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Auflistung nach Schlagwort "agriculture"

1 - 8 von 8
  • Konferenzbeitrag
    Antecedents of organizational resilience and how these can be transferred to agriculture
    (43. GIL-Jahrestagung, Resiliente Agri-Food-Systeme, 2023) Hohagen, Saskia; Obermann, Niklas; Wilkens; Uta
    The agricultural sector is increasingly characterized by national competition and a dynamic environment. The resilience concept, which is used in connection with farms, is based on the social-ecological perspective and primarily gives emphasis to a system. To this end, there is a research gap in the consideration of resilience from a management perspective in agriculture. Drawing on the literature on organizational resilience from a managerial perspective, this article examines resilience-enabling factors that can be used by operations managers to prepare for future challenges in agriculture. A systematic literature review was conducted from which four main categories of antecedents (leadership, individual factors, digitalization and strategic alignment) could be derived, consistent with a socio-technical perspective on organizations. Considering these factors can help farm managers to build resilient farms not only from a social-ecological, but also from an organizational (management) perspective.
  • Konferenzbeitrag
    Compliance of agricultural AI systems – app-based legal verification throughout the development
    (44. GIL - Jahrestagung, Biodiversität fördern durch digitale Landwirtschaft, 2024) Kruse, Niklas; Wachter, Paul; Schöning, Julius
    Significant advances in artificial intelligence (AI) have been achieved; however, practical implementation in agriculture remains limited. Compliance with emerging regulations, such as the EU AI Act and GDPR, is now vital, even for non-critical AI systems. Developers need tools to assess legal compliance, which is complex, often requiring full legal advice. To address this issue, we are developing a support app that simplifies the legal aspects of AI system development, covering the entire lifecycle, from conception to distribution. The current app, which covers the key legal area of copyright and will soon include GDPR and the AI Act, aims to bridge the gap between AI research and agriculture. An evaluation of our app by experts from both the legal and the IT domains shows that the app assists the developers so that they make legally correct statements. Consequently, it promotes legal compliance and awareness among developers, contributing to the seamless integration of AI into agriculture. The need for compliant AI systems in various industries, including agriculture, will only increase as regulations evolve.
  • Konferenzbeitrag
    Does e-government contribute to a reduction of farmers’ administrative burden in Switzerland
    (40. GIL-Jahrestagung, Digitalisierung für Mensch, Umwelt und Tier, 2020) Stoinescu, Andrei; Reissig, Linda; Mack, Gabriele
    Since the shift to direct payments and the growing environmental regulations, the administrative costs for farmers and public administration have increased. The introduction of e-government changed the farmers’ working conditions. For this study, we examined how variables such as the ‘perceived organizational benefits’, ‘organizational characteristics’, ‘organizational usage characteristics’ and ‘perceived characteristics’ influence the administrative burden of Swiss farmers when using e-government. A quantitative survey, as well as qualitative open statements and in-depth interviews were analyzed for this purpose. We found that due to the transition from paper to electronic forms, the administrative workload of about one third of the farmers decreased. Attitude and the skills of the farmers seem to influence the administrative burden the strongest.
  • Konferenzbeitrag
    Evaluating synthetic vs. real data generation for AI-based selective weeding
    (43. GIL-Jahrestagung, Resiliente Agri-Food-Systeme, 2023) Iqbal, Naeem; Bracke, Justus; Elmiger, Anton; Hameed, Hunaid; von Szadkowski, Kai
    Synthetic data has the potential to reduce the cost for ML training in agriculture but poses its own set of problems compared to real data acquisition. In this work, we present two methods of training data acquisition for the application of machine vision algorithms in the use case of selective weeding. Results from ML experiments suggest that current methods for generating synthetic data in the field of agriculture cannot fully replace real data but may greatly reduce the quantity of real data required for model training.
  • Konferenzbeitrag
    Remote plant sensing and phenotyping – an e-learning tool in higher education
    (43. GIL-Jahrestagung, Resiliente Agri-Food-Systeme, 2023) Bethge, Hans; Mählmann, Thomas; Winkelmann, Traud; Rath, Thomas
    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.
  • Konferenzbeitrag
    Review of agricultural field robots and their applicability in potato cultivation
    (43. GIL-Jahrestagung, Resiliente Agri-Food-Systeme, 2023) Käthner, Jana; Koch, Karuna; Höfner, Nora; Dworak, Volker; Shokrian Zeini, Mostafa; Shamshiri; Redmond; Figurski, Woj; Weltzien, Cornelia
    This paper lists the potential, challenges and requirements of autonomous field robots for potato production. It presents an overview of existing autonomous field robots in arable farming, evaluates their suitability for potato production based on literature findings and gives an outlook on possible future solutions. The analysis was confined to the European market. In summary, 17 commercially available field robots, 4 robots in the test phase and 14 prototypes in the development phase were identified. The minimum requirements identified for field robots to enable their application in a potato field are primarily geometric due to the specific ridge structure and the habitus of potato plants. As a result, the field robot must have a track width of 0.75 m or a multiple of this dimension. In addition, a ground clearance between 0.35 m and 0.8 m must be ensured. The evaluation showed that two of the identified market-ready robot systems fulfilled the identified minimum requirements.
  • Konferenzbeitrag
    Totally Digital? Adoption of Digital Farm Management Information Systems
    (40. GIL-Jahrestagung, Digitalisierung für Mensch, Umwelt und Tier, 2020) Schulze Schwering, Dorothee; Lemken, Dominic
    Digital applications are widely used in agricultural practice and offer opportunities to increase agricultural productivity and safety. In recent years, especially digital farm management information systems (FMIS) combined with mobile applications have made technical progress, which has significantly increased their potential to e.g. enhance sustainability, facilitate networking processes, reduce working time or cut costs. However, the low number of active FMIS users shows that their potential has not yet been fully exploited in practice. This study examined the factors that influence agricultural adaptation behaviour of FMIS using data from a survey of 285 German farmers. Results show that the actual use of FMIS was determined particularly by the assessment of the suitability of the systems for the respective farm, economic efficiency and compatibility of the systems were the main factors that affected intended use. To transform farmers from intended to actual users, the providers of FMIS should work on overcoming these barriers.
  • Konferenzbeitrag
    Towards a warning system for beekeepers: Detecting anomalous changes in sensor data from honey bee colonies
    (EnviroInfo 2023, 2023) Senger, Diren; Kluss, Thorsten; Förster, Anna
    Beekeepers in most parts of the world are challenged by colony losses induced by diseases, parasites, shortage of nectar and pollen, and various other causes. For a better understanding of these causes and to inform beekeepers when to intervene and to perform certain beekeeping activities to protect their colonies, monitoring systems using sensor technology in the hives can be implemented. Currently, most monitoring systems available at the market provide a visualisation of the measured sensor values, but do no integrate further analysis or an interpretation of the values, e.g. by time series classification or by comparing to time series prediction data. We describe a system architecture where predictions made for a specific colony can be used to find aberrations, potentially indicating an anomalous development of the bee colony. We summarise challenges of such an implementation and evaluate the system using data from a German Citizen Science Project, consisting of temperature, humidity and weight measurements and a log of all activities and observations made by the beekeepers in a web app.