabbage model was evaluated for cabbage production under temperate European climate conditions. After calibration of main parameters of phenology and plant growth, the model showed a high accuracy with indices of agreement mostly above d=0.94. Observed dry matter cabbage head yields of the different years and different locations ranged between 6574 kg ha-1 and 11926 kg ha 1 which were predicted by the model with an accuracy of R2=0.98. Also the sensitivity analysis, conducted under different nitrogen fertilizer amounts and different fertilizer application strategies, generated realistic values from an agronomic point of view. Overall, row covers and strip-tillage seem to be suitable for minimizing the erosion risk in vegetable production. The hypotheses of high erosion control under row covers and strip tillage can be accepted. Due to the modified microclimate under row covers, the infestation with pests and diseases can increase and the influence on cabbage growth can result in either a yield increase or decrease. Based on the study results, there is no evidence that the intensive, double-tilled strip-tillage treatment or the band-placed nitrogen fertilization lead to a yield increase. The non-intensive strip-tillage with only soil preparation in autumn showed the highest yield potential within the strip-tillage treatments, with similar or even higher yields than under conventional tillage. Furthermore, the CROPGRO cabbage model is suitable to simulate growth parameters and yield potential of white cabbage under temperate European climate conditions. For the future, due to the prediction of increased frequency of heavy rainfall events, soil conservation will focus increasingly on intensive crop production and farmers, particularly vegetables growers, will be increasingly dependent on erosion control strategies. For this reason, the approaches presented in this thesis can contribute significantly to produce field grown vegetables in a sustainable way that promotes soil protection.
Equifinality, sloppiness and emergent minimal structures of biogeochemical models
(2019) Marschmann, Gianna; Streck, Thilo
Process-based biogeochemical models consider increasingly the control of microorganisms on biogeochemical processes. These models are used for a number of important purposes, from small-scale (mm-cm) controls on pollutant turnover to impacts of global climate change. A major challenge is to validate mechanistic descriptions of microbial processes and predicted emergent system responses against experimental observations. The validity of model assumptions for microbial activity in soil is often difficult to assess due to the scarcity of experimental data. Therefore, most complex biogeochemical models suffer from equifinality, i.e. many different model realizations lead to the same system behavior. In order to minimize parameter equifinality and prediction uncertainty in biogeochemical modeling, a key question is to determine what can and cannot be inferred from available data. My thesis aimed at solving the problem of equifinality in biogeochemical modeling. Thereby, I opted to test a novel mathematical framework (the Manifold Boundary Approximation Method) that allows to systematically tailor the complexity of biogeochemical models to the information content of available data.
Exploring and modelling the influence of spectral light composition on soybean (Glycine max (L.) Merr.)
(2019) Hitz, Tina; Graeff-Hönninger, Simone
The development of soybean cultivars for the climatic conditions in Europe is an urgent need in order to increase the European production and to decrease the dependence of imported soybean. A speed breeding system can accelerate the process of developing new cultivars by growing more generations per season in climate chambers. The project MoLED-Plant aimed towards the development of a speed breeding system for soybean under LED lighting. The major objectives of this thesis were to: (i) construct a three dimensional model of an LED chamber to simulate micro-light climate, (ii) develop a functional-structural plant (FSP) model of soybean and derive a blue photon flux density (BPFD) response curve from simulations, (iii) apply the FSP model with the integrated response curve for spectral optimization, (iv) explore the influence of BPFD under constant photosynthetic photon flux density (PPFD), and (v) disentangle the influence of red to far-red ratio (R:FR) and PPFD on the shade avoidance response (SAR). The objectives were fulfilled with a combination of FSP modelling in the Growth Grammar-related Interactive Modelling Platform (GroIMP) and plant experiments under multiple spectra in LED chambers. The presented LED chamber model was the first three dimensional environment, which was developed for spectral optimizations in indoor farming using FSP modeling. Measurements performed with a spectrometer in multiple heights and orientations were compared to simulations recorded with a virtual sensor at the same locations. The model was evaluated as a tool for assessment of spectral light heterogeneity under an alternative placement of the LED modules. Applying the model can assist in choosing the best chamber design and placements of LEDs to assure homogeneous light conditions. Subsequently, static soybean plants were incorporated into the chamber model. Comparison of light simulations and measurements from below the soybean canopy in four reconstructed scenarios assured a good simulation of micro-light climate. The model was applied to simulate the effect of an increased plant density in an experiment in the chamber. The simulations of light homogeneity in the experimental setup can assist in choosing the optimal design. The developed dynamic FSP model of soybean within the chamber model represents the first FSP model with an integrated response to BPFD. The soybean model was calibrated with data from BPFD experiments. From simulations, a common response curve of internode elongation to the perceived BPFD was derived for the second and third internode. The response curve was integrated in the model and was applied for spectral optimization in a chamber scenario with an alternative high reflective bottom material. The soybean response to BPFD under constant PPFD and the influence of R:FR and PPFD on SAR was explored by designing specific spectra from LEDs. Soybean experiments were performed under six levels of BPFD (60-310 µmol m-2 s-1) and constant PPFD (400 µmol m-2 s-1). Plant height and biomass decreased, leaf mass ratio increased and the ratio of stem biomass (internode plus petiole) translocated to the internode decreased under high BPFD. Three soybean cultivars were grown under nine light treatments to disentangle the effect of R:FR and PPFD. Internode elongation responded mainly to low PPFD with an additive effect from low R:FR, whereas petiole elongation was influenced to a great extent by low R:FR. In the context of SAR, petiole elongation can be seen as the main response to the threat of shade (high PPFD and low R:FR) and both petiole and internode elongation as the response to true shade (low PPFD and low R:FR). This thesis showed how PPFD, BPFD and R:FR work both independently, antagonistically and synergistically on the physiology and morphology of soybean. The increased insight in these responses can e.g. support crop breeding and spectral optimization in indoor farming. Furthermore, interesting and important objectives for future research were identified. These experiments should include physiological measurements for a deeper understanding of interactions and underlying mechanisms. Spectral optimization of indoor farming depends on the purpose of the production. For instance, a high BPFD of 260 µmol m-2 s-1 was optimal for speed breeding, whereas an intermediate BPFD would be preferable to increase biomass. Comprehensive investigation of spectral influence on plant physiology and morphology is necessary to fully utilize the spectral flexibility of LED lighting. The developed FSP model of soybean in a virtual LED chamber represents an important step towards utilizing the advantages of FSP modelling by simulation of a wide variety of scenarios. The model can be adjusted or extended depending on the purpose of the model. It can be calibrated for other crop species and the setting of the chamber dimensions can be changed.
Improved prediction of dietary protein use and nitrogen excretion in tropical dairy cattle
(2023) Salazar‐Cubillas, Khaterine; Dickhöfer, Uta
The overall objective of the present doctoral thesis was to evaluate the adequacy (i.e., accuracy and precision) of existing laboratory methodologies and modeling tools, originally designed for temperate systems, in predicting the nitrogen (N) supply and excretion of cattle in tropical husbandry systems. It was hypothesized that the adoption of laboratory methodologies and modeling tools from temperate systems without validating and adapting them for tropical systems may result in inaccurate estimations of N supply, utilization, and excretion, which will hamper the assessment of N use efficiency. An in vitro study was conducted to evaluate the adequacy of the chemical method (Sniffen et al., 1992; Kirchhof et al., 2010; Valdés et al., 2011) to predict rumen-undegraded crude protein (RUP) of tropical forages grasses and legumes (n = 23). The adequacy of the predictions was assessed by comparing them with RUP proportions measured in situ at rumen passage rates of 2, 5, and 8% per hour. Results showed that the RUP of tropical forages estimated with the in situ method can be predicted using the chemical method. However, regression equations developed for temperate forages were not adequate enough to predict RUP proportions of tropical forages consistently for all rumen passage rates. Instead, developed equations in the present thesis can be used to predict RUP proportion of tropical forages with a similar chemical composition than the reference forage sample set. A second in vitro study was conducted to evaluate the adequacy of the chemical (Sniffen et al., 1992; Zhao and Cao, 2004) and in vitro methods (Steingaß et al., 2001) to predict post-ruminal crude protein (PRCP) supply of tropical forages (n = 23). The adequacy of the PRCP supply with the chemical and in vitro methods were tested against PRCP supply estimated from in situ measurements at rumen passage rates of 2, 5, and 8% per hour and digested organic matter. Results showed that the in vitro method can be used as an alternative method to estimate PRCP supply in tropical forages at moderate to fast rumen passage rate but not at slow rumen passage rate. Available regression equations developed for temperate forages were not adequate enough to predict the PRCP supply of tropical forages from concentrations of chemical crude protein fractions. Instead, developed equations in the present thesis can be used to estimate PRCP supply of tropical forages with a similar chemical composition than the reference forage sample set. A third study was conducted to assess the adequacy of modeling tools to predict N excretion of cattle in tropical husbandry systems. These models, namely model A (based on AFRC, 1993), model G (based on GfE, 2001), and model I (INRA, 2019), were selected to predict fecal N (FN), urine N (UN), and total N (TN) excretion as well as FN fractions of dairy cows, heifers, and steers kept under typical tropical husbandry conditions. The adequacy of the model predictions was assessed against reference values of UN (total collection and creatinine method) and FN excretion (total collection, internal and external markers) (n = 392 observations). Adjustments were made to the models with the greatest potential to predict N excretion. The adjustments were focused on the input variables driving the variability in N excretion predictions, identified through a sensitivity analysis. None of the tested models predicts adequately the excretion of UN, FN, and of different FN fractions of individual cattle kept under tropical conditions. Instead, model I in the present thesis, adjusted for increased efficiency of rumen microbial crude protein synthesis and reduced intercept of FN prediction, can be used to estimate FN and TN excretion of individual cattle kept under tropical conditions. The findings from the present thesis partially support our hypothesis. The adjustment of laboratory methodologies, such as the chemical method used to estimate the protein value of temperate forages, to tropical forages, results in more adequate estimates of the proportion of RUP and PRCP supply of tropical forages. Model I is, therefore, able to predict the N excretion of cattle more adequately in tropical husbandry systems, because it is sensitive to differences in the RUP proportion and PRCP supply. In addition to increasing the adequacy of these input variables, adjustments made to the microbial protein synthesis and intercept of the FN excretion of model I results in a more adequate prediction of N excretion by cattle in tropical husbandry systems. However, not all adjustments to laboratory methodologies and modeling tools from temperate systems yielded adequate predictions. Specifically, challenges remained in predicting RUP proportion and PRCP supply for tropical forage legume with slow rumen passage rates, as well as urinary N excretion in cattle with low N intakes. Consequently, further research is required to identify the factors contributing to their poor adequacy.
Investigation and Modeling of the Optimization Potential of Adapted Nitrogen Fertilization Strategies in Corn Cropping Systems with Regard to Minimize Nitrogen Losses
(2005) Link, Eva Johanna; Claupein, Wilhelm
The aim of this study was the "Investigation and Modeling of the Optimization Potential of Adapted Nitrogen Fertilization Strategies in Corn Cropping Systems with Regard to Minimize Nitrogen Losses". The background for the investigation could be seen in the increasing number of environmental pollution by agricultural land use. The dissertation was embedded in the context of the Graduiertenkolleg "Strategies to Reduce the Emission of Greenhouse Gases and Environmental Toxic Agents from Agriculture and Land Use" at the University of Hohenheim. The objective of this Graduiertenkolleg was to develop methods for quantifying and modeling the origin and the emission of greenhouse gases and environmentally toxic agents from agriculture and land use and for assessing them economically in the sense of practicable avoidance strategies. In order to determine the optimization potential of adapted nitrogen fertilization strategies in corn the study was organized in the following parts: 1. Investigation of the spatial variability and temporal stability of corn grain yield on three fields in the Upper Rhine Valley. 2. Determination of underlying yield-limiting factors in each field by the use of simple and complex models. 3. Development of adapted nitrogen fertilization strategies in consideration of the yield variability and the underlying yield-limiting factors. The area of investigation was located in the Upper Rhine Valley, which is characterized as a region with intense corn cultivation. At the same time this region belongs to the most important water protection areas in Europe. Thus, a conflict between agricultural land use associated with high fertilizer inputs on one hand and the protection of water bodies on the other hand rose, because measured nitrate concentrations in the groundwater increased constantly within the last decades. The study was conducted on three farm fields in the boundary of Weisweil, which is located northwest of Freiburg, Germany. Since 1998 the three fields were planted continuously with corn. In a 7-year field experiment spatial variability and stability of yield could be indicated. The determined yield pattern in each field raised assumptions about varying growth conditions within and among the fields. Thus, on the one hand the corn yield seemed to be influenced by temporal variations in cultivar, climate and management and by spatial and temporal variation of possible yield-limiting factors like nutrient availability or water supply on the other hand. In order to optimize management strategies the underlying yield-limiting factors causing the spatial and temporal yield variability needed to be determined in these three fields. Whereas plant yield parameters did not explain the existing yield variability very well, soil characteristics were identified as the major factors affecting the observed yield variability in all three fields. Significant relationships were found between combinations of soil nutrient levels, soil characteristics and yield. Based on these results, it appeared that soil characteristics were the primary factor affecting spatial yield variability in the three farmer fields in the Upper Rhine Valley. However, some of the spatial yield variability remained unexplained by simple regression analysis. In a more complex approach crop growth models were implemented to simulate the spatial yield variability within the field and to get information about the underlying yield-limiting factors. Therefore the process-oriented crop growth model APOLLO was implemented to evaluate the causes of spatial yield variability of corn in the three fields. APOLLO (Application of Precision Agriculture for Field Management Optimization) is a precision farming decision support system, which is based on the CERES and CROPGRO family of crop growth models and includes different soil parameter to calibrate the model. In general the APOLLO model performed well in simulating spatial yield variability in the fields. The results indicated that the spatial yield variability was mainly affected by a varying restrictive layers and reduction of root growth within the three fields. The correlation between simulated and measured yields provided information about the strength of the soil parameter affecting the yield within these fields. The calibration results were influenced by the grid size. Whereas smaller grids provided more random monitor yield data, larger grids provided a more representative set of yield monitor data, due to the coverage of a larger area. Consequently, the APOLLO model performed better when yields belonging to larger grids were used for model calibration. The applicability of the APOLLO model can be extended by developing prescriptions for different management strategies and thus enhancing the possibilities of successfully implementing site-specific management strategies. Thus, APOLLO was used to simulate the current uniform nitrogen management strategy of the producers in Weisweil over a 28-year period. Additionally an optimum uniform management and an optimum variable-rate management were developed and simulated. For these strategies also the different weather pattern were taken into account. All three strategies were evaluated based on the simulated yield, the simulated leaching potential and the simulated economics. It was obvious, that variable-rate nitrogen fertilization strategies were most advantageous compared to the other strategies, especially, when the nitrogen application rates were differentiated for dry, normal and wet weather scenarios. Adapted nitrogen fertilization strategies, as optimum uniform management and variable-rate management indicated a potential to reduce the amount of nitrogen, which is left in the soil after harvest, and associated that the potential nitrate leaching was reduced. In a case study the cumulative denitrification under these weather and fertilization scenarios over the growing season was simulated. The results indicated a reduction of cumulative denitrification under adapted fertilization strategies when compared to current uniform management. Summarizing, the results of this study suggest, that the implementation of adapted fertilization strategies (especially the variable-rate management of nitrogen) could lead to a reduction of nitrogen losses, as nitrogen leaching and nitrogen emissions could be minimized. Generally, the optimization potential for adapted nitrogen fertilizer strategies (optimum uniform management and variable-rate management) could be improved for cropping systems that were associated with higher risk for nitrogen losses.
Investigation of fluidised bed coating : measurement, optimisation and statistical modelling of coating layers
(2017) van Kampen, Andreas; Kohlus, Reinhard
Fluidised bed coating describes a process to encapsulate particles. The coating layer is applied in order to protect the core material from chemical reactions with the environment, to control the release of drugs or to mask bad taste. Depending on the application, the coating layer must fulfil various quality requirements, such as completeness, homogeneity and minimum layer thickness. The measurement of the coating layer thickness is therefore necessary in order to determine appropriate parameters for an optimal coating process. This, however, is difficult in the investigated core particle size range of 100 to 500 μm with a coating layer thickness of around 10 μm. Fluorescent imaging of sliced particles or imaging of optical slices using confocal laser scanning microscopy are possible ways to make the coating layer visible and to measure the coating layer thickness using image analysis techniques. This leads to detailed images of the coating layer and an accurate description of the coating layer thickness distribution, but is rather time consuming due to tedious sample preparation and long image acquisition times. Consequently only relatively few particles are measured and used to draw conclusions on the population. Other methods like measurement of the change of particle size using laser diffraction or assessment of the volume ratio of coating to core material usually only deliver the mean thickness and no information on completeness and homogeneity of the coating. In the first part of this thesis a quick method for coating thickness measurement was developed based on a dissolution test. Sodium chloride was used as a core material and maltodextrin DE21 was used as a coating material. When dissolved in deionised water, sodium chloride raises the conductivity in contrast to maltodextrin. Therefore, the measurement of conductivity can be used to assess the dissolution curve of the core material. The coating layer delays the dissolution of the core and by comparison with the dissolution curve of pure sodium chloride the coating thickness distribution can be assessed by deconvolution. It was shown that this method is well reproducible and delivers reliable results comparable to other methods. The method is fast, which enables the measurement of many samples with replicates and using appropriate sample division should provide a good representation of the population. The shape of the thickness distribution allows the quantification of the three aforementioned quality parameters. The method was therefore used in the second part of this thesis in order to investigate the coating process using design of experiments. The four factors spray rate, air temperature, air velocity and concentration of the coating solution were investigated using a central composite design of experiments. The dissolution method was used to assess the coating quality. The particle size distribution was measured in order to quantify the agglomeration rate and the mass of deposited coating material was assessed by quantifying a tracer colour in order to assess the efficiency of the process. Significant quadratic models were fitted to all response variables. These were successfully used to find a local optimum within the investigated parameter space which allowed the formation of an optimal coating layer within a short time frame. The results of the previous investigations showed that the thickness distribution can be well described by a Weibull distribution. Furthermore, it was possible to confirm effects that were previously described in the literature, i.e. that a low concentration of the coating solution leads to more homogeneous coating layers. In order to give a general description of the coating layer, a statistical model of the coating thickness distribution was developed in the third part of this thesis and verified by a Monte-Carlo simulation. The model reproduces the experimentally determined effect of the concentration of the coating solution qualitatively and is able to calculate the mean thickness distribution with given concentration, contact angle, sprayed mass and core particle and droplet size. Appropriate adjustments of these parameters lead to a good agreement between the model and measured thickness distributions of real experiments. It was concluded that predominant spray drying of small droplets and an increase of concentration of the remaining droplets due to pre drying negatively affects the homogeneity of the coating layer. It was further confirmed that the Weibull distribution can be used to describe the coating layer thickness in the investigated thickness range. The thickness distribution transitions from the Weibull distribution to a normal distribution as the coating becomes thicker. Thin coatings with defects can be described by a clinched Weibull distribution containing the uncoated area fraction as an offset.
Land use management under climate change : a microeconomic analysis with emphasis on risk
(2018) Reinmuth, Evelyn; Dabbert, Stephan
This cumulative dissertation was conducted under a grant from the German Research Foundation (DFG) for the research group FOR 1695 - “Agricultural Landscapes under Global Climate Change – Processes and Feedbacks on a Regional Scale”. The goal of the sub-project from which this dissertation stems from was to explore, extend and strengthen the scientific basis for learning and risk strategies and the adaptation behavior of farmers’ economic planning decisions in crop production under the influence of climate change. The integrated bioeconomic simulation model FarmActor, was to be used as an experimental tool to develop an interdisciplinary methodological approach supported by empirical work in two study regions in Southwest Germany, the Kraichgau and the Swabian Alb. This dissertation examines risk in the context of land use management and specifically crop production. Risk in this context is related to how outcome distributions are affected by climatic influences. Risk strategies assess these contributions and account for them in the resulting decisions. The thesis is written as a cumulative dissertation and is composed of five articles. Four articles have been published by peer-reviewed journals. A fifth article has been published as a peer-reviewed conference proceeding. The article at fifth place represents the results of the main focus of this dissertation as presented in the following. Available economic models assume that farmers assess climatic risks only through yields or costs when building their land use management risk strategy for crop production. However, the available methodological approaches have been criticized for either under- or overestimating farmers’ actual behavior. In reality, and as a basis for field allocation planning, farmers have additional knowledge from monitoring crop development throughout the whole season. Yield is actually just the last point in a long sequence of (economic) evaluative observations about the production process. This influences how farmers define not only the riskiness of a yield distribution but also its costs. We hypothesize that, because it is not possible to methodologically integrate process evaluations in economic planning decisions, models lack performance, and as a consequence, it is very difficult to conduct proper research on the climate’s influences on land use management decisions. In this original research, we present a newly developed downside risk measure based on evaluations throughout the production process that can be included in the planning process as an additional parameter—so-called Annual Risk Scores. A comparative static analysis was performed to demonstrate how ARS scores assess future climatic conditions in the example of winter wheat production in the Kraichgau region as supported by empirical data. It was shown that the mechanism is sensitive to different climatic conditions. Furthermore, the ARS scores provide a different picture of climatic influence compared to an analysis based only on yields. The last article presented in this dissertation represents an integrative review that promotes more efficient model development and the reuse of newly developed methodologies in the field of integrated bio-economic simulation models. The review is based on lessons learned from working with the simulation model. Thus, the intended and outstanding full implementation of the ARS mechanism is presented in the last part of the synthesis, where we advise including the ARS scores as another constraint in the field allocation mechanisms of the FarmActor model. This is expected to improve the integration of both bio-physical and economic dimensions for complex integrated bio-economic simulation models.
Measuring and modelling of soil water dynamics in two German landscapes
(2018) Poltoradnev, Maksim; Streck, Thilo
The soil water regime is focus of various disciplines including agricultural sciences, hydrology, weather forecast and climate modelling. As an inherent part of land surface exchange processes, the dynamics of soil water content (SWC) is simulated in distributed hydrological models and land surface models (LSM). The accuracy of the simulated SWC directly influences the simulation outcome and its performance. Biases in modelled temporal SWC dynamics and its spatial distribution lead to errors in evapotranspiration, runoff, cloud and precipitation simulations. The main objective of my thesis was to study the factors that control the SWC dynamics and its spatial variability. Long-term measurements from the soil moisture networks Kraichgau (KR) and Swabian Alb (SA) provided the data basis of this study. SWC was sensed based on the Time Domain Transmission (TDT) technique. In each region, 21 measuring locations were distributed across three spatial domains: an inner domain 3 km × 3 km (5 stations), a middle 9 km × 9 km (8 stations), and an outer domain 27 km × 27 km (8 stations). The sizes of the three domains correspond with typical grid sizes of coupled atmosphere-LSM models. All stations were mounted on cropped agricultural sites. Each station was equipped with a TDT sensor, installed 15 cm deep into the soil, a rain gauge and a remote transfer unit. After adjusting the sensor networks, an in-situ field calibration was performed to derive pedotransfer and site-specific calibrations for TDT soil moisture sensors. The chemical and physical analysis of soil samples collected at each station revealed that soil bulk density influences in both regions the TDT readings. Moreover, the pedotransfer calibrations included electrical conductivity in KR and silt fraction and organic nitrogen content on SA. These variables are relatively easy to measure. Accordingly, the pedotransfer calibrations derived in this study are a quick possibility to calibrate TDT sensors in areas with similar soil properties as in KR and SA. Nevertheless, the site-specific calibrations performed the best and were therefore used for further data analysis. In the second study, a three-year record of SWC and rainfall was evaluated. The response of the regional mean (theta) of SWC to a rain event was influenced by the seasonal water balance (SWB). In KR, the relation was more pronounced for positive SWB and less for neutral and negative SWB. On SA, where SWB was highly positive in all three years, the response of theta to rainfall was always strong. At the seasonal scale, the relationship between the spatial standard deviation of SWC (sigma) and theta was investigated through sigma-theta phase-space diagrams. The results show that with decreasing SWC sigma-theta data pairs are approaching sigma at the permanent wilting point (sigma-thetawp). With increasing SWC, in contrast, sigma-theta data pairs are moving towards sigma at saturation (sigma-thetas). These two points were termed anchor points. The sigma-theta relationships formed combinations of concave and convex hyperbolas reflecting the variability of soil texture and depending on sigma in relation to the anchor points. At the event scale, hysteresis in the sigma-theta was observed. Most sigma-theta clockwise hysteresis cases occurred at an intermediate and intermediate/wet state of SWC. Among the factors that trigger the initiation of a sigma-theta hysteretic loop, the present study revealed the following: rainstorms with spatially highly variable intensities (threshold rainfall intensity of 1.1 ± 0.6 mm and 2.9 ± 2.8 mm for KR and SA, respectively), preferential flow and, possibly, hysteresis in soil water retention curves. Based on these results, the following hypothesis was formulated: sigma-theta phase space diagrams are useful to test whether hydrological models or land surface models (LSMs) capture the realistic range of spatial soil water variability. The concept was tested with the Noah-MP LSM. Observations obtained from KR and SA soil moisture networks over a three-year period from 2010 to 2012 were used to build up the sigma-theta phase-space. The study included two different setups used to compute the hydraulic conductivity and the diffusivity: 1) the default setting: the Clapp and Hornberger approach, and 2) the van Genuchten-Mualem functions. The default model parameterization was stepwise substituted with site-specific rainfall, soil texture, leaf area index (LAI) and green vegetation fraction (GVF) data. The atmospheric forcing was obtained from eddy covariance stations located in the regions. Although the model matched observed temporal theta dynamics fairly well for the loess soils of KR, it performed poorly in the case of the shallow, clayey and stony soils of SA. The best match was achieved with the van Genuchten-Mualem functions and site-specific rainfall, soil texture, GVF and LAI. Nevertheless, the Noah-MP LSM failed to represent the spatial variability of SWC. In most cases, the simulated sigma-theta data points were located below the bottom edge of the envelope, which indicates that the model smooths spatial variability of soil moisture. This smoothing can be mainly attributed to missing topography and terrain information, inadequate representation of the spatial variability of soil texture and hydraulic parameters, and the model assumption of a uniform root distribution.