Detection, identification, and quantification of fungal diseases of sugar beet leaves using imaging and non-imaging hyperspectral techniques [Elektronische Ressource] / von Anne-Katrin Mahlein

Institute of Crop Science and Rescource Conservation - PhytomedicineDetection, identification, and quantification of fungaldiseases of sugar beet leaves using imaging andnon-imaging hyperspectral techniquesInaugural-DissertationzurErlangung des GradesDoktor der Agrarwissenschaften(Dr. agr.)derHohen Landwirtschaftlichen FakultätderRheinischen Friedrich-Wilhelms-Universitätzu Bonnvorgelegt am 04.11.2010vonAnne-Katrin Mahleinaus AnsbachReferent: Prof. Dr. H.-W. DehneKoreferent: Prof. Dr. H. GoldbachTag der mündlichen Prüfung: 20.01.2011Erscheinungsjahr: 2011In liebevoller Erinnerung an meine Großmutter Maria EffAbstractPlant diseases influence the optical properties of plants in different ways. Depending on the hostpathogen system and disease specific symptoms, different regions of the reflectance spectrum areaffected, resulting in specific spectral signatures of diseased plants. The aim of this study was toexamine the potential of hyperspectral imaging and non-imaging sensor systems for the detection,differentiation, and quantification of plant diseases. Reflectance spectra of sugar beet leaves in-fected with the fungal pathogens Cercospora beticola, Erysiphe betae, and Uromyces betae causingCercospora leaf spot, powdery mildew, and sugar beet rust, respectively, were recorded repeatedlyduring pathogenesis. Hyperspectral data were analyzed using various methods of data and imageanalysis and were compared to ground truth data.