Using remote sensing to map in-field variability of peanut maturity

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorTifton Campus-
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.creatorSantos, A. F. [UNESP]-
Autor(es): dc.creatorLacerda, L. N.-
Autor(es): dc.creatorGobbo, S.-
Autor(es): dc.creatorTofannin, A.-
Autor(es): dc.creatorSilva, R. P. [UNESP]-
Autor(es): dc.creatorVellidis, G.-
Data de aceite: dc.date.accessioned2022-02-22T00:23:22Z-
Data de disponibilização: dc.date.available2022-02-22T00:23:22Z-
Data de envio: dc.date.issued2020-12-11-
Data de envio: dc.date.issued2020-12-11-
Data de envio: dc.date.issued2019-01-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.3920/978-90-8686-888-9_75-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/198036-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/198036-
Descrição: dc.descriptionA study was conducted to assess if vegetation indices (VIs) could be used as indicators of peanut maturity. A 24 ha block of a rainfed field with clearly visible soil and crop variability was used. An unmanned aerial vehicle (UAV) equipped with a multispectral camera captured spectral reflectance from the peanut canopy. The reflectance data were used to evaluate several VIs as potential indicators of peanut maturity. Pearson's correlation and linear regression were used to evaluate the response of the VIs as well as the sensitivity of individual reflectance bands to peanut maturity. The red edge band was the most sensitive. The most responsive VIs were the non-linear index (NLI) and the modified non-linear index (MNLI) when red edge reflectance was substituted for red reflectance.-
Descrição: dc.descriptionUniversity of Wisconsin - Superior-
Descrição: dc.descriptionUniversity of Georgia Tifton Campus-
Descrição: dc.descriptionSão Paulo State University (UNESP) Jaboticabal Campus-
Descrição: dc.descriptionSão Paulo State University (UNESP) Jaboticabal Campus-
Formato: dc.format605-611-
Idioma: dc.languageen-
Relação: dc.relationPrecision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectMultispectral images-
Palavras-chave: dc.subjectRed edge-
Palavras-chave: dc.subjectReflectance-
Palavras-chave: dc.subjectUAV-
Palavras-chave: dc.subjectVegetation index-
Título: dc.titleUsing remote sensing to map in-field variability of peanut maturity-
Aparece nas coleções:Repositório Institucional - Unesp

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