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Publicação:
Use of remote sensing to characterize the phenological development and to predict sweet potato yield in two growing seasons

dc.contributor.authorTedesco, Danilo [UNESP]
dc.contributor.authorde Oliveira, Maílson Freire [UNESP]
dc.contributor.authordos Santos, Adão Felipe
dc.contributor.authorCosta Silva, Edgard Henrique
dc.contributor.authorde Souza Rolim, Glauco [UNESP]
dc.contributor.authorda Silva, Rouverson Pereira [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionFederal University Lavras
dc.contributor.institutionTaquaritinguense Institute of Higher Education
dc.date.accessioned2022-05-01T05:29:32Z
dc.date.available2022-05-01T05:29:32Z
dc.date.issued2021-09-01
dc.description.abstractSweet potato is a tuberous root with versatility in food products, but also with applications in the energy industry, such as in ethanol production. Developing mechanisms to assess the performance of this crop is important, difficult, and costly, as its commercial product grows below ground. The use of remote sensing to evaluate the development of sweet potato has not yet been reported in the literature. In our study, we showed that spectral vegetation indices are good proxies to monitor the temporal dynamics of crop growth and differentiate phenological stages, regardless of the growing season. The development phases were divided into three stages according to the vegetation indices: (I) initial stage (<200 GDD), when vegetation has little influence on VIs; (II) growth stage (from 200 to 500 GDD), when vegetation has high influence on VIs due to its growth; and (III) stabilization stage (> 500 GDD), when major changes in VIs no longer occur because vegetative growth has ceased. Besides that, we found that these indices can predict crop yield before harvest. In two growing seasons, the smallest errors in yield estimates occurred during the growth stage. In the summer season with NDVI at 355 GDD with errors of 2.63 t ha−1 and in the winter season when GNDVI at 440 GDD had errors of 3.06 t ha−1.en
dc.description.affiliationDepartment of Engineering and Mathematical Sciences São Paulo State University
dc.description.affiliationDepartment of Agriculture Federal University Lavras
dc.description.affiliationDepartment of Agronomy Taquaritinguense Institute of Higher Education
dc.description.affiliationUnespDepartment of Engineering and Mathematical Sciences São Paulo State University
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.identifierhttp://dx.doi.org/10.1016/j.eja.2021.126337
dc.identifier.citationEuropean Journal of Agronomy, v. 129.
dc.identifier.doi10.1016/j.eja.2021.126337
dc.identifier.issn1161-0301
dc.identifier.scopus2-s2.0-85108453802
dc.identifier.urihttp://hdl.handle.net/11449/233184
dc.language.isoeng
dc.relation.ispartofEuropean Journal of Agronomy
dc.sourceScopus
dc.subjectCrop growth
dc.subjectDigital agriculture
dc.subjectPhenology
dc.subjectReflectance
dc.subjectSmart harvesting
dc.subjectYield prediction
dc.titleUse of remote sensing to characterize the phenological development and to predict sweet potato yield in two growing seasonsen
dc.typeArtigo
dspace.entity.typePublication
unesp.author.orcid0000-0003-1875-1489[1]
unesp.author.orcid0000-0003-4771-0424[2]
unesp.author.orcid0000-0003-3405-5360[3]
unesp.author.orcid0000-0002-3554-4118[4]
unesp.author.orcid0000-0001-8852-2548[6]
unesp.departmentEngenharia Rural - FCAVpt

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