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dc.contributor.authorQUILOANGO-CHIMARRO, C. A.
dc.contributor.authorCOELHO, R. D.
dc.contributor.authorCOSTA, J. de O.
dc.contributor.authorGUNDIM, A. da S.
dc.contributor.authorHEINEMANN, A. B.
dc.date.accessioned2024-01-17T17:32:28Z-
dc.date.available2024-01-17T17:32:28Z-
dc.date.created2024-01-17
dc.date.issued2023
dc.identifier.citationIrriga, v. 28, n. 3, p. 465-478, jul./set. 2023.
dc.identifier.issn1808-8546
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1160927-
dc.descriptionWater stress negatively affects upland rice production. The objective of this study was to identify physiological traits that could depict yield responses under water stress conditions. Three modern upland rice cultivars (C): BRS A501 CL (C1), BRS Esmeralda (C2) and BRS Serra Dourada (C3) were subjected to three water availability levels (W): Control (100% of the field capacity throughout the growing cycle) and 70 and 40% of the water applied to the control during flowering. Yield, spikelet sterility, and 1000-grain weight were influenced by the water availability level (p < 0.05), whereas for the cultivar, only 1000-grain weight was significant. The W × C interaction was not significant for the analyzed yield components. Multivariate analysis revealed that well-irrigated plants were positively associated with grain yield and gas exchange traits, whereas the 40% water availability level was highly related to spikelet sterility and the crop water stress index. The best-fitted model for grain yield was obtained using photosynthesis, stomatal conductance, and transpiration (R2 = 0.76). Thus, physiological parameters can be used to explain the variations in upland rice yield under water stress.
dc.language.isoeng
dc.rightsopenAccess
dc.subjectMultiple linear regression
dc.titleWater stress in modern upland rice cultivars: a multivariate study between physiological traits and yield.
dc.typeArtigo de periódico
dc.subject.thesagroArroz
dc.subject.thesagroOryza Sativa
dc.subject.thesagroStress
dc.subject.thesagroÁgua
dc.subject.thesagroSeca
dc.subject.thesagroRegressão Linear
dc.subject.nalthesaurusRice
dc.subject.nalthesaurusDrought
dc.subject.nalthesaurusRegression analysis
riaa.ainfo.id1160927
riaa.ainfo.lastupdate2024-01-17
dc.identifier.doihttps://doi.org/10.15809/irriga.2023v28n3p465-478
dc.contributor.institutionCARLOS ALBERTO QUILOANGO-CHIMARRO, ESALQ; RUBENS DUARTE COELHO, ESALQ; JÉFFERSON DE OLIVEIRA COSTA, EPAMIG; ALICE DA SILVA GUNDIM, ESALQ; ALEXANDRE BRYAN HEINEMANN, CNPAF.
Aparece en las colecciones:Artigo em periódico indexado (CNPAF)

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