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| 1. |  | KUHN, J.; ADKINS, S.; AGWANDA, B. R.; KUBRUSLI, R. A.; ALKHOVSKY, S. V.; AMARASINGHE, G. K.; TATJANA, A.-Z.; AYLLÓN, M. A.; BAHL, J.; BALKEMA BUSCHMANN, A.; BALLINGER, M. J.; BASLER, C. F.; BAVARI, S.; BEER, M.; BEJERMAN, N.; BENNETT, A. J.; DBENTE, D. A.; BERGERON, É.; BIRD, B. H.; BLAIR, C. D.; BLASDELL, K. R.; BLYSTAD, D. R.; BOJKO, J.; BORTH, W. B.; BRADFUTE, S.; BREYTA, R.; BRIESE, T.; BROWN, P. A.; BROWN, J. K.; BUCHHOLZ, U. J.; BUCHMEIER, M. J.; ABUKREYEV, A.; BURT, F.; BÜTTNER, C.; CALISHER, C. H.; CAO, M.; CASAS, I.; CHANDRAN, K.; CHARREL, R. N.; CHENG, Q.; CHIAKI, Y.; CHIAPELLO, M.; CHOI, I. R.; CIUFO, M.; CLEGG, J. C. S.; CROZIER, I.; BÓ, E. D.; DE LA TORRE, J. C.; LAMBALLERIE, X. de; SWART, R. L. de; DEBAT, H.; DHEILLY, N. M.; DI CICCO, E.; DI PAOLA, N.; DI SERIO, F.; DIETZGEN, R. G.; DIGIARO, M.; DOLNIK, O.; DREBOT, M. A.; DREXLER, J. F.; DUNDON, W. G.; DUPREX, W. P.; DÜRRWALD, R.; DYE, J. M.; EASTON, A. J.; EBIHARA, H.; ELBEAINO, T.; ERGÜNAY, K.; FERGUSON, H. W.; FOOKS, A. R.; FORGIA, M.; FORMENTY, P. B. H.; FRÁNOVÁ, J.; ASTUA, J. de F.; FU, J.; FÜRL, S.; ZACHERT, S. G.; GĀO, G. F.; GARCÍA, M. L.; SASTRE, A. G.; GARRISON, A. R.; GASKIN, T.; GONZALE, J. P. J.; GRIFTHS, A.; GOLDBERG, T. L.; GROSCHUP, M. H.; GÜNTHER, S.; HALL, R. A.; HAMMOND, J.; HAN, O.; HEPOJOKI, J.; HEWSON, R.; HONG, J.; HONG, N.; HORIE, M.; HU, J. S.; HU, T.; HUGHES, H. R.; HÜTTNER, F.; HYNDMAN, T. H.; ILYAS, M.; JALKANEN, R.; JIĀNG, D.; JONSON, G. J.; JUNGLEN, S.; KADONO, F.; KAUKINEN, K. H.; KAWATE, M.; KLEMPA, B.; KLINGSTRÖM, J.; KOBINGER, G.; KOLONIUK, I.; KONDŌ, H.; KOONIN, V.; KRUPOVIC, M.; KUBOTA, K.; KURATH, G.; LAENEN, L.; LAMBERT, A. J.; LANGEVIN, S. L.; LEE, B.; LEFKOWITZ, E. J.; LI, L.; LEROY, E. M.; LI, S.; LÍ, J.; LIU, H.; LUKASHEVICH, I. S.; MAES, P.; SOUZA, W. M. de; MARKLEWITZ, M.; MARSHALL, S. H.; MARZANO, S. L.; MASSART, S.; MCCAULEY, J. W.; MELZER, M.; MILLER, K. M.; MING, T. J.; MIRAZIMI, A.; MORDECAI, G. J.; MÜHLBACH, H. P.; MÜHLBERGER, E.; NAIDU, R.; NATSUAKI, T.; NAVARRO, J. A.; NETESOV, S. Y V.; NEUMANN, G.; NOWOTNY, N.; NUNES, M. R. T.; VELARDE, A. O.; PALACIOS, G.; PALLÁS, V.; PÁLYI, B.; PAPA, A.; PARASKEVOPOULOU, S.; PARK, A. C.; PARRISH, C. R.; PATTERSON, D. A.; CORRÊA, A. P.; PAWESKA, J. T.; PAYNE, S.; PERACCHIO, C.; PÉREZ, D. R.; POSTLER, T. S.; QI, L.; RADOSHITZKY, S. R.; RESENDE, R. O.; REYES, C. A.; RIMA, B. K.; LUNA, G. R.; ROMANOWSKI, V.; ROTA, P.; RUBBENSTROTH, D.; RUBINO, L.; RUNSTADLER, J. A.; SABANADZOVIC, S.; SALL, A. A.; SALVATO, M. S.; SANG, R.; SASAYA, T.; SCHULZE, A. D.; SCHWEMMLE, M.; SHI, M.; SHÍ, X.; SHIMOMOTO, Y.; SHIRAKO, Y.; SIDDELL, S. G.; SIMMONDS, P.; SIRONI, M.; SMAGGHE, G.; SMITHER, S.; SONG, J. W.; SPANN, K.; SPENGLER, J. R.; STENGLEIN, M. D.; STONE, D. M.; SUGANO, J.; TABATA, A.; TAKADA, A.; TAKEUCHI, S.; TCHOUASSI, D. P.; TEFER, A.; TESH, R. B.; THORNBURG, N. J.; TOMITAKA, Y.; TOMONAGA, K.; TORDO, N.; TORTO, B.; TOWNER, J. S.; TSUDA, S.; TU, C.; TURINA, M.; TZANETAKIS, I. E.; UCHIDA, J.; USUGI, T.; VAIRA, A. M.; VALLINO, M.; VAN DEN HOOGEN, B.; VARSANI, A.; VASILAKIS, N.; VERBEEK, M.; BARGEN, S. V.; WADA, J.; WAHL, V.; WALKER, P. J.; WANG, L. F.; WANG, G.; WANG, Y.; WANG, Y.; WAQAS, M.; WÈI, T.; WEN, S.; WHITFELD, A. E.; WILLIAMS, J. V.; WOLF, Y. I.; WU, J.; XU, L.; YANAGISAWA, H.; YANG, C.; YANG, Z.; ZERBINI, F. M.; ZHAI, L.; ZHANG, Y. Z.; ZHANG, O.; ZHANG, J.; ZHANG, Z.; ZHOU, X. 2021 Taxonomic update of phylum Negarnaviricota (Riboviria: Orthornavirae), including the large orders Bunyavirales and Mononegavirale. Archives of Virology, August, 2021.| Biblioteca(s): Embrapa Mandioca e Fruticultura. |
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| 2. | | MATTOS, P. P. de; SALIS, S. M. de; BRAZ, E. M.; GARRASTAZU, M. C. Aplicação da dendrocronologia no Pantanal Sul- Matogrossense. CONGRESSO NACIONAL DE BOTÂNCIA, 61., 2010, Manaus. Diversidade vegetal brasileira: conhecimento, conservação e uso. Manaus: Sociedade Botânica do Brasil, 2010. p. 239 -242. Conferências, simpósios e mesas-redondas.| Biblioteca(s): Embrapa Pantanal. |
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| 12. | | Brazilian Flora 2020: Leveraging the power of a collaborative scientific network. Taxon, v. 71, n. 1, p. 178-198, Feb. 2022. Autores Embrapa: Bruno Machado Teles Walter, Gustavo Heiden, José Francisco Montenegro Valls, Luciano de Bem Bianchetti, Marcelo Fragomeni Simon, Marta Camargo de Assis, Taciana Barbosa Cavalcanti.| Biblioteca(s): Embrapa Clima Temperado. |
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| Registros recuperados : 3.908 | |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Clima Temperado. Para informações adicionais entre em contato com cpact.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Clima Temperado. |
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Data corrente: |
24/03/2020 |
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Data da última atualização: |
09/06/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
DUTRA, L. M.; SANTOS, A. D. da C.; LOURENÇO, A. V. F.; NAGATA, N.; HEIDEN, G.; CAMPOS, F. R.; BARISON, A. |
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Afiliação: |
LIVIA MACEDO DUTRA; ALAN DIEGO DA CONCEIÇÃO SANTOS; ALLAN VINICIUS FELIX LOURENÇO; NOEMI NAGATA; GUSTAVO HEIDEN, CPACT; FRANCINETE RAMOS CAMPOS; ANDERSSON BARISON. |
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Título: |
1H HR-MAS NMR and chemometric methods for discrimination and classification of Baccharis (Asteraceae): A proposal for quality control of Baccharis trimera. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Journal of Pharmaceutical and Biomedical Analysis, v. 184, 113200, 2020. |
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ISSN: |
0731-7085 |
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DOI: |
https://doi.org/10.1016/j.jpba.2020.113200 |
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Idioma: |
Inglês |
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Conteúdo: |
Baccharis trimera is a species recognized by health agencies and recommended by the Brazilian Pharmacopoeia by having medicinal properties. In this work, HR-MAS NMR spectroscopy combined with chemometric tools, such as Principal Components Analysis (PCA), Partial Least Squares Discriminant Analysis (PLS-DA) and Soft Independent Modeling by Class Analogy (SIMCA), were used to evaluate the quality control and authenticity of commercial samples of Baccharis, as well as to discriminate B. trimera samples from other species of the Caulopterae section (B. articulata, B. trimera, B. junciformis, B. milleflora, and B. myriocephala). The high morphological similarity of these species makes it difficult for their identifications and discriminations, even by taxonomists. Different PCA pre-processing (autoscaling, Pareto scaling, and mean centering) allowed to discriminate B. trimera and B. myriocephala from the other species, mainly due to the presence of carquejyl acetate, indicated their chemical similarity. The 1H HR-MAS NMR spectral profile offers the possibility of tracking not only the chemical markers, such as the presence of carquejyl acetate, which can also be helpful in the B. trimera authentication/identification. The application of classification methods in standard samples revealed that PLS-DA models showed better performance on the calibration and validation sets than SIMCA model. However, PLS-DA and SIMCA applied to commercial samples showed that none ofthe commercial samples were classified as B. trimera, which suggested the lack of strict quality control regarding these products. The methodology developed in the present work might contribute to chemotaxonomy of the genus Baccharis. MenosBaccharis trimera is a species recognized by health agencies and recommended by the Brazilian Pharmacopoeia by having medicinal properties. In this work, HR-MAS NMR spectroscopy combined with chemometric tools, such as Principal Components Analysis (PCA), Partial Least Squares Discriminant Analysis (PLS-DA) and Soft Independent Modeling by Class Analogy (SIMCA), were used to evaluate the quality control and authenticity of commercial samples of Baccharis, as well as to discriminate B. trimera samples from other species of the Caulopterae section (B. articulata, B. trimera, B. junciformis, B. milleflora, and B. myriocephala). The high morphological similarity of these species makes it difficult for their identifications and discriminations, even by taxonomists. Different PCA pre-processing (autoscaling, Pareto scaling, and mean centering) allowed to discriminate B. trimera and B. myriocephala from the other species, mainly due to the presence of carquejyl acetate, indicated their chemical similarity. The 1H HR-MAS NMR spectral profile offers the possibility of tracking not only the chemical markers, such as the presence of carquejyl acetate, which can also be helpful in the B. trimera authentication/identification. The application of classification methods in standard samples revealed that PLS-DA models showed better performance on the calibration and validation sets than SIMCA model. However, PLS-DA and SIMCA applied to commercial samples showed that none ofthe commercial sa... Mostrar Tudo |
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Palavras-Chave: |
Baccharis trimera; Caulopterae; Espectroscopia; Quimiotaxonomia. |
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Thesagro: |
Baccharis; Taxonomia. |
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Categoria do assunto: |
-- |
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Marc: |
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001 2121354
005 2020-06-09
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022 $a0731-7085
024 7 $ahttps://doi.org/10.1016/j.jpba.2020.113200$2DOI
100 1 $aDUTRA, L. M.
245 $a1H HR-MAS NMR and chemometric methods for discrimination and classification of Baccharis (Asteraceae)$bA proposal for quality control of Baccharis trimera.$h[electronic resource]
260 $c2020
520 $aBaccharis trimera is a species recognized by health agencies and recommended by the Brazilian Pharmacopoeia by having medicinal properties. In this work, HR-MAS NMR spectroscopy combined with chemometric tools, such as Principal Components Analysis (PCA), Partial Least Squares Discriminant Analysis (PLS-DA) and Soft Independent Modeling by Class Analogy (SIMCA), were used to evaluate the quality control and authenticity of commercial samples of Baccharis, as well as to discriminate B. trimera samples from other species of the Caulopterae section (B. articulata, B. trimera, B. junciformis, B. milleflora, and B. myriocephala). The high morphological similarity of these species makes it difficult for their identifications and discriminations, even by taxonomists. Different PCA pre-processing (autoscaling, Pareto scaling, and mean centering) allowed to discriminate B. trimera and B. myriocephala from the other species, mainly due to the presence of carquejyl acetate, indicated their chemical similarity. The 1H HR-MAS NMR spectral profile offers the possibility of tracking not only the chemical markers, such as the presence of carquejyl acetate, which can also be helpful in the B. trimera authentication/identification. The application of classification methods in standard samples revealed that PLS-DA models showed better performance on the calibration and validation sets than SIMCA model. However, PLS-DA and SIMCA applied to commercial samples showed that none ofthe commercial samples were classified as B. trimera, which suggested the lack of strict quality control regarding these products. The methodology developed in the present work might contribute to chemotaxonomy of the genus Baccharis.
650 $aBaccharis
650 $aTaxonomia
653 $aBaccharis trimera
653 $aCaulopterae
653 $aEspectroscopia
653 $aQuimiotaxonomia
700 1 $aSANTOS, A. D. da C.
700 1 $aLOURENÇO, A. V. F.
700 1 $aNAGATA, N.
700 1 $aHEIDEN, G.
700 1 $aCAMPOS, F. R.
700 1 $aBARISON, A.
773 $tJournal of Pharmaceutical and Biomedical Analysis$gv. 184, 113200, 2020.
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