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Assessing the predictive capability of N, P, and B diagnosis in cotton crop

dc.contributor.authorTraspadini, Edilaine Istéfani Franklin [UNESP]
dc.contributor.authorWadt, Paulo Guilherme Salvador
dc.contributor.authorde Prado, Renato Mello [UNESP]
dc.contributor.authorFurtado Oliveira, Douglas
dc.contributor.authorCampos, Cid Naudi Silva
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionEmpresa Brasileira de Pesquisa Agropecuária (EMBRAPA)
dc.contributor.institutionUniversidade Federal do Mato Grosso do Sul
dc.date.accessioned2025-04-29T20:01:37Z
dc.date.issued2024-12-01
dc.description.abstractThe compositional nutrient diagnosis—CND method is a standard tool for evaluating plant nutritional status. Adjustments are crucial to elevate accuracy. The effectiveness of such methodological refinements should be rigorously assessed through accuracy tests that are benchmarked against the prescient diagnostic analysis—PDA methodology. The objective of this investigation was to refine the CND technique for a more precise evaluation of N, P, and B nutrient status in cotton. The study’s database encompasses 144 data points pertaining to crop yield and foliar nutrient concentrations from cotton plantations in the Cerrado biome of Brazil. Subsequently, the CND norms were established through rigorous calibration. Three separate nutrient-dose trials, each featuring four levels of N, P and B, were carried out to assess plant true nutritional status. Adjustments were made to the nutrient responsiveness range—NRr (0.5 and 1.0), while yield response—YR were scrutinized at threshold levels (5% and 10%). The prerequisites for achieving high diagnostic accuracy were nutrient specific. For N, maximal accuracy was linked only to the YR parameter (YR = 10%). For P, the most precise outcomes were attained with a NRr = 0.5 and YI = 5%. For B, highest diagnostic accuracy when the NRr = 1.0 and YI = 10%. These insights highlight the need to fine-tune the CND method for reliable nutritional evaluations and cotton crop productivity optimization.en
dc.description.affiliationUniversidade Estadual Paulista
dc.description.affiliationEmpresa Brasileira de Pesquisa Agropecuária
dc.description.affiliationUniversidade Federal do Mato Grosso do Sul
dc.description.affiliationUnespUniversidade Estadual Paulista
dc.identifierhttp://dx.doi.org/10.1038/s41598-024-67593-7
dc.identifier.citationScientific Reports, v. 14, n. 1, 2024.
dc.identifier.doi10.1038/s41598-024-67593-7
dc.identifier.issn2045-2322
dc.identifier.scopus2-s2.0-85199401214
dc.identifier.urihttps://hdl.handle.net/11449/305007
dc.language.isoeng
dc.relation.ispartofScientific Reports
dc.sourceScopus
dc.subjectAccuracy
dc.subjectCND method
dc.subjectDiagnostic analysis
dc.subjectFoliar diagnosis
dc.subjectGossypium hirsutum
dc.subjectNet yield productivity
dc.titleAssessing the predictive capability of N, P, and B diagnosis in cotton cropen
dc.typeArtigopt
dspace.entity.typePublication
unesp.author.orcid0000-0001-8209-4212[1]
unesp.author.orcid0000-0002-5429-6308[2]
unesp.author.orcid0000-0003-1998-6343[3]
unesp.author.orcid0000-0001-6810-885X[5]

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