| |
|
|
| Registros recuperados : 17 | |
| 6. |  | GUIMARAES, C. C.; ASSIS, C.; SIMEONE, M. L. F.; SENA, M. M. Use of near-infrared spectroscopy, partial least-squares, and ordered predictors selection to predict four quality parameters of sweet sorghum juice used to produce bioethanol. Energy & Fuels, Washington, v. 30, p. 4137- 4144, 2016.| Biblioteca(s): Embrapa Milho e Sorgo. |
|    |
| 8. | | GUIMARÃES, C. C.; ROSA, S. D. V. F. da; MALTA, M. R.; CARVALHO, M. H.; OLIVEIRA, R. M. E. Lipid content and fatty acid profile in Embryos, endosperm, and seeds of dried Coffea arabica. In: INTERNATIONAL CONFERENCE ON COFFEE SCIENCE, 26., 2016, Kunming,Yunnan, China. Proceedings... ASIC - Association for Science and Information on Coffee, 2016. p. 120.| Biblioteca(s): Embrapa Café. |
|  |
| 10. | | SALAZAR, D. U.; DEMATTÊ, J. A. M.; VICENTE, L. E.; GUIMARAES, C. C.; PADILHA, M. C. de C.; MELLO, F. A. de O.; SOUZA, A. B. Emissividade via laboratório e satélite como abordagem na análise textural de solos. In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 19., 2019, Santos. Anais... São José dos Campos: INPE, 2019. Artigo 95977. p. 1-4.| Biblioteca(s): Embrapa Meio Ambiente. |
| |
| 11. | | SALAZAR, D. U.; DEMATTÊ, J. A. M.; VICENTE, L. E.; GUIMARÃES, C. C.; SOUZA, A. B. de; INFORSATO, L.; CARVALHO, H. W. L. de. Spectral range (FRX-VIS-NIR-SWIR-MIR) interaction on the organic matter prediction. In: WORLD CONGRESS OF SOIL SCIENCE, 21., 2018, Rio de Janeiro. Soil science: beyond food and fuel: abstracts. Viçosa, MG: SBCS, 2018. Trabalho 392.| Biblioteca(s): Embrapa Meio Ambiente. |
| |
| 12. | | URBINA SALAZAR, D. F.; DEMATTÊ, J. A. M.; VICENTE, L. E.; GUIMARAES, C. C. B.; SAYÃO, V. M.; CERRI, C. E. P.; PADILHA, M. C. de C.; MENDES, W. de S. Emissivity of agricultural soil attributes in southeastern Brazil via terrestrial and satellite sensors. Geoderma, v. 361, article 114038, 2020.| Biblioteca(s): Embrapa Meio Ambiente. |
| |
| 13. | | CARVALHO, M. H. de; ROSA, S. D. V. F. da; COELHO, S. V. B.; GUIMARÃES, C. C.; MARTINS, R. de S.; CLEMENTE, A. da C. S.; PAIVA, L. V. Drying of arabica coffee and its effect on the gene expression and activity of enzymes linked to seed physiological quality. Acta Scientiarum: Agronomy, v. 45, e56908, 2023.| Biblioteca(s): Embrapa Café. |
| |
| 14. | | GUIMARÃES, M. F. (Org).; TAVARES FILHO, J.; GUIMARÃES, C. C. M.; CASTRO FILHO, C.; VAZ, C. M. P.; MORAES, M. H.; ZIMBACH, C. R. L.; JORGE, L. A. C.; RALISCH, R. Manual de metodologias para avaliação de manejo do solo. Londrina : Editora UEL, 1999.| Biblioteca(s): Embrapa Instrumentação. |
| |
| 15. | | SANTOS, U. J. dos; DEMATTÊ, J. A. de M.; MENEZES, R. S. C.; DOTTO, A. C.; GUIMARÃES, C. C. B.; ALVES, B. J. R.; PRIMO, D. C.; SAMPA, E. V. de S. B. Predicting carbon and nitrogen by visible near-infrared (Vis-NIR) .and mid-infrared (MIR) spectroscopy in soils of Northeast Brazil Geoderma Regional, v. 23, e00333, December 2020.| Biblioteca(s): Embrapa Agrobiologia. |
| |
| 16. | | PADILHA, M. C. de C.; VICENTE, L. E.; DEMATTÊ, J. A. M.; LOEBMANN, D. G. dos S. W.; VICENTE, A. K.; URBINA SALAZAR, D. F.; GUIMARÃES, C. C. B. Using Landsat and soil clay content to map soil organic carbon of oxisols and Ultisols near São Paulo, Brazil. Geoderma Regional, v. 21, e00253, 2020.| Biblioteca(s): Embrapa Meio Ambiente. |
| |
| 17. | | DEMATTÊ, J. A. M.; DOTTO, A. C.; PAIVA, A. F. S.; SATO, M. V.; DALMOLIN, R. S. D.; ARAÚJO, M. do S. B. de; SILVA, E. B. da; NANNI, M. R.; CATEN, A. ten; NORONHA, N. C.; LACERDA, M. P. C.; ARAUJO FILHO, J. C. de; RIZZO, R.; BELLINASO, H.; FRANCELINO, M. R.; SCHAEFER, C. E. G. R.; VICENTE, L. E.; SANTOS, U. J. dos; SAMPAIO, E. V. de S. B.; MENEZES, R. S. C.; SOUZA, J. J. L. L. de; ABRAHÃO, W. A. P.; COELHO, R. M.; GREGO, C. R.; LANI, J. L.; FERNANDES, A. R.; GONÇALVES, D. A. M.; SILVA, S. H. G.; MENEZES, M. D. de; CURI, N.; COUTO, E. G.; ANJOS, L. H. C. dos; CEDDIA, M. B.; PINHEIRO, E. F. M.; GRUNWALD, S.; VASQUES, G. de M.; MARQUES JÚNIOR, J.; SILVA, A. J. da; BARRETO, M. C. de V.; NÓBREGA, G. N.; SILVA, M. Z. da; SOUZA, S. F. de; VALLADARES, G. S.; VIANA, J. H. M.; TERRA, F. da S.; HORÁK-TERRA, I.; FIORIO, P. R.; SILVA, R. C. da; FRADE JÚNIOR, E. F.; LIMA, R. H. C.; FILIPPINI ALBA, J. M.; SOUZA JUNIOR, V. S. de; BREFIN, M. de L. M. S.; RUIVO, M. de L. P.; FERREIRA, T. O.; BRAIT, M. A.; CAETANO, N. R.; BRINGHENTI, I.; MENDES, W. de S.; SAFANELLI, J. L.; GUIMARÃES, C. C. B.; POPPIEL, R. R.; SOUZA, A. B. e; QUESADA, C. A.; COUTO, H. T. Z. do. The Brazilian Soil Spectral Library (BSSL): a general view, application and challenges. Geoderma, v. 354, 113793, 2019. Na publicação: Gustavo M. Vasques.| Biblioteca(s): Embrapa Agricultura Digital; Embrapa Clima Temperado; Embrapa Cocais; Embrapa Meio Ambiente; Embrapa Milho e Sorgo; Embrapa Solos. |
| |
| Registros recuperados : 17 | |
|
|
|
 | Acesso ao texto completo restrito à biblioteca da Embrapa Milho e Sorgo. Para informações adicionais entre em contato com cnpms.biblioteca@embrapa.br. |
Registro Completo
|
Biblioteca(s): |
Embrapa Milho e Sorgo. |
|
Data corrente: |
20/07/2016 |
|
Data da última atualização: |
24/02/2017 |
|
Tipo da produção científica: |
Artigo em Periódico Indexado |
|
Circulação/Nível: |
A - 2 |
|
Autoria: |
GUIMARAES, C. C.; ASSIS, C.; SIMEONE, M. L. F.; SENA, M. M. |
|
Afiliação: |
MARIA LUCIA FERREIRA SIMEONE, CNPMS. |
|
Título: |
Use of near-infrared spectroscopy, partial least-squares, and ordered predictors selection to predict four quality parameters of sweet sorghum juice used to produce bioethanol. |
|
Ano de publicação: |
2016 |
|
Fonte/Imprenta: |
Energy & Fuels, Washington, v. 30, p. 4137- 4144, 2016. |
|
DOI: |
10.1021/acs.energyfuels.6b00408 |
|
Idioma: |
Inglês |
|
Conteúdo: |
Sweet sorghum juice is gaining importance as a raw material for the first-generation ethanol production in the period between harvests of sugar cane. Breeding programs are seeking to improve sorghum quality to increase productivity, what has generated an excessive number of samples to be analyzed. Thus, the aim of this paper was to develop rapid and low-cost methods based on partial least-squares (PLS) and near-infrared spectroscopy (NIRS) for the determination of four quality chemical parameters of sweet sorghum. Spectra were recorded with a transflectance accessory, and robust models were built with 500 samples obtained from more than 200 hybrids and inbred strains. Optimization by variable selection was carried out with ordered predictors selection (OPS), providing simpler, more interpretable and predictive multivariate calibration models. The methods were developed in the working ranges of 5.5−18.1° Brix, 1.2−5.2%, 0.3−13.0%, and 9.8−83.0% for degrees Brix, reducing sugars, polarizable sugars, and apparent purity, respectively. Root-mean-square errors of prediction (RMSEP) of 0.3° Brix, 0.3%, 0.6%, and 5.3% were obtained for these four parameters, respectively. Finally, a complete multivariate analytical validation was carried out, and the methods were considered linear, accurate, sensitive, and without bias. |
|
Thesagro: |
Análise de Laboratório; Etanol; Química; Sorgo açucareiro. |
|
Categoria do assunto: |
-- |
|
Marc: |
LEADER 02105naa a2200217 a 4500
001 2049288
005 2017-02-24
008 2016 bl uuuu u00u1 u #d
024 7 $a10.1021/acs.energyfuels.6b00408$2DOI
100 1 $aGUIMARAES, C. C.
245 $aUse of near-infrared spectroscopy, partial least-squares, and ordered predictors selection to predict four quality parameters of sweet sorghum juice used to produce bioethanol.$h[electronic resource]
260 $c2016
520 $aSweet sorghum juice is gaining importance as a raw material for the first-generation ethanol production in the period between harvests of sugar cane. Breeding programs are seeking to improve sorghum quality to increase productivity, what has generated an excessive number of samples to be analyzed. Thus, the aim of this paper was to develop rapid and low-cost methods based on partial least-squares (PLS) and near-infrared spectroscopy (NIRS) for the determination of four quality chemical parameters of sweet sorghum. Spectra were recorded with a transflectance accessory, and robust models were built with 500 samples obtained from more than 200 hybrids and inbred strains. Optimization by variable selection was carried out with ordered predictors selection (OPS), providing simpler, more interpretable and predictive multivariate calibration models. The methods were developed in the working ranges of 5.5−18.1° Brix, 1.2−5.2%, 0.3−13.0%, and 9.8−83.0% for degrees Brix, reducing sugars, polarizable sugars, and apparent purity, respectively. Root-mean-square errors of prediction (RMSEP) of 0.3° Brix, 0.3%, 0.6%, and 5.3% were obtained for these four parameters, respectively. Finally, a complete multivariate analytical validation was carried out, and the methods were considered linear, accurate, sensitive, and without bias.
650 $aAnálise de Laboratório
650 $aEtanol
650 $aQuímica
650 $aSorgo açucareiro
700 1 $aASSIS, C.
700 1 $aSIMEONE, M. L. F.
700 1 $aSENA, M. M.
773 $tEnergy & Fuels, Washington$gv. 30, p. 4137- 4144, 2016.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Milho e Sorgo (CNPMS) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
Fechar
|
| Nenhum registro encontrado para a expressão de busca informada. |
|
|
