Optimizing Corn Tar Spot Measurement : A Deep Learning Approach Using Red-Green-Blue Imaging and the Stromata Contour Detection Algorithm for Leaf-Level Disease Severity Analysis
Visual detection of stromata (brown-black, elevated fungal fruiting bodies) is the primary method for quantifying tar spot early in the season because these structures are definitive signs of the disease and essential for effective disease monitoring and management. Here, we present the Stromata Con...
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| Veröffentlicht in: | Plant disease. - 1997. - (2024) vom: 31. Dez., Seite PDIS12232702RE
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| 1. Verfasser: |
Lee, Da-Young
(VerfasserIn) |
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| Weitere Verfasser: |
Na, Dong-Yeop,
Góngora-Canul, Carlos,
Jimenez-Beitia, Fidel E,
Goodwin, Stephen B,
Cruz, Andrés P,
Delp, Edward J,
Acosta, Alex G,
Lee, Jeong-Soo,
Falconí, César E,
Cruz, C D |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2024
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| Zugriff auf das übergeordnete Werk: | Plant disease
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| Schlagworte: | Journal Article
contour analysis
convolutional neural network
plant disease phenotyping
tar spot of corn severity |
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