Predictive tool of energy performance of cold storage in agrifood industries

Detalhes bibliográficos
Autor(a) principal: Nunes, José
Data de Publicação: 2014
Outros Autores: Neves, Diogo, Gaspar, Pedro Dinis, Silva, Pedro Dinho da
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.6/7272
Resumo: Food processing and conservation represent decisive factors for the sustainability of the planet given the significant growth of the world population in the last decades. Therefore, the cooling process during the manufacture and/or storage of food products has been subject of study and improvement in order to ensure the food supply with good quality and safety. A predictive tool for assessment of the energy performance in agrifood industries that use cold storage is developed in order to contribute to the improvement of the energy efficiency of this industry. The predictive tool is based on a set of characteristic correlated parameters: amount of raw material annually processed, annual energy consumption and volume of cold rooms. Case studies of application of the predictive tool consider industries in the meat sector, specifically slaughterhouses. The results obtained help on the decision-making of practice measures for improvement of the energy efficiency in this industry
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spelling Predictive tool of energy performance of cold storage in agrifood industriesThe portuguese case studyEnergy efficiencySustainabilityPerishable productsCold storagePredictive toolCold industryFood processing and conservation represent decisive factors for the sustainability of the planet given the significant growth of the world population in the last decades. Therefore, the cooling process during the manufacture and/or storage of food products has been subject of study and improvement in order to ensure the food supply with good quality and safety. A predictive tool for assessment of the energy performance in agrifood industries that use cold storage is developed in order to contribute to the improvement of the energy efficiency of this industry. The predictive tool is based on a set of characteristic correlated parameters: amount of raw material annually processed, annual energy consumption and volume of cold rooms. Case studies of application of the predictive tool consider industries in the meat sector, specifically slaughterhouses. The results obtained help on the decision-making of practice measures for improvement of the energy efficiency in this industryElsevieruBibliorumNunes, JoséNeves, DiogoGaspar, Pedro DinisSilva, Pedro Dinho da2019-10-17T16:19:14Z20142014-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.6/7272eng0196-8904metadata only accessinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-12-15T09:46:30Zoai:ubibliorum.ubi.pt:10400.6/7272Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:47:49.599468Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Predictive tool of energy performance of cold storage in agrifood industries
The portuguese case study
title Predictive tool of energy performance of cold storage in agrifood industries
spellingShingle Predictive tool of energy performance of cold storage in agrifood industries
Nunes, José
Energy efficiency
Sustainability
Perishable products
Cold storage
Predictive tool
Cold industry
title_short Predictive tool of energy performance of cold storage in agrifood industries
title_full Predictive tool of energy performance of cold storage in agrifood industries
title_fullStr Predictive tool of energy performance of cold storage in agrifood industries
title_full_unstemmed Predictive tool of energy performance of cold storage in agrifood industries
title_sort Predictive tool of energy performance of cold storage in agrifood industries
author Nunes, José
author_facet Nunes, José
Neves, Diogo
Gaspar, Pedro Dinis
Silva, Pedro Dinho da
author_role author
author2 Neves, Diogo
Gaspar, Pedro Dinis
Silva, Pedro Dinho da
author2_role author
author
author
dc.contributor.none.fl_str_mv uBibliorum
dc.contributor.author.fl_str_mv Nunes, José
Neves, Diogo
Gaspar, Pedro Dinis
Silva, Pedro Dinho da
dc.subject.por.fl_str_mv Energy efficiency
Sustainability
Perishable products
Cold storage
Predictive tool
Cold industry
topic Energy efficiency
Sustainability
Perishable products
Cold storage
Predictive tool
Cold industry
description Food processing and conservation represent decisive factors for the sustainability of the planet given the significant growth of the world population in the last decades. Therefore, the cooling process during the manufacture and/or storage of food products has been subject of study and improvement in order to ensure the food supply with good quality and safety. A predictive tool for assessment of the energy performance in agrifood industries that use cold storage is developed in order to contribute to the improvement of the energy efficiency of this industry. The predictive tool is based on a set of characteristic correlated parameters: amount of raw material annually processed, annual energy consumption and volume of cold rooms. Case studies of application of the predictive tool consider industries in the meat sector, specifically slaughterhouses. The results obtained help on the decision-making of practice measures for improvement of the energy efficiency in this industry
publishDate 2014
dc.date.none.fl_str_mv 2014
2014-01-01T00:00:00Z
2019-10-17T16:19:14Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.6/7272
url http://hdl.handle.net/10400.6/7272
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0196-8904
dc.rights.driver.fl_str_mv metadata only access
info:eu-repo/semantics/openAccess
rights_invalid_str_mv metadata only access
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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