Browsing by Subject "Pflanzenwachstumsmodell"

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Developing cropping systems for the ancient grain chia (Salvia hispanica L.) in two contrasting environments in Egypt and Germany
(2020) Mack, Laura; Graeff-Hönninger, Simone
Chia (Salvia hispanica L.) seeds have been revived as functional “superfood” for human nourishment especially for vegan and vegetarian diets and are becoming increasingly widespread and present in new food products in Europe. The seeds are beneficial because of being gluten-free, containing antioxidants and a high concentration of α-linolenic acid, and having a high content of dietary fiber and high-quality protein. Chia is originally adapted to short-day conditions and grows naturally in tropical and subtropical environments. Nevertheless, it can survive under water stress and could, therefore, be cultivated in arid regions. Egypt has been classified as a water-scarce state. Due to its drought tolerance, chia might contribute to saving the scarce source “water” in Egypt and offer the chance to export these high value seeds, generating foreign exchange for reimporting e.g. wheat characterized by a higher water demand. Worldwide, the biggest problems and key challenges under climate change (CC) are water and food security in arid and semiarid regions. In the future, CC and water scarcity will significantly threaten agriculture and sustainable development. A rising population requires on the one hand an increase in food grain production, but also a change toward environmentally sound sustainable agriculture. Chia has been suggested as a favorably economic alternative for common field crops sustaining diversification and stabilization of the local agricultural economy. However, broad experience in growing chia in new environments is missing. The agronomic management has not been improved from formerly small-scale production systems. Most of the previous studies focused on seed characteristics. Information on fertilization, plant protection, and improved varieties is scarce, which are reasons for its low productivity in the countries of origin. Field experiments were conducted at the experimental station “Ihinger Hof” of the University of Hohenheim in southwestern Germany from 2015 to 2017 and in Egypt during the cropping season 2015 to 2016 at SEKEM’s experimental station located 50 km Northeast of Cairo. The present doctoral thesis was based on a project embedded in the graduate school Water-People-Agriculture (WPA) at the University of Hohenheim funded by the Anton-&-Petra-Ehrmann foundation that focuses on key water issues and water related challenges of todays society. On a final note, the main results of this thesis provide further information and expanded knowledge on chia cultivation in two contrasting environments (including a desert region) out of its center of origin. Overall, the current doctoral thesis presents a combined approach of experimental field research and crop modeling to support the optimization of farming practices of chia in new environments. A universal and nondestructive LA estimation model for chia was developed. Further, the CROPGRO model was adapted for chia to provide a preliminary model for a realistic simulation of crop growth variables. The approaches presented in this thesis may contribute to testing new environments for chia cultivation and to improving its production. Moreover, this study helped to develop further general model source codes to simulate the growth of tiny seeds. The adaptation to other Salvias should be much easier with this developed model. Future research requirements and issues requiring model improvement such as N-response and the development of code relationships that can simulate parameters of seed quality could improve the plant growth model for chia.
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.