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.

Detalhes bibliográficos
Autor(a) principal: MOREIRA, B. R. de A.
Data de Publicação: 2019
Outros Autores: 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.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1115795
Resumo: 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.
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spelling 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.Alternative clean energy sourcesExploratory data analysisFCM algorithmFiber-rich biomassPCAHibridoEtanolCana de AçúcarAnálise de DadosBiomassaBioenergiaFuzzy logicSugarcaneHybridsBiomassBioenergyEthanolData analysisAbstract: 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.BRUNO RAFAEL DE ALMEIRA MOREIRA, FEIS-UNESPRONALDO DA SILVA VIANA, FCAT-UNESPLUCAS APARECIDO MANZANI LISBOA, FCAT-UNESPPAULO RENATO MATOS LOPES, FCAT-UNESPPAULO ALEXANDRE MONTEIRO DE FIGUEIREDO, FCAT-UNESPSÉRGIO BISPO RAMOS, FCAT-UNESPCAROLINA DOS SANTOS BATISTA BONINI, FCAT-UNESPV D R TRINDADE, UNESPM G O ANDRADE, FEIS-UNESPANDRE MAY, CNPMA.MOREIRA, B. R. de A.VIANA, R. da S.LISBOA, L. A. M.LOPES, P. R. M.FIGUEIREDO, P. A. M. deRAMOS, S. B.BONINI, C. S. B.TRINDADE, V. D. R.ANDRADE, M. G. de O.MAY, A.2019-12-03T18:17:30Z2019-12-03T18:17:30Z2019-12-0320192019-12-05T11:11:11Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleJournal of Agricultural Science, Richmond Hill, v. 11, n. 14, p. 246-253, 2019.1916-9760http://www.alice.cnptia.embrapa.br/alice/handle/doc/1115795enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2019-12-03T18:17:36Zoai:www.alice.cnptia.embrapa.br:doc/1115795Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542019-12-03T18:17:36falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542019-12-03T18:17:36Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv 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.
title 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.
spellingShingle 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.
MOREIRA, B. R. de A.
Alternative clean energy sources
Exploratory data analysis
FCM algorithm
Fiber-rich biomass
PCA
Hibrido
Etanol
Cana de Açúcar
Análise de Dados
Biomassa
Bioenergia
Fuzzy logic
Sugarcane
Hybrids
Biomass
Bioenergy
Ethanol
Data analysis
title_short 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.
title_full 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.
title_fullStr 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.
title_full_unstemmed 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.
title_sort 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.
author MOREIRA, B. R. de A.
author_facet 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.
author_role author
author2 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.
author2_role author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv 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.
dc.contributor.author.fl_str_mv 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.
dc.subject.por.fl_str_mv Alternative clean energy sources
Exploratory data analysis
FCM algorithm
Fiber-rich biomass
PCA
Hibrido
Etanol
Cana de Açúcar
Análise de Dados
Biomassa
Bioenergia
Fuzzy logic
Sugarcane
Hybrids
Biomass
Bioenergy
Ethanol
Data analysis
topic Alternative clean energy sources
Exploratory data analysis
FCM algorithm
Fiber-rich biomass
PCA
Hibrido
Etanol
Cana de Açúcar
Análise de Dados
Biomassa
Bioenergia
Fuzzy logic
Sugarcane
Hybrids
Biomass
Bioenergy
Ethanol
Data analysis
description 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.
publishDate 2019
dc.date.none.fl_str_mv 2019-12-03T18:17:30Z
2019-12-03T18:17:30Z
2019-12-03
2019
2019-12-05T11:11:11Z
dc.type.driver.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv Journal of Agricultural Science, Richmond Hill, v. 11, n. 14, p. 246-253, 2019.
1916-9760
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1115795
identifier_str_mv Journal of Agricultural Science, Richmond Hill, v. 11, n. 14, p. 246-253, 2019.
1916-9760
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1115795
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
instname_str Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron_str EMBRAPA
institution EMBRAPA
reponame_str Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
collection Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
repository.name.fl_str_mv Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
repository.mail.fl_str_mv cg-riaa@embrapa.br
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