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Registro Completo |
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Biblioteca(s): |
Embrapa Recursos Genéticos e Biotecnologia. |
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Data corrente: |
03/08/2022 |
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Data da última atualização: |
28/09/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
NOGUEIRA, G. F.; LUIS, Z. G.; SALLES, L. A.; PASQUAL, M.; PEREIRA, J. E. S. |
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Afiliação: |
GABRIELA FERREIRA NOGUEIRA, UFLA; ZANDERLUCE GOMES LUIS; LEILA APARECIDA SALLES, UFLA; MOACIR PASQUAL, UFLA; JONNY EVERSON SCHERWINSKI PEREIRA, Cenargen. |
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Título: |
High-efficiency organogenesis and evaluation of the regenerated plants by flow cytometry of a broad range of Saccharum spp. hybrids. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Acta Physiologiae Plantarum, v. 44, 2022. Article 87. |
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DOI: |
https://doi.org/10.1007/s11756-022-01176-7 |
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Idioma: |
Inglês |
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Notas: |
Na publicação: Jonny Everson Scherwinski-Pereira. |
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Palavras-Chave: |
DNA content; Large-scale propagation; Morphological variation; Saccharum spp. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 00807naa a2200229 a 4500
001 2145183
005 2023-09-28
008 2022 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1007/s11756-022-01176-7$2DOI
100 1 $aNOGUEIRA, G. F.
245 $aHigh-efficiency organogenesis and evaluation of the regenerated plants by flow cytometry of a broad range of Saccharum spp. hybrids.$h[electronic resource]
260 $c2022
500 $aNa publicação: Jonny Everson Scherwinski-Pereira.
653 $aDNA content
653 $aLarge-scale propagation
653 $aMorphological variation
653 $aSaccharum spp
700 1 $aLUIS, Z. G.
700 1 $aSALLES, L. A.
700 1 $aPASQUAL, M.
700 1 $aPEREIRA, J. E. S.
773 $tActa Physiologiae Plantarum$gv. 44, 2022. Article 87.
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Registro original: |
Embrapa Recursos Genéticos e Biotecnologia (CENARGEN) |
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Registro Completo
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Biblioteca(s): |
Embrapa Café. |
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Data corrente: |
09/11/2023 |
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Data da última atualização: |
09/11/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 2 |
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Autoria: |
MANOEL, I. dos S.; RESENDE, M.; SOUSA, P. H. A.; ROSA, S. D. V. F. da; CIRILLO, M. A. |
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Afiliação: |
IURI DOS SANTOS MANOEL, UNIVERSIDADE FEDERAL DE LAVRAS; MARIANA RESENDE, UNIVERSIDADE FEDERAL DE LAVRAS; PEDRO HERIQUE ASSIS SOUSA, UNIVERSIDADE FEDERAL DE LAVRAS; STTELA DELLYZETE VEIGA F DA ROSA, CNPCa; MARCELO ANGELO CIRILLO, UNIVERSIDADE FEDERAL DE LAVRAS. |
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Título: |
Simulation of robust adaptive regression multi-level models for quality analysis of special coffees in cold storage. |
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Ano de publicação: |
2024 |
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Fonte/Imprenta: |
Acta Scientiarum. Technology, v. 46, n. 1, e59135, 2024. |
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Páginas: |
10 p. |
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DOI: |
https://doi.org/10.4025/actascitechnol.v46i1.59135 |
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Idioma: |
Inglês |
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Conteúdo: |
ABSTRACT. Numerous factors contribute to specialty coffee quality, storage and cooling conditions. We may therefore assume that sensory evaluation results can be corrupted by measurement errors, especially when cuppers are not trained, leading to occurrence of observation outliers. Therefore, this study aimed to propose simulation scenarios considering parametric values of multilevel model fit with robust adaptive regressions to the presence of outliers in a real experiment with processed and unprocessed coffee beans stored at different times and temperatures. In this context, we considered computationally simulated scenarios in which sensory scoring errors can be made at L = 5 and 10 units. The proposed method was feasible for the sensory scoring of an experiment of coffee storage conditions and cooled environments. This is because it included robust characteristics of samples evaluated with up to 30% of outliers. |
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Thesaurus NAL: |
Coffea; Cold storage; Regression analysis. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1158148/1/Simulation-of-robust-adaptive-regression.pdf
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Marc: |
LEADER 01661naa a2200229 a 4500
001 2158148
005 2023-11-09
008 2024 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.4025/actascitechnol.v46i1.59135$2DOI
100 1 $aMANOEL, I. dos S.
245 $aSimulation of robust adaptive regression multi-level models for quality analysis of special coffees in cold storage.$h[electronic resource]
260 $c2024
300 $a10 p.
520 $aABSTRACT. Numerous factors contribute to specialty coffee quality, storage and cooling conditions. We may therefore assume that sensory evaluation results can be corrupted by measurement errors, especially when cuppers are not trained, leading to occurrence of observation outliers. Therefore, this study aimed to propose simulation scenarios considering parametric values of multilevel model fit with robust adaptive regressions to the presence of outliers in a real experiment with processed and unprocessed coffee beans stored at different times and temperatures. In this context, we considered computationally simulated scenarios in which sensory scoring errors can be made at L = 5 and 10 units. The proposed method was feasible for the sensory scoring of an experiment of coffee storage conditions and cooled environments. This is because it included robust characteristics of samples evaluated with up to 30% of outliers.
650 $aCoffea
650 $aCold storage
650 $aRegression analysis
700 1 $aRESENDE, M.
700 1 $aSOUSA, P. H. A.
700 1 $aROSA, S. D. V. F. da
700 1 $aCIRILLO, M. A.
773 $tActa Scientiarum. Technology$gv. 46, n. 1, e59135, 2024.
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