Meyer, LukasGilson, AndreasUhrmann, FranzWeule, MareikeKeil, FabianHaunschild, BernhardOschek, JoachimSteglich, MarcoHansen, JonathanStamminger, MarcScholz, OliverHoffmann, ChristaStein, AnthonyRuckelshausen, ArnoMüller, HenningSteckel, ThiloFloto, Helga2023-02-212023-02-212023978-3-88579-724-1https://dl.gi.de/handle/20.500.12116/40283We present a systematic approach for creating digital twins of cherry trees in orchards as part of the project “For5G: Digital Twin”. We aim to develop a basic concept for 5G applications in orchards using a mobile campus network. Digital twins monitor the status of individual trees in every aspect and are a crucial step for the digitalization of processes in horticulture. Our framework incorporates a transformation of photometric data to a 3D reconstruction, which is subsequently segmented and modeled using learning-based approaches. Collecting objective phenotypic features from individual trees over time and storing them in a knowledge graph offers a convenient foundation for gaining new insights. Our approach shows promising results at this point for creating a detailed digital twin of a cherry tree and ultimately the entire orchard.en5Gcherry treedeep learningdigital horticulturedigital twinknowledge graphorchardphenotypingphotogrammetryprecision farmingUAVText/Conference Paper1617-5468