Orbital multispectral imaging: a tool for discriminating management strategies for nematodes in coffee

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Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorUniversidade Federal de Uberlândia (UFU)-
Autor(es): dc.contributorFederal University of Viçosa-
Autor(es): dc.creatorOrlando, Vinicius Silva Werneck-
Autor(es): dc.creatorVieira, Bruno Sérgio-
Autor(es): dc.creatorMartins, George Deroco-
Autor(es): dc.creatorLopes, Everaldo Antônio-
Autor(es): dc.creatorAssis, Gleice Aparecida de-
Autor(es): dc.creatorPereira, Fernando Vasconcelos-
Autor(es): dc.creatorGalo, Maria de Lourdes Bueno Trindade-
Autor(es): dc.creatorRodrigues, Leidiane da Silva-
Data de aceite: dc.date.accessioned2025-08-21T22:30:27Z-
Data de disponibilização: dc.date.available2025-08-21T22:30:27Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2024-10-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1007/s11119-024-10188-z-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/307954-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/307954-
Descrição: dc.descriptionBackground: Remote sensing based on multispectral imaging may be useful for detecting vegetation stress responses in agriculture. Objectives: To evaluate the potential of orbital multispectral imaging in discriminating the most effective strategies for reducing plant-parasitic nematode populations, thereby preventing yield losses in coffee production. Methods: Coffee plants were treated with eleven treatments, including Bacillus spp. isolates, commercial biological products, commercial chemical nematicides, and water (control group). Initial and final nematode populations in the soil were quantified, and surface reflectance data were collected using the Planet orbital multispectral sensor. The data were classified using the random tree algorithm. Results: The population of plant-parasitic nematodes was reduced by 35.90% and 55.13% following the application of B. amyloliquefaciens isolate B266 and B. subtilis isolate B33, respectively. Under the conditions of this experiment, multispectral imaging accurately discriminated the most nematicidal treatments, with a global accuracy of 80%. Conclusions: Orbital multispectral imaging can discriminate the most effective treatments used for nematode management in coffee plants, highlighting its potential as a supportive tool in agriculture.-
Descrição: dc.descriptionDoctorate’s Program in Cartographic Sciences São Paulo State University, SP-
Descrição: dc.descriptionInstitute of Agricultural Sciences Federal University of Uberlândia, MG-
Descrição: dc.descriptionCivil Engineering College Federal University of Uberlândia, MG-
Descrição: dc.descriptionPostgraduate Program in Plant Production Federal University of Viçosa, Monte Carmelo, MG-
Descrição: dc.descriptionMaster’s Program in Agriculture and Geospatial Information Federal University of Uberlândia, MG-
Descrição: dc.descriptionPosgraduate Program in Cartographic Sciences São Paulo State University, SP-
Descrição: dc.descriptionInstitute of Agricultural Sciences Bachelor Graduation in Agronomy Federal University of Uberlândia, MG-
Descrição: dc.descriptionDoctorate’s Program in Cartographic Sciences São Paulo State University, SP-
Descrição: dc.descriptionPosgraduate Program in Cartographic Sciences São Paulo State University, SP-
Formato: dc.format2573-2588-
Idioma: dc.languageen-
Relação: dc.relationPrecision Agriculture-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectBacillus spp-
Palavras-chave: dc.subjectBiological control-
Palavras-chave: dc.subjectMachine learning-
Palavras-chave: dc.subjectPest management-
Palavras-chave: dc.subjectRemote sensing-
Título: dc.titleOrbital multispectral imaging: a tool for discriminating management strategies for nematodes in coffee-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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