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

dc.contributor.authorSantos, A. F. [UNESP]
dc.contributor.authorLacerda, L. N.
dc.contributor.authorGobbo, S.
dc.contributor.authorTofannin, A.
dc.contributor.authorSilva, R. P. [UNESP]
dc.contributor.authorVellidis, G.
dc.contributor.institutionTifton Campus
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2020-12-12T00:57:13Z
dc.date.available2020-12-12T00:57:13Z
dc.date.issued2019-01-01
dc.description.abstractA 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.en
dc.description.affiliationUniversity of Georgia Tifton Campus
dc.description.affiliationSão Paulo State University (UNESP) Jaboticabal Campus
dc.description.affiliationUnespSão Paulo State University (UNESP) Jaboticabal Campus
dc.description.sponsorshipUniversity of Wisconsin - Superior
dc.format.extent605-611
dc.identifierhttp://dx.doi.org/10.3920/978-90-8686-888-9_75
dc.identifier.citationPrecision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019, p. 605-611.
dc.identifier.doi10.3920/978-90-8686-888-9_75
dc.identifier.scopus2-s2.0-85073749480
dc.identifier.urihttp://hdl.handle.net/11449/198036
dc.language.isoeng
dc.relation.ispartofPrecision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019
dc.sourceScopus
dc.subjectMultispectral images
dc.subjectRed edge
dc.subjectReflectance
dc.subjectUAV
dc.subjectVegetation index
dc.titleUsing remote sensing to map in-field variability of peanut maturityen
dc.typeTrabalho apresentado em eventopt
dspace.entity.typePublication
unesp.campusUniversidade Estadual Paulista (UNESP), Faculdade de Ciências Agrárias e Veterinárias, Jaboticabalpt

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