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 | Acesso ao texto completo restrito à biblioteca da Epagri-Sede. Para informações adicionais entre em contato com biblio@epagri.sc.gov.br. |
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Biblioteca(s): |
Epagri-Sede. |
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Data corrente: |
18/01/2007 |
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Data da última atualização: |
17/05/2011 |
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Autoria: |
HINZ, R. H.; LICHTEMBERG, L. A.; DELLA BRUNA, E.; MALBURG, J. L. |
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Afiliação: |
Empasc |
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Título: |
Producao de mudas basicas de cultivares de bananeira. |
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Ano de publicação: |
1990 |
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Fonte/Imprenta: |
In: PIANA, Z.; ZANINI NETO, J.A. (Coord.).Producao de sementes basicas, mudas e plantas matrizes pela EMPASC, periodo 1976-1988. Florianopolis: EMPASC, 1990. |
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Páginas: |
p. 41-43. |
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Idioma: |
Português |
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Palavras-Chave: |
Banana; Producao de muda. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 00595naa a2200181 a 4500
001 1050814
005 2011-05-17
008 1990 bl uuuu u00u1 u #d
100 1 $aHINZ, R. H.
245 $aProducao de mudas basicas de cultivares de bananeira.
260 $c1990
300 $ap. 41-43.
653 $aBanana
653 $aProducao de muda
700 1 $aLICHTEMBERG, L. A.
700 1 $aDELLA BRUNA, E.
700 1 $aMALBURG, J. L.
773 $tIn: PIANA, Z.; ZANINI NETO, J.A. (Coord.).Producao de sementes basicas, mudas e plantas matrizes pela EMPASC, periodo 1976-1988. Florianopolis: EMPASC, 1990.
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Epagri-Sede (Epagri-Sede) |
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Biblioteca(s): |
Epagri-Sede. |
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Data corrente: |
24/11/2021 |
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Data da última atualização: |
24/11/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
Internacional - A |
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Autoria: |
SOUZA, M.; COMIN, J. J.; MORESCO, R.; MARASCHIN, M.; KURTZ, C.; LOVATO, P. E.; LOURENZI, C. R.; PILATTI, F. K.; LOSS, A.; KUHNEN, S. |
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Título: |
Exploratory and discriminant analysis of plant phenolic profiles obtained by UV?vis scanning spectroscopy. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Journal of Integrative Bioinformatics, Berlin, Alemanha, v. 18, p. 1-11, 2021. |
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Idioma: |
Inglês |
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Conteúdo: |
Some species of cover crops produce phenolic compounds with allelopathic potential. The use of
math, statistical and computational tools to analyze data obtained with spectrophotometry can assist in the
chemical profle discrimination to choose which species and cultivation are the best for weed management
purposes. The aim of this study was to perform exploratory and discriminant analysis using R package
specmineonthephenolicprofleofSecalecerealeL.,AvenastrigosaL.andRaphanussativusL.shootsobtained
by UV?vis scanning spectrophotometry. Plants were collected at 60, 80 and 100 days after sowing and at 15
and 30 days after rolling in experiment in Brazil. Exploratory and discriminant analysis, namely principal
component analysis, hierarchical clustering analysis, t-test, fold-change, analysis of variance and supervised
machine learning analysis were performed. Results showed a stronger tendency to cluster phenolic profles
according to plant species rather than crop management system, period of sampling or plant phenologic
stage. PCA analysis showed a strong distinction of S. cereale L. and A. strigosa L. 30 days after rolling. Due
to the fast analysis and friendly use, the R package specmine can be recommended as a supporting tool to
exploratory and discriminatory analysis of multivariate data. |
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Palavras-Chave: |
chemometrics; cover crops; multivariate analysis; R language; specmine. |
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Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
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Marc: |
LEADER 02143naa a2200289 a 4500
001 1131514
005 2021-11-24
008 2021 bl uuuu u00u1 u #d
100 1 $aSOUZA, M.
245 $aExploratory and discriminant analysis of plant phenolic profiles obtained by UV?vis scanning spectroscopy.$h[electronic resource]
260 $c2021
520 $aSome species of cover crops produce phenolic compounds with allelopathic potential. The use of math, statistical and computational tools to analyze data obtained with spectrophotometry can assist in the chemical profle discrimination to choose which species and cultivation are the best for weed management purposes. The aim of this study was to perform exploratory and discriminant analysis using R package specmineonthephenolicprofleofSecalecerealeL.,AvenastrigosaL.andRaphanussativusL.shootsobtained by UV?vis scanning spectrophotometry. Plants were collected at 60, 80 and 100 days after sowing and at 15 and 30 days after rolling in experiment in Brazil. Exploratory and discriminant analysis, namely principal component analysis, hierarchical clustering analysis, t-test, fold-change, analysis of variance and supervised machine learning analysis were performed. Results showed a stronger tendency to cluster phenolic profles according to plant species rather than crop management system, period of sampling or plant phenologic stage. PCA analysis showed a strong distinction of S. cereale L. and A. strigosa L. 30 days after rolling. Due to the fast analysis and friendly use, the R package specmine can be recommended as a supporting tool to exploratory and discriminatory analysis of multivariate data.
653 $achemometrics
653 $acover crops
653 $amultivariate analysis
653 $aR language
653 $aspecmine
700 1 $aCOMIN, J. J.
700 1 $aMORESCO, R.
700 1 $aMARASCHIN, M.
700 1 $aKURTZ, C.
700 1 $aLOVATO, P. E.
700 1 $aLOURENZI, C. R.
700 1 $aPILATTI, F. K.
700 1 $aLOSS, A.
700 1 $aKUHNEN, S.
773 $tJournal of Integrative Bioinformatics, Berlin, Alemanha$gv. 18, p. 1-11, 2021.
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