Browsing by Subject "Teilschlagbewirtschaftung"

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An image analysis and classification system for automatic weed species identification in different crops for precision weed management
(2010) Weis, Martin; Gerhards, Roland
A system for the automatic weed detection in arable fields was developed in this thesis. With the resulting maps, weeds in fields can be controlled on a sub-field level, according to their abundance. The system contributes to the emerging field of Precision Farming technologies. Precision Farming technologies have been developed during the last two decades to refine the agricultural management practise. The goal of Precision Farming is to vary treatments within fields, according to the local situation. These techniques lead to an optimisation of the management practice, thereby saving resources, increasing the farmers outcome, reducing the overall management costs and the environmental impact. A successful introduction of Precision Farming involves the development of application equipment capable of varying treatments and sensor technology to measure the spatial heterogeneity of important growth factors. Such systems are able to record, store and use large amounts of data gathered by the sensors. Decision components are needed to transform the measurements into practical management decisions. Since the treatments are varied spatially, positional data, usually measured using GPS technology, has to be processed. The located measurements lead to a delineation of management zones within a field and are represented by geo-data and can be visualised in maps. The improved, detailed knowledge of the situation within the field leads to new and extended scopes of applications and allows to document the management practices more precisely. In this work, parts of Precision Farming technology were developed for site-specific weed management. Five selected publications are presented, covering the technological prerequisites and details of the developed system.
Integrated technical approach for differentiated nitrogen application based on expert knowledge and multiple parameters
(2023) Heiß, Andreas; Griepentrog, Hans
Variable rate nitrogen (N) application is subject to spatio-temporal dynamics of multiple parameters and a high dependency on specific local conditions. Furthermore, existing algorithms are barely capable of considering agronomic expert knowledge and common application technology limits the precise in-field realization. This work approached the complexity of site-specific N management in terms of the decision making, as well as the technical and organizational realization in a systemic manner. A commercial real-time N-sensor system’s behavior was transferred into a fuzzy expert system and extended with soil information. The incorporation into a real-time control included also the spatial synchronization of dose rate determination and realization. A digital process chain to facilitate decision making, data management and execution in the field was conceptualized and evaluated with a prototypical implementation. The N-sensor’s algorithms were precisely imitated with a maximum percentage root mean square error of 0.14%, while the multi-parametric system has implied more robust decisions. In field tests, the real-time control has shown acceptable synchronization errors largely below 1 m and with medians in the range of 0.25 m under realistic conditions. The integrated system architecture has shown a high consistency in terms of straightforward and situative expert knowledge acquisition, as well as the suitability for different sensor and application technologies. The work represents a systemic approach for a derivation and employment of machine-readable algorithms from agronomic expert knowledge defining the cause-effect relationships for a site-specific N application. Its generic properties allow a supplementation by other models and can in turn strengthen them further.