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Registros recuperados : 69 | |
10. | | SIMEONE, M. L. F.; PARRELLA, R. A. da C.; DAMASCENO, C. M. B.; SCHAFFERT, R. E. Prediction of high-biomass sorghum quality using near infrared spectroscopy to monitoring calorific value, moisture, and ash content. International Journal of Development Research, v. 10, n. 9, p. 40916-40920, 2020. Biblioteca(s): Embrapa Milho e Sorgo. |
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12. | | DAMASCENO, C. M. B.; PARRELLA, R. A. da C.; SIMEONE, M. L. F.; SCHAFFERT, R. E.; MAGALHAES, J. V. de. Caracterização bioquímica de genótipos de sorgo quanto ao teor de lignina e análise molecular de rotas metabólicas visando à produção de etanol de segunda geração. In: CONGRESSO NACIONAL DE MILHO E SORGO, 28.; SIMPÓSIO BRASILEIRO SOBRE A LAGARTA DO CARTUCHO, 4., 2010, Goiânia. Potencialidades, desafios e sustentabilidade: resumos expandidos... Sete Lagoas: ABMS, 2010. 1 CD-ROM. Biblioteca(s): Embrapa Milho e Sorgo. |
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15. | | DAMASCENO, C. M. B.; PARRELLA, R. A. C.; SIMEONE, M. L. P.; SCHAFFERT, R. E.; MAGALHAES, J. V. Biochemical and molecular analysis of bioenergy sorghums for variation in lignin content. In: PAN AMERICAN CONGRESS ON PLANTS AND BIOENERGY, 2., 2010, São Pedro, São Paulo. [Abstracts]. São Pedro: [s.n.], 2010. p. 21-22. Biblioteca(s): Embrapa Milho e Sorgo. |
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17. | | RIBEIRO, P. B.; BARROS, B. de A.; PARRELLA, R. A. da C.; SCHAFFERT, R. E.; DAMASCENO, C. M. B. Análise de expressão de genes relacionados à biossíntese de lignina em sorgo. In: ENCONTRO DA REDE DE PESQUISA, DESENVOLVIMENTO E INOVAÇÃO EM BIOCOMBUSTÍVEIS EM MINAS GERAIS, 7., 2012, Sete Lagoas. [Anais]. [S.l.: s.n.], 2012. Biblioteca(s): Embrapa Milho e Sorgo. |
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19. | | PARRELLA, R. A. da C.; MAY, A.; SIMEONE, M. L. F.; DAMASCENO, C. M. B.; SCHAFFERT, R. E. Sorgo bioenergia. In: PEREIRA FILHO, I. A.; RODRIGUES, J. A. S. (Ed.). Sorgo: o produtor pergunta, a Embrapa responde. Brasília, DF: Embrapa, 2015. cap. 17, p. 281-291. (Coleção 500 perguntas, 500 respostas). Biblioteca(s): Embrapa Milho e Sorgo. |
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Registro Completo
Biblioteca(s): |
Embrapa Milho e Sorgo. |
Data corrente: |
22/10/2020 |
Data da última atualização: |
29/10/2020 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 2 |
Autoria: |
SIMEONE, M. L. F.; PARRELLA, R. A. da C.; DAMASCENO, C. M. B.; SCHAFFERT, R. E. |
Afiliação: |
MARIA LUCIA FERREIRA SIMEONE, CNPMS; RAFAEL AUGUSTO DA COSTA PARRELLA, CNPMS; CYNTHIA MARIA BORGES DAMASCENO, CNPMS; ROBERT EUGENE SCHAFFERT, CNPMS. |
Título: |
Prediction of high-biomass sorghum quality using near infrared spectroscopy to monitoring calorific value, moisture, and ash content. |
Ano de publicação: |
2020 |
Fonte/Imprenta: |
International Journal of Development Research, v. 10, n. 9, p. 40916-40920, 2020. |
Idioma: |
Inglês |
Conteúdo: |
High-biomass sorghum is a crop that has great potential as a source of biomass for energy generation, due to its high productivity, drought tolerance and for being mechanizable. Thus, culture is an alternative to vegetable biomass to be used in electric energy cogeneration processes. The objective of the work was to develop multivariate calibration models, using the near infrared spectroscopy, for analysis of gross calorific value, moisture, and ash content in high-sorghum biomass. At samples were analyzed by reference methods and the results associated with the near infrared spectrum of each sample. Then they were developed for each parameter, multivariate calibration models using the partial least square (PLS) algorithm. A high correlation was obtained between the values predicted by the model and the values obtained by reference method for all properties evaluated. Ratio of prediction to deviation (RPD) and range error ratio (RER) values, respectively, above 3 and 10, for all the models constructed, thus being considered adequate for carrying out quantitative analyzes of chemical composition in the qualification of the sorghum biomass as a source of raw material for energy cogeneration and optimization of biomass conversion technologies. |
Palavras-Chave: |
Calibração multivariada; Espectroscopia. |
Thesagro: |
Análise de Laboratório; Biocombustível; Biomassa; Energia. |
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/216918/1/Prediction-high.pdf
|
Marc: |
LEADER 02027naa a2200229 a 4500 001 2125761 005 2020-10-29 008 2020 bl uuuu u00u1 u #d 100 1 $aSIMEONE, M. L. F. 245 $aPrediction of high-biomass sorghum quality using near infrared spectroscopy to monitoring calorific value, moisture, and ash content.$h[electronic resource] 260 $c2020 520 $aHigh-biomass sorghum is a crop that has great potential as a source of biomass for energy generation, due to its high productivity, drought tolerance and for being mechanizable. Thus, culture is an alternative to vegetable biomass to be used in electric energy cogeneration processes. The objective of the work was to develop multivariate calibration models, using the near infrared spectroscopy, for analysis of gross calorific value, moisture, and ash content in high-sorghum biomass. At samples were analyzed by reference methods and the results associated with the near infrared spectrum of each sample. Then they were developed for each parameter, multivariate calibration models using the partial least square (PLS) algorithm. A high correlation was obtained between the values predicted by the model and the values obtained by reference method for all properties evaluated. Ratio of prediction to deviation (RPD) and range error ratio (RER) values, respectively, above 3 and 10, for all the models constructed, thus being considered adequate for carrying out quantitative analyzes of chemical composition in the qualification of the sorghum biomass as a source of raw material for energy cogeneration and optimization of biomass conversion technologies. 650 $aAnálise de Laboratório 650 $aBiocombustível 650 $aBiomassa 650 $aEnergia 653 $aCalibração multivariada 653 $aEspectroscopia 700 1 $aPARRELLA, R. A. da C. 700 1 $aDAMASCENO, C. M. B. 700 1 $aSCHAFFERT, R. E. 773 $tInternational Journal of Development Research$gv. 10, n. 9, p. 40916-40920, 2020.
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