Use este identificador para citar ou linkar para este item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1133046
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dc.contributor.authorPEDROZO, C. A.
dc.contributor.authorALCOFORADO, A. T. W.
dc.contributor.authorMAYER, M. M.
dc.contributor.authorSANTOS, R. F. dos
dc.contributor.authorPESSONI, L. A.
dc.date.accessioned2021-07-20T19:00:53Z-
dc.date.available2021-07-20T19:00:53Z-
dc.date.created2021-07-20
dc.date.issued2021
dc.identifier.citationScientia Forestalis, v. 49, n.129, e3458, 2021.
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1133046-
dc.descriptionThe objective of this study was to estimate the spatial repeatability coefficients of Bertholletia excelsa fruits and nuts using different statistical methods, as well as to define the minimum number of fruits and nuts to be evaluated for the selection of superior genotypes. Twenty-one genotypes in the 2017 crop and 28 genotypes in the 2018 crop were evaluated. From each genotype, 10 fruits and 10 nuts per fruit were sampled. Seven fruit traits and three nut traits were measured, which were used to estimate repeatability coefficients by four statistical methods: 1) analysis of variance; 2) main components based on the correlation matrix; 3) principal components based on the covariance matrix and 4) structural analysis based on the correlation matrix. Estimates of repeatability coefficients varied among crops, traits and estimation methods. In general, the coefficients presented moderate magnitudes, and the methods based on principal components provided the highest estimates. For the most economically important traits for the Brazil nut market, minimum sampling of 8 fruits and 7 nuts per genotype is required to select genotypes with determination coefficients above 85%.
dc.language.isopor
dc.rightsopenAccesspt_BR
dc.titleRepetibility of the yield traits of Brazil nut cultivated in Roraima.
dc.typeArtigo de periódico
dc.subject.thesagroBertholletia Excelsa
dc.subject.nalthesaurusVariability
dc.subject.nalthesaurusGenetic improvement
riaa.ainfo.id1133046
riaa.ainfo.lastupdate2021-07-20
dc.contributor.institutionCASSIA ANGELA PEDROZO, CPAF-RR; IFRR; IFRR; UFRR; UFRR.
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