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Registros recuperados : 24 | |
1. | | RAMOS, S. B.; NUNES, B. N.; LEDUR, M. C.; NONES, K.; KLEIN, C. H.; COUTINHO, L. L.; MUNARI, D. P. Associações genéticas e ambientais entre peso corporal ao abate e deposição de gordura na carcaça de aves resultantes do cruzamento de linhagens de corte e postura. In: CONGRESSO BRASILEIRO DE GENÉTICA, 53., 2007, Águas de Lindóia. Anais. Águas de Lindóia: SGB, 2007. p. 167. Projeto n. 01.02.10.210-10. Biblioteca(s): Embrapa Suínos e Aves. |
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2. | | SAVEGNAGO, R. P.; RAMOS, S. B.; CAETANO, S. L.; LEDUR, M. C.; SCHMIDT, G. S.; MUNARI, D. P. Associações genéticas entre características de qualidade do ovo e produção de ovos em uma linhagem de aves de postura In: CONGRESSO BRASILEIRO DE GENÉTICA, 55, 2009, Águas de Lindóia. Anais... Águas de Lindóia:SBG, 2009. p. 155. Projeto/Plano de Ação: 01.06.106.03-05 Biblioteca(s): Embrapa Suínos e Aves. |
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5. | | NUNES, B. N.; RAMOS, S. B.; BONASSI, C. A.; LEDUR, M. C.; NONES, K.; COUTINHO, L. L.; MUNARI, D. P. Parâmetros genéticos e ambientais de rendimento e composição de carcaça de aves resultantes de cruzamento recíproco de linhagens de corte e postura. In: CONGRESSO BRASILEIRO DE GENÉTICA, 53., 2007, Águas de Lindóia. Anais. Águas de Lindóia: SBG, 2007. p. 246 Projeto n. 01.02.10.210-10. Biblioteca(s): Embrapa Suínos e Aves. |
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6. | | RAMOS, S. B.; SAVEGNAGO, R. P.; ZUIN, R. G.; LEDUR, M. C.; FIGUEIREDO, E. A. P. de; MUNARI, D. P. Comparação de modelos não lineares para o ajuste da produção de ovos de aves selecionadas para postura In: CONGRESSO BRASILEIRO DE GENÉTICA, 55, 2009, Águas de Lindóia. Anais... Águas de Lindóia:SBG, 2009. p. 156. Projeto/Plano de Ação: 01.06.106.03-05 Biblioteca(s): Embrapa Suínos e Aves. |
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7. | | SAVEGNAGO, R. P.; BUZANSKAS, M. E.; NUNES, B. do N.; RAMOS, S. B.; LEDUR, M. C.; NONES, K.; MUNARI, D. P. Heritabilities and genetic correlations for reproductive traits in an F2 reciprocal cross chicken population. Genetics and Molecular Research, v. 10, n. 3, p. 1247-1254, 2011. Projeto: 01.06.01.003. Biblioteca(s): Embrapa Suínos e Aves. |
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8. | | NUNES, B. do N.; RAMOS, S. B.; SAVEGNAGO, R. P.; LEDUR, M. C.; NONES, K.; KLEIN, C. H.; MUNARI, D. P. Genetic parameters for body weight, carcass chemical composition and yield in a broiler-layer cross developed for QTL mapping. Genetics and Molecular Biology, Ribeirão Preto, v. 34, n. 3, p. 429-434, 2011. Projeto/Plano de Ação: 01.06.10.603-05. Biblioteca(s): Embrapa Suínos e Aves. |
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9. | | ROSOLEM, M. C.; VASCONCELOS, R. O.; GARRIDO, E.; CASTANHEIRA, T. L. L.; MOREIRA, P. R. R.; MAGALHÃES, G. M.; ROZZA, D. B.; RAMOS, S. B. Immunodetection of myeloid and plasmacytoid dendritic cells in mammary carcinomas of female dogs. Pesquisa Veterinária Brasileira, Brasília, DF, v. 35, n. 11, p. 906-912, nov. 2015. Biblioteca(s): Embrapa Unidades Centrais. |
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10. | | BUZANSKAS, M. E.; SAVEGNAGO, R. P.; RAMOS, S. B.; NUNES, B. do N.; CARDOSO, D. F.; MUNARI, D. P.; ALENCAR, M. M. de. Análise de componentes principais do peso corporal e de características reprodutivas de fêmeas da raça Canchim. In: SIMPÓSIO BRASILEIRO DE MELHORAMENTO ANIMAL, 8., 2010, Maringá. Melhoramento animal no Brasil: uma visão crítica - anais. Maringa: SBMA, 2010 1 CD-ROM Biblioteca(s): Embrapa Pecuária Sudeste. |
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11. | | SAVEGNAGO, R. P.; CRUZ, V. A. R.; RAMOS, S. B.; CAETANO, S. L.; SCHMIDT, G. S.; LEDUR, M. C.; EL FARO, L.; MUNARI, D. P. Egg production curve fitting using nonlinear models for selected and nonselected lines of White Leghorn hens. Poultry Science, v. 91, p. 2977-2987, 2012. Projeto: 01.06.01.006. Biblioteca(s): Embrapa Suínos e Aves. |
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12. | | SAVEGNAGO, R. P.; CAETANO, S. L.; RAMOS, S. B.; NASCIMENTO, G. B.; SCHMIDT, G. S.; LEDUR, M. C.; MUNARI, D. P. Estimates of genetic parameters, and cluster and principal components analyses of breeding values related to egg production traits in a White Leghorn population. Poultry Science, v. 90, n. 10, p. 2174-2188, 2011. Projeto: 01.06.01.006. Biblioteca(s): Embrapa Suínos e Aves. |
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13. | | SAVEGNAGO, R. P.; PAULA, D. M. de; NUNES, B. do N.; RAMOS, S. B.; LEDUR, M. C.; NONES, K.; MUNARI, D. P. Estimativas de parâmetros genéticos e fenotípicos de características reprodutivas em cruzamentos recíprocos de aves de corte e postura. In: SIMPÓSIO BRASILEIRO DE RECURSOS GENÉTICOS, 2., 2008, Brasilia, DF. Anais... Funcredi/Embrapa Recursos Genéticos e Biotecnologia, p.489, 2008. Projeto/Plano de Ação: 01.02.102.10-10 Biblioteca(s): Embrapa Suínos e Aves. |
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14. | | VIANA, R. da S.; LISBOA, L. A. M.; FIGUEIREDO, P. A. M.; RAMOS, S. B.; FERRARI, S.; MAY, A.; PRADO, E. P.; MIASAKI, C. T.; FERREIRA, I. S.; BRENHA, J. A. M. Productivity and biochemical characteristics of sugarcane when submitted to the action of chemical ripeners. Australian Journal of Basic and Applied Sciences, v. 13, n. 2, p. 64-71, 2019. Biblioteca(s): Embrapa Meio Ambiente. |
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15. | | MOREIRA, B. R. de A.; VIANA, R. da S.; FIGUEIREDA, P. A. M. de; LISBOA, L. A. M.; MIASAKI, C. T.; MAGALHÃES, A. C.; RAMOS, S. B.; VIANA, C. R. de A.; TRINDADE, V. D. R.; MAY, A. Glyphosate plus carboxylic compounds boost activity of free radical-scavenging enzymes in sugarcane. Agriculture, v. 10, n. 4, article 106, 2020. p. 1-12. Biblioteca(s): Embrapa Meio Ambiente. |
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16. | | VENTURINI, G. C.; GROSSI, D. do A.; RAMOS, S. B.; CRUZ, A. A. R. da; SOUZA, C. G.; LEDUR, M. C.; EL FARO, L.; SCHMIDT, G. S.; MUNARI, D. P. Estimation of genetic parameters for partial egg production periods by means of random regression models. Genetics and Molecular Research, v. 11, n. 3, p. 1819-1829, 2012. Projeto: 01.06.01.006. Biblioteca(s): Embrapa Suínos e Aves. |
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17. | | MOREIRA, B. R. de A.; VIANA, R. da S.; LISBOA, L. A. M.; LOPES, P. R. M.; FIGUEIREDO, P. A. M. de; RAMOS, S. B.; BONINI, C. S. B.; TRINDADE, V. D. R.; ANDRADE, M. G. de O.; MAY, A. Classifying hybrids of energy cane for production of bioethanol and cogeneration of biomass-based electricity by principal component analysis-linked fuzzy c-means clustering algorithm. Journal of Agricultural Science, Richmond Hill, v. 11, n. 14, p. 246-253, 2019. Biblioteca(s): Embrapa Meio Ambiente. |
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18. | | MOREIRA, B. R. de A.; VIANA, R. da S.; LISBOA, L. A. M.; LOPES, P. R. M.; FIGUEIREDO, P. A. M.; RAMOS, S. B.; BONINI, C. S. B.; TRINDADE, V. D. R.; ANDRADE, M. G. de O.; MAY, A. Jasmonic acid and K-phosphite enhance productivity and technological quality of sugarcane crop. Journal of Agricultural Science, v. 11, n. 14, p. 254-264, 2019. Biblioteca(s): Embrapa Meio Ambiente. |
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19. | | FREITAS, L. A. de; SAVEGNAGO, R. P.; GRUPIONI, N. V.; RAMOS, S. B.; STAFUZZA, N. B.; FIGUEIREDO, E. A. P. de; SCHMIDT, G. S.; LEDUR, M. C.; MUNARI, D. P. Reduced-rank estimation of genetic parameters for egg production traits and cluster analyses with predicted breeding values. Acta Agriculturae Scandinavica, Section A ? Animal Science, v. 68, n. 2, p. 81-86, 2019 Biblioteca(s): Embrapa Suínos e Aves. |
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20. | | MOREIRA, B. R. de A.; VIANA, R. S.; FIGUEIREDO, P. A. M. de; RAMOS, S. B.; TEIXEIRA FILHO, M. C. M.; MAY, A.; CRUZ, V. H.; LOPES, P. R. M. Qualidade tecnológica do sorgo sob manejo de maturadores químicos. Ponta Grossa, PR: Atena, 2021. 119 p. Biblioteca(s): Embrapa Meio Ambiente. |
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Registros recuperados : 24 | |
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Registro Completo
Biblioteca(s): |
Embrapa Meio Ambiente. |
Data corrente: |
03/12/2019 |
Data da última atualização: |
05/12/2019 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
B - 1 |
Autoria: |
MOREIRA, B. R. de A.; VIANA, R. da S.; LISBOA, L. A. M.; LOPES, P. R. M.; FIGUEIREDO, P. A. M. de; RAMOS, S. B.; BONINI, C. S. B.; TRINDADE, V. D. R.; ANDRADE, M. G. de O.; MAY, A. |
Afiliação: |
BRUNO RAFAEL DE ALMEIRA MOREIRA, FEIS-UNESP; RONALDO DA SILVA VIANA, FCAT-UNESP; LUCAS APARECIDO MANZANI LISBOA, FCAT-UNESP; PAULO RENATO MATOS LOPES, FCAT-UNESP; PAULO ALEXANDRE MONTEIRO DE FIGUEIREDO, FCAT-UNESP; SÉRGIO BISPO RAMOS, FCAT-UNESP; CAROLINA DOS SANTOS BATISTA BONINI, FCAT-UNESP; V D R TRINDADE, UNESP; M G O ANDRADE, FEIS-UNESP; ANDRE MAY, CNPMA. |
Título: |
Classifying hybrids of energy cane for production of bioethanol and cogeneration of biomass-based electricity by principal component analysis-linked fuzzy c-means clustering algorithm. |
Ano de publicação: |
2019 |
Fonte/Imprenta: |
Journal of Agricultural Science, Richmond Hill, v. 11, n. 14, p. 246-253, 2019. |
ISSN: |
1916-9760 |
Idioma: |
Inglês |
Conteúdo: |
Abstract: The biggest challenge facing in sugar-energy plants is to move towards the biorefinery concept, without threatening the environment and health. Energy cane is the state-of-the-art of smart energy crops to provide suitable whole-raw material to produce upgraded biofuels, dehydrated alcohol for transportation, refined sugar, yeast- fermented alcoholic beverages, soft drinks, silage and high quality fodder, as well as to cogenerate heat and bioelectricity from burnt lignocellulose. We, accordingly, present fuzzy c-means (FCM) clustering algorithm interconnected with principal component analysis (PCA) as powerful exploratory data analysis tool to wisely classify hybrids of energy cane for production of first-generation ethanol and cogeneration of heat and bioelectricity. From the orthogonally-rotated factorial map, fuzzy cluster I aggregated the hybrids VX12-0277, VX12-1191, VX12-1356 and VX12-1658 composed of higher contents of soluble solids and sucrose, and larger productive yields of fermentable sugars. These parameters correlated with the X-axis component referring to technological quality of cane juice. Fuzzy cluster III aggregated the hybrids VX12-0180 and VX12-1022 consisted of higher fiber content. This parameter correlated with the Y-axis component referring to physicochemical quality of lignocellulose. From the PCA-FCM methodology, the conclusion is, therefore, hybrids from fuzzy cluster I prove to be type I energy cane (higher sucrose to fiber ratio) and could serve as energy supply pathways to produce bioethanol, while the hybrids from fuzzy cluster III are type II energy cane (lower sucrose to fiber ratio), denoting potential as higher fiber yield biomass sources to feed cogeneration of heat and bioelectricity in high temperature and pressure furnace-boiler system. MenosAbstract: The biggest challenge facing in sugar-energy plants is to move towards the biorefinery concept, without threatening the environment and health. Energy cane is the state-of-the-art of smart energy crops to provide suitable whole-raw material to produce upgraded biofuels, dehydrated alcohol for transportation, refined sugar, yeast- fermented alcoholic beverages, soft drinks, silage and high quality fodder, as well as to cogenerate heat and bioelectricity from burnt lignocellulose. We, accordingly, present fuzzy c-means (FCM) clustering algorithm interconnected with principal component analysis (PCA) as powerful exploratory data analysis tool to wisely classify hybrids of energy cane for production of first-generation ethanol and cogeneration of heat and bioelectricity. From the orthogonally-rotated factorial map, fuzzy cluster I aggregated the hybrids VX12-0277, VX12-1191, VX12-1356 and VX12-1658 composed of higher contents of soluble solids and sucrose, and larger productive yields of fermentable sugars. These parameters correlated with the X-axis component referring to technological quality of cane juice. Fuzzy cluster III aggregated the hybrids VX12-0180 and VX12-1022 consisted of higher fiber content. This parameter correlated with the Y-axis component referring to physicochemical quality of lignocellulose. From the PCA-FCM methodology, the conclusion is, therefore, hybrids from fuzzy cluster I prove to be type I energy cane (higher sucrose to fiber ratio) and co... Mostrar Tudo |
Palavras-Chave: |
Alternative clean energy sources; Exploratory data analysis; FCM algorithm; Fiber-rich biomass; PCA. |
Thesagro: |
Análise de Dados; Bioenergia; Biomassa; Cana de Açúcar; Etanol; Hibrido. |
Thesaurus NAL: |
Bioenergy; Biomass; Data analysis; Ethanol; Fuzzy logic; Hybrids; Sugarcane. |
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/206044/1/May-Classifying-Hybrids-2019.pdf
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Marc: |
LEADER 03177naa a2200457 a 4500 001 2115795 005 2019-12-05 008 2019 bl uuuu u00u1 u #d 022 $a1916-9760 100 1 $aMOREIRA, B. R. de A. 245 $aClassifying hybrids of energy cane for production of bioethanol and cogeneration of biomass-based electricity by principal component analysis-linked fuzzy c-means clustering algorithm.$h[electronic resource] 260 $c2019 520 $aAbstract: The biggest challenge facing in sugar-energy plants is to move towards the biorefinery concept, without threatening the environment and health. Energy cane is the state-of-the-art of smart energy crops to provide suitable whole-raw material to produce upgraded biofuels, dehydrated alcohol for transportation, refined sugar, yeast- fermented alcoholic beverages, soft drinks, silage and high quality fodder, as well as to cogenerate heat and bioelectricity from burnt lignocellulose. We, accordingly, present fuzzy c-means (FCM) clustering algorithm interconnected with principal component analysis (PCA) as powerful exploratory data analysis tool to wisely classify hybrids of energy cane for production of first-generation ethanol and cogeneration of heat and bioelectricity. From the orthogonally-rotated factorial map, fuzzy cluster I aggregated the hybrids VX12-0277, VX12-1191, VX12-1356 and VX12-1658 composed of higher contents of soluble solids and sucrose, and larger productive yields of fermentable sugars. These parameters correlated with the X-axis component referring to technological quality of cane juice. Fuzzy cluster III aggregated the hybrids VX12-0180 and VX12-1022 consisted of higher fiber content. This parameter correlated with the Y-axis component referring to physicochemical quality of lignocellulose. From the PCA-FCM methodology, the conclusion is, therefore, hybrids from fuzzy cluster I prove to be type I energy cane (higher sucrose to fiber ratio) and could serve as energy supply pathways to produce bioethanol, while the hybrids from fuzzy cluster III are type II energy cane (lower sucrose to fiber ratio), denoting potential as higher fiber yield biomass sources to feed cogeneration of heat and bioelectricity in high temperature and pressure furnace-boiler system. 650 $aBioenergy 650 $aBiomass 650 $aData analysis 650 $aEthanol 650 $aFuzzy logic 650 $aHybrids 650 $aSugarcane 650 $aAnálise de Dados 650 $aBioenergia 650 $aBiomassa 650 $aCana de Açúcar 650 $aEtanol 650 $aHibrido 653 $aAlternative clean energy sources 653 $aExploratory data analysis 653 $aFCM algorithm 653 $aFiber-rich biomass 653 $aPCA 700 1 $aVIANA, R. da S. 700 1 $aLISBOA, L. A. M. 700 1 $aLOPES, P. R. M. 700 1 $aFIGUEIREDO, P. A. M. de 700 1 $aRAMOS, S. B. 700 1 $aBONINI, C. S. B. 700 1 $aTRINDADE, V. D. R. 700 1 $aANDRADE, M. G. de O. 700 1 $aMAY, A. 773 $tJournal of Agricultural Science, Richmond Hill$gv. 11, n. 14, p. 246-253, 2019.
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