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Comparison of variable liming strategies in organic farming systems using online pH-measurements
(2011)
In organic farming, soil pH is one of the most important soil characteristics affecting nutrient availability, soil microbial activity and plant growth. Using the soil pH mapping sensor system Veris MSP, detailed information on in-field variability of soil pH can be obtained enabling spatial variable lime application. Scenario calculations for an organically managed field in Germany reveal that compared with the standard farm practice (i.e. uniform liming rate) variable lime application does not lead to higher costs while soil pH is optimized in different field zones resulting in increased crop productivity. Using two different lime qualities increases liming costs moderately but gives farmers the chance to increase pH quickly in extreme low pH areas.
Transition road maps – an investigative approach to map the daily life consumption of individuals
(2014)
The present paper aims at investigating an innovative approach to guide consumers’ daily life choices in Germany towards a more sustainable way of acting. This should be achieved by introducing a new concept: transition road maps. Transition road maps bear the capability of illustrating courses of consumption behaviour without being prohibitive. These schemes foster self-determined behaviour and encourage the consumer to rethink and restructure his or her habits of consumption, with a focus on sustainability. The innovative thought is, not to simply stick to the usual triad of spheres of activity, consisting of nutrition, mobility and housing. Instead further aspects of consumers’ daily routines are considered, such as leisure activities, time usage or financial activities. Moreover the transition road maps are based on a new ideology of combining and connecting the qualitative algorithm of time use, financial spending and resource impact of social practices in the area of private consumption. In the long-term, the transition road maps could e.g. be used in sustainability communication or consumer counselling.
Between Ekaterinburg and Nowosibirsk, in the Western Siberian grain belt, spring wheat is grown on fertileChernozem soils. Field and farm sizes are large but the land-use intensity per area is low compared to CentralEurope. Fertilizers and pesticides are applied only in low to moderate quantities and yields range between 10and 20 dt ha-1 . We studied the arable weed flora in the northern forest steppe zone of Tyumen region using arandomized sampling design. Surprisingly, the species richness was only moderate, on average 9.8 ± 3.8species per 100 m². Compared to weed communities of Bashkiria (Southern Ural) and less intensively usedarable land of Central Europe these numbers are rather low. Moreover, most of the recorded species werecosmopolitans or widely distributed throughout the temperate zone. We suggest that the land use intensitywas high enough to reduce the density of a number of weed species in a way that they were not registered byour random sampling design. The limited conservational value of the weed vegetation of large grain fields inTyumen leads to the conclusion that if intensification of land use is unavoidable, it should be directed to arableland and not to ex-arable land or ancient grassland, which is of higher conservation value.
This study identifies and evaluates factors for success in innovation work in the Bavarian dairy farming industry. The research is based on an analysis of innovation system theories and a comparison with innovation work in the Dutch dairy sector. Dutch dairy farming is characterized by high productivity and technical efficiency at the farm level. Moreover, important developments in dairy farming have originated in the Netherlands. Therefore, this study delves into the systemic background of the successful innovation work in the Netherlands and makes a comparison with Bavaria. The main result of this study is that innovation work in the Bavarian dairy farming sector is lacking in two respects: end-user (farmer) integration and within-sector cooperation.
German farmers are required by law to regularly self-assess the welfare of their animals. The project Q Check is aiming at developing a system that will assist farmers to objectively assess animal health and welfare in dairy cows. For this reason, a quarterly report will be compiled from animal-based key indicators to give an overview of the on-farm situation. The anonymised and aggregated reports can also be used for national animal welfare monitoring: Continuous collection of these key indicators enables the summary and publication of figures reflecting the current animal health and welfare status and progressions at federal state and at national level. Q Check is based on four data recording and analysis systems, which are already established in Germany and implemented on a national level. Out of these systems, the most suitable indicators to describe herd health have been selected by 215 experts within a twostage Delphi study. In addition, over 50 face-to-face interviews with stakeholders related to the German dairy sector have been performed in order to take into account the socio-scientific point of view. To complete the process, the selected indicators are currently being checked against mass data and hence tested for suitability regarding monitoring purposes. An automatic farm-specific evaluation of animal health, based on verified indicators, will provide support to farmers in fulfilling their legal requirements and in identifying weak points on the individual farms. A benchmarking system will be set up which will allow tracking the individual herd health indicators in the same farm in their course over time and compared with similar farms. These routinely provided horizontal and vertical statistics will facilitate targeted intervention and support objectified management decisions, implying that dairy farmers can benefit in several respects. In the course of the project, new tools for determining the risk of ketosis in the scope of milk recording will also be validated and implemented at national level to enhance monitoring of this major disease complex. The results of these nationwide, systematic investigations will contribute substantially to objectifying the discussion about the health and welfare situation of dairy cows.
In this paper, we evaluate the application of Bayesian Optimization (BO) to discrete event simulation (DES) models. In a first step, we create a simple model, for which we know the optimal set of parameter values in advance. We implement the model in SimPy, a framework for DES written in Python. We then interpret the simulation model as a black box function subject to optimization. We show that it is possible to find the optimal set of parameter values using the open source library GPyOpt. To enhance our evaluation, we create a second and more complex model. To better handle the complexity of the model, and to add a visual component, we build the second model in Simio, a commercial off-the-shelf simulation modeling tool. To apply BO to a model in Simio, we use the Simio API to write an extension for optimization plug-ins. This extension encapsulates the logic of the BO algorithm, which we deployed as a web service in the cloud.
The fact that simulation models are black box functions with regard to their behavior and the influence of their input parameters makes them an apparent candidate for Bayesian Optimization (BO). Simulation models are multivariable and stochastic, and their behavior is to a large extent unpredictable. In particular, we do not know for sure which input parameters to adjust to maximize (or minimize) the model’s outcome. In addition, the complex models can take a substantial amount of time to run.
Bayesian Optimization is a sequential and self-learning algorithm to optimize black box functions similar to as we find them in simulation models: they contain a set of parameters for which we want to identify the optimal set, they are expensive to evaluate, and they exhibit stochastic noise. BO has proven to efficiently optimize black box functions from varius disciplines. Among those, and most notably, it is successfully applied in machine learning algorithms to optimize hyperparameters.
Studies on nutrition have historically concentrated on food-shortages and over-nutrition. The physiological states of feeling hungry or being satiated and its dynamics in food choices, dietary patterns, and nutritional behavior, have not been the focus of many studies. Currently, visual analytic using easy-to-use tooling offers applicability in a wide-range of disciplines. In this interdisciplinary pilot-study we tested a novel visual analytic software to assess dietary patterns and food choices for greater understanding of nutritional behavior when hungry and when satiated. We developed software toolchain and tested the hypotheses that there is no difference between visual search patterns of dishes 1) when hungry and when satiated and 2) in being vegetarian and non-vegetarian. Results indicate that food choices can be deviant from dietary patterns but correlate slightly with dish-gazing. Further, scene perception probably could vary between being hungry and satiated. Understanding t he complicated relationship between scene perception and nutritional behavioral patterns and scaling up this pilot-study to a full-study using our introduced software approaches is indispensable.
To assess the effect of intercropping on malting quality a field trial with spring barley (Hordeum vulgare) and legume (pea) as well as non-legume (camelina and linseed) intercrops in two additive seeding ratios as well as sole cops was established in 2017 at the organic experimental station of University of Applied Sciences Osnabrück in North-Western Germany. Two tested malting barley cultivars (cv. Marthe and cv. Odilia) showed different performance, but all variants achieved brewing quality. Results after two years indicate that linseed and camelina were able to limit protein content. For best land-use efficiency of malting barley production intercropping with linseed showed best results. Mixed intercropping can help to promote internal efficiency loops and is therefore a promising sustainable intensification strategy for more resilient future crop production under changing climate conditions.
Nitrogen (N) pollution of groundwater bodies is often a result of high livestock densities combined with use of mineral N fertilisers in Northwest Germany, specifically in combination with sandy soils and high amounts of precipitation. Organic agriculture is discussed as an alternative management practice reducing nitrogen losses due to area-based livestock densities and waiving of mineral N fertilisers. A field trial with integrated ceramic suction cups over three years showed potential for reduced N loads under conventional management specifically with organic fertilisation. Now, the field trial is under transition into organic farming with promising additional benefits for drinking water quality and the great potential to develop optimised N management strategies.
Animal husbandry methods also play an important role in public discussion, as animal welfare is often valued in society by visual perceptions. In this context, there is often an idealized idea of livestock husbandry and nutrition, which is staged by ideal-typical images. In the minds of many citizens, nature-loving images trigger a positive imagination that results from the longings of urban living conditions. Media and stakeholder analyses indicate that the use of straw in livestock husbandry and nutrition also has a positive impact on the welfare of livestock. According to this, straw is preferred by the public for more animal welfare. But what is not considered is the fact that the straw must be of impeccable hygienic quality
Animal husbandry methods also play an important role in public discussion, as animal welfare is often valued in society by visual perceptions. In this context, there is often an idealized idea of livestock husbandry and nutrition, which is staged by ideal-typical images. In the minds of many citizens, nature-loving images trigger a positive imagination that results from the longings of urban living conditions. Media and stakeholder analyses indicate that the use of straw in livestock husbandry and nutrition also has a positive impact on the welfare of livestock. According to this, straw is preferred by the public for more animal welfare.
But what is not considered is the fact that the straw must be of impeccable hygienic quality. Fungal infestation and the formation of mycotoxins in straw can cause diseases in livestock with consequences for animal welfare.
The first evaluation of a perfect straw quality also takes place in science through sensory tests, i.e. through smell, grip, colour and impurities. Only in the case of abnormalities in the sensory tests are further examinations indicated, such as microbiological examination procedures.
The hygienic properties of straw were examined on the basis of these assessment criteria. In addition to the microbiological-hygienic tests, the sensors of the straw were also tested.
The results show that there are no abnormalities in the sensory examination of the hygiene status. This was to observe an impeccable hygiene status.
However, the microbiological-hygienic investigations showed that the straw had microbiological as well as mycotoxin loads above the orientation values. This can have negative health effects, such as diseases for farm animals.
The scientific results led to the conclusion: The public discussion about animal welfare, which is often conducted primarily on the basis of visual impressions, could gain in scientific resilience if it includes objective results such as microbiological analyses in addition to images in order to evaluate animal welfare in livestock farming
Boron dynamics in a peat-based growing medium and its impact on the growth of basil (Abstract)
(2021)
The production of food-grade substances and complex biocatalysts used as additives or active ingredients – mainly for food applications – can be achieved in the eukaryotic expression system of Aspergillus niger. Food proteins or food enzymes e.g., casein, ovalbumin, phytase or glucoamylase are highly complex polymers. Most of them could be used as nitrogen or energy source for animals and humans, while others are industrial relevant biomass-degrading enzymes used for biological waste processing and food production.
However, the successful production of novel recombinant proteins can be challenging, resource- and time consuming. Therefore, A. niger mutant libraries are needed to understand the “adjusting screws” to produce high yields of recombinant proteins, preferably even in a kind of generic, transferable system. In order to establish a universal and multipurpose expression platform, there is the need to overcome the lack of high throughput assays first.
To tackle this problem, we designed a modular, quantitative and feasible high-throughput screening system to express and screen recombinant proteins regarding their stability and functionality in A. niger. For this purpose a dual-luciferase reporter gene system, which is applicable in small scale will be established for A. niger. After the generation of an A. niger secretion mutant library, the system will be transferred and tested to other proteins of interest. The technology can be integrated into bio-regenerative life support systems for the autonomous production of e.g., food, food additives and food enzymes on earth as well as in deep-space.
Perceptions of German consumers regarding methods for fortifying foods with iodine (Abstract)
(2022)
Taking the transdisciplinary research study “Green fingers for a climate resilient city”, funded by the German Ministry of education and research (BMBF), as an example, this paper follows the hypothesis that processes of landscape planning and designing multifunctional green spaces and processes of co-creation need to be combined to stimulate climate resilient city transformation. The findings are that efforts to combine these processes benefit from making complex climate-resilient city planning accessible for people of different professional backgrounds. The paper showcases how storytelling (Schmidt 2019), mapping (Langner 2009) and guided walks (Schultz 2019) are means to mutually engage with, perceive and understand multifunctional green spaces, inspire ownership, and build capacity for the city’s climate-resilient transformation.
When the ECLAS Conference took place in 1972 western societies were undergoing profound change: They transformed from industrial to postindustrial societies – the so-called service societies. 50 years later, the knowledge society is emerging: Knowledge is considered the key resource of this era. Digitalization and widespread dissemination of ICT allow information to be obtained anywhere anytime. This has severe implications for individual lifestyles and everyday practices. Different aspects of living, learning and working are no longer bound to physical limitations but can be enhanced by or even transferred to the virtual space. So being on the move today means travelling in hybrid spaces. We call this the space and practice “en route”.
At the University of Applied Sciences Osnabrück we explore the following questions:
What does “en route” mean and look like in landscapes of higher education?
How is it perceived individually?
(How) can landscape architecture shape it?
Our transdisciplinary research project EN ROUTE aims to meet current challenges at universities (e.g. digitalisation, sustainable development) with a comprehensive understanding of space and practices “en route”. In a transdisciplinary process, researchers from various disciplines – landscape architecture, geography, urban planning, business administrations and marketing, energy technology and computer science – develop concepts and strategies for sustainable and digital mobility in the higher education sector. New “EN ROUTE” types provide insights into the individual production and utilization of spaces “en route”.
The campuses of the University of Applied Science Osnabrück as well as the virtual and physical space network of its members serve as research example. Initial findings will be presented at the conference. While the ECLAS conference in 1972 focused on physical scales, landscape architecture has to reflect them critically and ask: What could be an innovative understanding of spaces “en route”?
The contribution follows the hypothesis that the concept of transformative resilience can be a driver in transdisciplinary processes bringing together landscape planning and landscape design. Combining processes of generating, structuring and spatializing knowledge on landscape functions and designing visions for sustainable landscapes on different scales benefits from the creative use of mappings.
Taking the transdisciplinary research study “Green fingers for a climate resilient city”, funded by the German Ministry of education and research (BMBF), as an example, this paper follows the hypothesis that processes of landscape planning and designing multifunctional green spaces and processes of co-creation need to be combined to stimulate climate resilient city transformation. The findings are that efforts to combine these processes benefit from making complex climate-resilient city planning accessible for people of different professional backgrounds. The paper showcases how storytelling (Schmidt 2019), mapping (Langner 2009) and guided walks (Schultz 2019) are means to mutually engage with, perceive and understand multifunctional green spaces, inspire ownership, and build capacity for the city’s climate-resilient transformation.
Iron deficiency is a global issue and can lead to a variety of clinical pictures. The biofor-tification of vegetables with iron could complement the existing portfolio of iron-rich products, thus improving iron supply in the long term. In order to determine whether the iron-biofortified vegetables could meet this demand and would address appropriate target groups, a quantitative online survey was conducted in Germany. Based on 1000 consumer responses, a cluster analysis was performed. The results showed a four-cluster solution. The first cluster was holistically engaged, the second was fitness-affine but health unconcerned, the third cluster consists frugal eaters with a focus on medical prevention, and the fourth cluster are hedonists. No cluster focused its consumption on iron-enriched products, but instead all developed an individual mix of the three product groups.
SimBO is a flexible framework for optimizing discrete event-driven simulations (DES) using sequential optimization algorithms. While specifically designed for Bayesian Optimization (BO) in the context of DES, SimBO can be applied to any black-box problem with other optimization algorithms. The framework consists of four encapsulated components - the black-box problem, the sequential optimization algorithm, a database for experiment configuration and results, and a web-based graphical user interface - that communicate via well-defined interfaces. Each component can be run in different environments, allowing for cooperation between different hardware- and software configurations. In our research context, SimBO’s architecture enabled BO algorithms to be run on a high-performance cluster with GPU support, while the simulation is executed on a local Windows machine using the Simio simulation software. The framework’s flexibility also makes it suitable for evolving from a research-focused tool to a production-ready, cloud-based optimization tool for modern algorithms.
Within the consortium “Experimentation Field Agro-Nordwest”, a practical concept for knowledge and technology transfer of digital competence in agriculture was created. For this purpose, the web-based e-learning system “SensX” was set up, consisting of videos, presentations and instructions. In addition, the classical e-learning concept was extended by data sets, student experiments and sensor data of plants acquired by a remote phenotyping robot. This resulted in a massive open online course (MOOC), which was tested with agricultural and biotechnology students in higher education at the University of Applied Sciences Osnabrück over two years. The evaluation process of “SensX” included an empirical survey, qualitative interviews of the participating students by an external institution and an evaluation of the concept by the lecturers.
Computer-image processing becomes more and more important in the analysis of data in biological and agricultural research and practice. However, robust image processing is highly de pendent on the histogram analysis algorithms used and the quality of the data being processed. The algorithm presented here aims to improve the accuracy of the classification of image data generated under complex boundary situations and inconsistent lighting conditions. Using the example of the determination of nitrogen content of tomato leaves and the qualitative determination of starch con tent of apples on the basis of color image processing, we showed that the developed algorithm is able to perform a robust classification and represents an improvement to simple histogram analysis.