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![](/consulta/web/img/deny.png) | Acesso ao texto completo restrito à biblioteca da Embrapa Rondônia. Para informações adicionais entre em contato com cpafro.biblioteca@embrapa.br. |
Registro Completo |
Biblioteca(s): |
Embrapa Rondônia. |
Data corrente: |
06/02/2018 |
Data da última atualização: |
06/02/2018 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
LUNA, A. S.; SILVA, A. P. da; ALVES, E. A.; ROCHA, R. B.; LIMA, I. C. A.; GOIS, J. S. de. |
Afiliação: |
Aderval S. Luna, UFRJ; Arnaldo P. da Silva, UFRJ; ENRIQUE ANASTACIO ALVES, CPAF-Rondonia; RODRIGO BARROS ROCHA, CPAF-Rondonia; Igor C. A. Lima, UFRJ; Jefferson S. de Gois, UFRJ. |
Título: |
Evaluation of chemometric methodologies for the classification of Coffea canephora cultivars via FT-NIR spectroscopy and direct sample analysis. |
Ano de publicação: |
2017 |
Fonte/Imprenta: |
Analytical Methods, v. 9, p. 4255-4260, 2017. |
Idioma: |
Inglês |
Conteúdo: |
his work presents a study of chemometric tools for the classification of Coffea canephora (whole beans) cultivars via in situ direct sample analysis using near-infrared spectroscopy (NIR). The sample pretreatment was carried out by washing and sun-drying the coffee beans and then selecting only non-defective coffee beans. A near-infrared reflectance accessory was used for direct sample analysis. The NIR spectra were baseline-aligned, mean centered, and smoothed using Savitzky?Golay polynomial order zero with 15 points window mean centered data, and the first derivative was calculated. The principal component analysis results demonstrated the formation of different clusters that were further related to the presence of lipids, water, caffeine, chlorogenic acids, sugars, proteins, and carbohydrates (based on the plot of loadings versus wavenumber). Partial least squares discriminant analysis (PLS-DA), soft independent modeling of class analogy (SIMCA), self-organizing map (SOM), and support vector machine (SVM) were applied for the classification of different cultivars of coffee. The best results were achieved using SOM that provided 100.0% correct identification of the validation samples, whereas PLS-DA, SIMCA, SVM (3 PCs), and SVM (4 PCs) provided 82.9, 99.6, 82.9, and 99.6%, respectively. The performance of the methodologies was evaluated using the Matthews correlation coefficient, which confirmed that SOM presented the best results for all the classes. |
Palavras-Chave: |
Café conilon; NIR. |
Thesaurus Nal: |
near-infrared spectroscopy. |
Categoria do assunto: |
-- |
Marc: |
LEADER 02156naa a2200217 a 4500 001 2087188 005 2018-02-06 008 2017 bl uuuu u00u1 u #d 100 1 $aLUNA, A. S. 245 $aEvaluation of chemometric methodologies for the classification of Coffea canephora cultivars via FT-NIR spectroscopy and direct sample analysis.$h[electronic resource] 260 $c2017 520 $ahis work presents a study of chemometric tools for the classification of Coffea canephora (whole beans) cultivars via in situ direct sample analysis using near-infrared spectroscopy (NIR). The sample pretreatment was carried out by washing and sun-drying the coffee beans and then selecting only non-defective coffee beans. A near-infrared reflectance accessory was used for direct sample analysis. The NIR spectra were baseline-aligned, mean centered, and smoothed using Savitzky?Golay polynomial order zero with 15 points window mean centered data, and the first derivative was calculated. The principal component analysis results demonstrated the formation of different clusters that were further related to the presence of lipids, water, caffeine, chlorogenic acids, sugars, proteins, and carbohydrates (based on the plot of loadings versus wavenumber). Partial least squares discriminant analysis (PLS-DA), soft independent modeling of class analogy (SIMCA), self-organizing map (SOM), and support vector machine (SVM) were applied for the classification of different cultivars of coffee. The best results were achieved using SOM that provided 100.0% correct identification of the validation samples, whereas PLS-DA, SIMCA, SVM (3 PCs), and SVM (4 PCs) provided 82.9, 99.6, 82.9, and 99.6%, respectively. The performance of the methodologies was evaluated using the Matthews correlation coefficient, which confirmed that SOM presented the best results for all the classes. 650 $anear-infrared spectroscopy 653 $aCafé conilon 653 $aNIR 700 1 $aSILVA, A. P. da 700 1 $aALVES, E. A. 700 1 $aROCHA, R. B. 700 1 $aLIMA, I. C. A. 700 1 $aGOIS, J. S. de 773 $tAnalytical Methods$gv. 9, p. 4255-4260, 2017.
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![](/consulta/web/img/deny.png) | Acesso ao texto completo restrito à biblioteca da Embrapa Hortaliças. Para informações adicionais entre em contato com cnph.biblioteca@embrapa.br. |
Registro Completo
Biblioteca(s): |
Embrapa Hortaliças. |
Data corrente: |
14/06/1996 |
Data da última atualização: |
14/06/1996 |
Autoria: |
BOITEUX, L. S.; CUPERTINO, F. P.; SILVA, C.; DUSI, A. N.; MONTE-NESHICH, D.C.; VLUGT, R. A. A. van der; FONSECA, M. E. N. |
Afiliação: |
EMBRAPA-CNPH. |
Título: |
Resistance to potato virus Y (pathotype 1-2) in Capsicum annuum and Capsicum chinense is controlled by two independent major genes. |
Ano de publicação: |
1996 |
Fonte/Imprenta: |
Euphytica, v.87, n.1, p.53-58, 1996. |
Idioma: |
Inglês |
Palavras-Chave: |
Capsicum spp; Disease; Pathotype 1-2; PVY; Resistance. |
Thesagro: |
Capsicum Annuum; Capsicum Chinense; Cerrado; Doença; Pimentão; Resistência; Vírus. |
Thesaurus NAL: |
pepper; Potyvirus. |
Categoria do assunto: |
-- |
Marc: |
LEADER 00943naa a2200349 a 4500 001 1754984 005 1996-06-14 008 1996 bl uuuu u00u1 u #d 100 1 $aBOITEUX, L. S. 245 $aResistance to potato virus Y (pathotype 1-2) in Capsicum annuum and Capsicum chinense is controlled by two independent major genes. 260 $c1996 650 $apepper 650 $aPotyvirus 650 $aCapsicum Annuum 650 $aCapsicum Chinense 650 $aCerrado 650 $aDoença 650 $aPimentão 650 $aResistência 650 $aVírus 653 $aCapsicum spp 653 $aDisease 653 $aPathotype 1-2 653 $aPVY 653 $aResistance 700 1 $aCUPERTINO, F. P. 700 1 $aSILVA, C. 700 1 $aDUSI, A. N. 700 1 $aMONTE-NESHICH, D.C. 700 1 $aVLUGT, R. A. A. van der 700 1 $aFONSECA, M. E. N. 773 $tEuphytica$gv.87, n.1, p.53-58, 1996.
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