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Precision Farming (PF) management strategies are commonly based on estimations of within-field yield potential, often derived from remotely-sensed products, e.g., Vegetation Index (VI) maps. These well-established means, however, lack important information, like crop height. Combinations of VI-maps and detailed 3D Crop Surface Models (CSMs) enable advanced(More)
The ability to identify diseases in an early infection stage and to accurately quantify the severity of infection is crucial in plant disease assessment and management. A greenhouse study was conducted to assess changes in leaf spectral reflectance of wheat plants during infection by powdery mildew and take-all disease to evaluate leaf reflectance(More)
Crop growth models have been used in the past to study causes of yield variability and to estimate the economic consequences of variable nitrogen rate prescriptions. In this study, the APOLLO model, which is based on the DSSAT crop growth model family, was implemented to develop optimum site-specific nitrogen management prescriptions for wheat. The nitrogen(More)
The current challenges crop production faces in the context of required yield increases while reducing fertilizer, water and pesticide inputs have created an increasing demand for agronomic knowledge and enhanced decision support guidelines, which are difficult to obtain on spatial scales appropriate for use in a multitude of global cropping systems.(More)
Aufgrund stetig steigender Produktionsmittelpreise wird es immer wichtiger, höchste Erträge mit einem optimierten Einsatz an Produktionsfaktoren zu erreichen. Teilflächenspezifische Strategien zur optimierten Verteilung der eingesetzten Produktionsfaktoren können hierzu einen wertvollen Beitrag leisten. Um teilflächenspezifische Bewirtschaftungsmaßnahmen(More)
The objective of this study was to use the process-oriented precision farming crop growth model APOLLO to identify problem grids for crop production within a field. The model was calibrated for a wheat and a corn field. During the calibration process soil parameters were adjusted iteratively for each grid within the fields, using a simulated annealing(More)
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