BIOMARKER REFLECTANCE SIGNATURES FOR DISEASE DETECTION AND CLASSIFICATION

    公开(公告)号:WO2023060053A1

    公开(公告)日:2023-04-13

    申请号:PCT/US2022/077495

    申请日:2022-10-04

    Abstract: Various embodiments of the present disclosure provide systems and methods for detecting and classifying a disease state of a plant based at least in part on generating a reflectance signature for the plant. The reflectance signature is generated using a reduced set of orthogonal signal components determined from the Karhunen-Loeve Expansion. Various embodiments enable the classification of different disease states (e.g., healthy, asymptomatic, early stage, late stage) of a particular plant disease and the classification of disease states of different plant diseases, such as the differentiation between plants infected with a first plant disease from plants affected with another plant condition. The reflectance signature is generated using reduced-spectrum frequency data extracted or processed from reflectance signal data obtained from the plant. One or more signal components of the reflectance signal data that accurately describe at least a threshold amount of variance or energy of the reflectance signal data are selected for generation of the reflectance signature.

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