Management approaches in organic potato and tomato production

The presented thesis considered three different system approach topics to ensure yield and plant health in organically grown potatoes and tomatoes. The first topic describes interactions between late blight (Phytophthora infestans) incidence and soil nitrogen supply on yield in organic potato farming focussing in detail on the yield loss relationship of late blight based on results of several field trials. The interactive effects of soil N-supply, climatic conditions and late blight on the yield were studied in the presence and absence of copper fungicides from 2002-2004 for the potato cultivar Nicola. Under conditions of central Germany the use of copper significantly reduced late blight in almost all cases (15-30 %). However, the reductions in disease through copper application did not result in statistically significant yield increases (+0 – +10 %). Subsequently, only 30 % of the variation in yield could be attributed to disease reductions. A multiple regression model (R²Max), however, including disease reduction, growth duration and temperature sum from planting until 60 % disease severity was reached and soil mineral N contents 10 days after emergence could explain 75 % of the observed variations in yield. The second topic describes the effect of some selected organic fertilisers and biostimulant products on nitrogen-mineralization and efficiency, yield and diseases in organic potato and tomato trials. The organic fertilisers Biofeed Basis (BFB, plant derived, AgroBioProducts, Wageningen, Netherlands) and BioIlsa 12,5 Export (physically hydrolysed leather shavings, hair and skin of animals; ILSA, Arizignano, Italy) and two biostimulant products BioFeed Quality (BFQ, multi-compound seaweed extract, AgroBioProducts) and AUSMA (aqueous pine and spruce needle extract, A/S BIOLAT, Latvia), were tested. Both fertilisers supplied considerable amounts of nitrogen during the main uptake phases of the crops and reached yields as high or higher as compared to the control with horn meal fertilisation. The N-efficiency of the tested fertilisers in potatoes ranged from 90 to 159 kg yield*kg-1 N – input. Most effective with tomatoes were the combined treatments of fertiliser BFB and the biostimulants AUSMA and BFQ. Both biostimulants significantly increased the share of healthy fruit and/or the number of fruits. BFQ significantly increased potato yields (+6 %) in one out of two years and reduced R. solani-infestation in the potatoes. This suggests that the biostimulants had effects on plant metabolism and resistance properties. However, no effects of biostimulants on potato late blight could be observed in the fields. The third topic focused on the effect of suppressive composts and seed tuber health on the saprophytic pathogen Rhizoctonia solani in organic potato systems. In the present study 5t ha-1 DM of a yard and bio-waste (60/40) compost produced in a 5 month composting process and a 15 month old 100 % yard waste compost were used to assess the effects on potato infection with R. solani when applying composts within the limits allowed. Across the differences in initial seed tuber infestation and 12 cultivars 5t DM ha-1 of high quality composts, applied in the seed tuber area, reduced the infestation of harvested potatoes with black scurf, tuber malformations and dry core tubers by 20 to 84 %, 20 to 49 % and 38 to 54 %, respectively, while marketable yields were increased by 5 to 25 % due to lower rates of wastes after sorting (marketable yield is gross yield minus malformed tubers, tubers with dry core, tubers with black scurf > 15% infested skin). The rate of initial black scurf infection of the seed tubers also affected tuber number, health and quality significantly. Compared to healthy seed tubers initial black scurf sclerotia infestation of 2-5 and >10 % of tuber surface led in untreated plots to a decrease in marketable yields by 14-19 and 44-66 %, a increase of black scurf severity by 8-40 and 34-86 % and also increased the amount of malformed and dry core tubers by 32-57 and 109-214 %.

Capturing Emergent Semantics from Social Annotation Systems

The ongoing growth of the World Wide Web, catalyzed by the increasing possibility of ubiquitous access via a variety of devices, continues to strengthen its role as our prevalent information and commmunication medium. However, although tools like search engines facilitate retrieval, the task of finally making sense of Web content is still often left to human interpretation. The vision of supporting both humans and machines in such knowledge-based activities led to the development of different systems which allow to structure Web resources by metadata annotations. Interestingly, two major approaches which gained a considerable amount of attention are addressing the problem from nearly opposite directions: On the one hand, the idea of the Semantic Web suggests to formalize the knowledge within a particular domain by means of the "top-down" approach of defining ontologies. On the other hand, Social Annotation Systems as part of the so-called Web 2.0 movement implement a "bottom-up" style of categorization using arbitrary keywords. Experience as well as research in the characteristics of both systems has shown that their strengths and weaknesses seem to be inverse: While Social Annotation suffers from problems like, e. g., ambiguity or lack or precision, ontologies were especially designed to eliminate those. On the contrary, the latter suffer from a knowledge acquisition bottleneck, which is successfully overcome by the large user populations of Social Annotation Systems. Instead of being regarded as competing paradigms, the obvious potential synergies from a combination of both motivated approaches to "bridge the gap" between them. These were fostered by the evidence of emergent semantics, i. e., the self-organized evolution of implicit conceptual structures, within Social Annotation data. While several techniques to exploit the emergent patterns were proposed, a systematic analysis - especially regarding paradigms from the field of ontology learning - is still largely missing. This also includes a deeper understanding of the circumstances which affect the evolution processes. This work aims to address this gap by providing an in-depth study of methods and influencing factors to capture emergent semantics from Social Annotation Systems. We focus hereby on the acquisition of lexical semantics from the underlying networks of keywords, users and resources. Structured along different ontology learning tasks, we use a methodology of semantic grounding to characterize and evaluate the semantic relations captured by different methods. In all cases, our studies are based on datasets from several Social Annotation Systems. Specifically, we first analyze semantic relatedness among keywords, and identify measures which detect different notions of relatedness. These constitute the input of concept learning algorithms, which focus then on the discovery of synonymous and ambiguous keywords. Hereby, we assess the usefulness of various clustering techniques. As a prerequisite to induce hierarchical relationships, our next step is to study measures which quantify the level of generality of a particular keyword. We find that comparatively simple measures can approximate the generality information encoded in reference taxonomies. These insights are used to inform the final task, namely the creation of concept hierarchies. For this purpose, generality-based algorithms exhibit advantages compared to clustering approaches. In order to complement the identification of suitable methods to capture semantic structures, we analyze as a next step several factors which influence their emergence. Empirical evidence is provided that the amount of available data plays a crucial role for determining keyword meanings. From a different perspective, we examine pragmatic aspects by considering different annotation patterns among users. Based on a broad distinction between "categorizers" and "describers", we find that the latter produce more accurate results. This suggests a causal link between pragmatic and semantic aspects of keyword annotation. As a special kind of usage pattern, we then have a look at system abuse and spam. While observing a mixed picture, we suggest that an individual decision should be taken instead of disregarding spammers as a matter of principle. Finally, we discuss a set of applications which operationalize the results of our studies for enhancing both Social Annotation and semantic systems. These comprise on the one hand tools which foster the emergence of semantics, and on the one hand applications which exploit the socially induced relations to improve, e. g., searching, browsing, or user profiling facilities. In summary, the contributions of this work highlight viable methods and crucial aspects for designing enhanced knowledge-based services of a Social Semantic Web.

Finding Spaces for Urban Food Production – Matching Spatial and Stakeholder Analysis with Urban Agriculture Approaches in the Urban Renewal Area of Dortmund-Hörde, Germany

Using the case of an economically declined neighbourhood in the post-industrial German Ruhr Area (sometimes characterized as Germany’s “Rust Belt”), we analyse, describe and conclude how urban agriculture can be used as a catalyst to stimulate and support urban renewal and regeneration, especially from a socio-cultural perspective. Using the methodological framework of participatory action research, and linking bottom-up and top-down planning approaches, a project path was developed to include the population affected and foster individual responsibility for their district, as well as to strengthen inhabitants and stakeholder groups in a permanent collective stewardship for the individual forms of urban agriculture developed and implemented. On a more abstract level, the research carried out can be characterized as a form of action research with an intended transgression of the boundaries between research, planning, design, and implementation. We conclude that by synchronously combining those four domains with intense feedback loops, synergies for the academic knowledge on the potential performance of urban agriculture in terms of sustainable development, as well as the benefits for the case-study area and the interests of individual urban gardeners can be achieved.