Leaf area estimation of cassava from linear dimensions

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dc.contributor.authorZanetti, Samara [UNESP]
dc.contributor.authorPereira, Laís F. M. [UNESP]
dc.contributor.authorSartori, Maria Márcia P. [UNESP]
dc.contributor.authorSilva, Marcelo De Almeida [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2018-12-11T17:15:03Z
dc.date.available2018-12-11T17:15:03Z
dc.date.issued2017-07-01
dc.description.abstractThe objective of this study was to determine predictor models of leaf area of cassava from linear leaf measurements. The experiment was carried out in greenhouse in the municipality of Botucatu, São Paulo state, Brazil. The stem cuttings with 5-7 nodes of the cultivar IAC 576-70 were planted in boxes filled with about 320 liters of soil, keeping soil moisture at field capacity, monitored by puncturing tensiometers. At 80 days after planting, 140 leaves were randomly collected from the top, middle third and base of cassava plants. We evaluated the length and width of the central lobe of leaves, number of lobes and leaf area. The measurements of leaf areas were correlated with the length and width of the central lobe and the number of lobes of the leaves, and adjusted to polynomial and multiple regression models. The linear function that used the length of the central lobe LA = -69.91114 + 15.06462L and linear multiple functions LA = -69.9188 + 15.5102L + 0.0197726K - 0.0768998J or LA = -69.9346 + 15.0106L + 0.188931K - 0.0264323H are suitable models to estimate leaf area of cassava cultivar IAC 576-70.en
dc.description.affiliationUniversidade Estadual Paulista/UNESP Faculdade de Ciências Agronômicas Departamento de Produção e Melhoramento Vegetal, Rua José Barbosa de Barros, 1780
dc.description.affiliationUnespUniversidade Estadual Paulista/UNESP Faculdade de Ciências Agronômicas Departamento de Produção e Melhoramento Vegetal, Rua José Barbosa de Barros, 1780
dc.format.extent1729-1736
dc.identifierhttp://dx.doi.org/10.1590/0001-376520172016-0475
dc.identifier.citationAnais da Academia Brasileira de Ciencias, v. 89, n. 3, p. 1729-1736, 2017.
dc.identifier.doi10.1590/0001-376520172016-0475
dc.identifier.fileS0001-37652017000401729.pdf
dc.identifier.issn1678-2690
dc.identifier.issn0001-3765
dc.identifier.lattes4203867944943427
dc.identifier.scieloS0001-37652017000401729
dc.identifier.scopus2-s2.0-85029957702
dc.identifier.urihttp://hdl.handle.net/11449/175264
dc.language.isoeng
dc.relation.ispartofAnais da Academia Brasileira de Ciencias
dc.relation.ispartofsjr0,418
dc.relation.ispartofsjr0,418
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectLeaf biometrics
dc.subjectManihot esculenta crantz
dc.subjectMultiple regression
dc.subjectStatistical models
dc.titleLeaf area estimation of cassava from linear dimensionsen
dc.typeArtigo
unesp.author.lattes4203867944943427
unesp.departmentProdução e Melhoramento Vegetal - FCApt

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Botucatu - FCA - Faculdade de Ciências Agronômicas