Building a hyperspectral library of common bean diseases.
Sensors attached to unmanned aerial vehicles can detect diseased plants before they become symptomatic, according to differences in their reflectance. Despite the advances in hardware and methods for detecting infections with remote sensing, using these tools to scout common bean diseases is still incipient. The objectives of this study were: 1) to evaluate the effectiveness of a hyperspectral sensor in the diagnosis of common bean diseases; 2) verify differences in the spectral signatures in different genotypes with healthy or infected plants; and 3) to investigate if mulch used in no-tillage can influence the spectral signatures.
Main Authors: | , , , , , , , , |
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Other Authors: | |
Format: | Resumo em anais e proceedings biblioteca |
Language: | eng |
Published: |
2024-04-23
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Subjects: | Feijão, Phaseolus Vulgaris, Doença de Planta, Tecnologia, Sensoriamento Remoto, Beans, Plant diseases and disorders, Hyperspectral imagery, |
Online Access: | http://www.alice.cnptia.embrapa.br/alice/handle/doc/1163790 |
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Summary: | Sensors attached to unmanned aerial vehicles can detect diseased plants before they become symptomatic, according to differences in their reflectance. Despite the advances in hardware and methods for detecting infections with remote sensing, using these tools to scout common bean diseases is still incipient. The objectives of this study were: 1) to evaluate the effectiveness of a hyperspectral sensor in the diagnosis of common bean diseases; 2) verify differences in the spectral signatures in different genotypes with healthy or infected plants; and 3) to investigate if mulch used in no-tillage can influence the spectral signatures. |
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