Convective drying of regular mint leaves: analysis based on fitting empirical correlations, response surface methodology and neural networks
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Acta scientiarum. Technology (Online) |
Texto Completo: | http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/19238 |
Resumo: | In the present work, an analysis of drying of peppermint (Menta x villosa H.) leaves has been made using empirical correlations, response surface models and a neural network model. The main goal was to apply different modeling approaches to predict moisture content and drying rates in the drying of leaves, and obtaining an overview on the subject. Experiments were carried out in a convective horizontal flow dryer in which samples were placed parallel to the air stream under operating conditions of air temperatures from 36 to 64°C, air velocities from 1.0 to 2.0 m s-1 and sample loads from 18 to 42 g, corresponding to sample heights of 1.4, 1.7 and 3.5 cm respectively. A complete 33 experimental design was used. Results have shown that the three methodologies employed in this work were complementary in the sense that they simultaneously provided a better understanding of leaves drying. |
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Acta scientiarum. Technology (Online) |
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Convective drying of regular mint leaves: analysis based on fitting empirical correlations, response surface methodology and neural networksMentha x villosa Hkinetic parametersconvective dryingmoisture contentEngenharia QuímicaIn the present work, an analysis of drying of peppermint (Menta x villosa H.) leaves has been made using empirical correlations, response surface models and a neural network model. The main goal was to apply different modeling approaches to predict moisture content and drying rates in the drying of leaves, and obtaining an overview on the subject. Experiments were carried out in a convective horizontal flow dryer in which samples were placed parallel to the air stream under operating conditions of air temperatures from 36 to 64°C, air velocities from 1.0 to 2.0 m s-1 and sample loads from 18 to 42 g, corresponding to sample heights of 1.4, 1.7 and 3.5 cm respectively. A complete 33 experimental design was used. Results have shown that the three methodologies employed in this work were complementary in the sense that they simultaneously provided a better understanding of leaves drying. Universidade Estadual De Maringá2014-04-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/1923810.4025/actascitechnol.v36i2.19238Acta Scientiarum. Technology; Vol 36 No 2 (2014); 270-278Acta Scientiarum. Technology; v. 36 n. 2 (2014); 270-2781806-25631807-8664reponame:Acta scientiarum. Technology (Online)instname:Universidade Estadual de Maringá (UEM)instacron:UEMenghttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/19238/12654Costa, Ariany Binda SilvaFreire, Fábio BentesFerreira, Maria do CarmoFreire, José Teixeirainfo:eu-repo/semantics/openAccess2014-04-04T15:34:15Zoai:periodicos.uem.br/ojs:article/19238Revistahttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/indexPUBhttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/oai||actatech@uem.br1807-86641806-2563opendoar:2014-04-04T15:34:15Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM)false |
dc.title.none.fl_str_mv |
Convective drying of regular mint leaves: analysis based on fitting empirical correlations, response surface methodology and neural networks |
title |
Convective drying of regular mint leaves: analysis based on fitting empirical correlations, response surface methodology and neural networks |
spellingShingle |
Convective drying of regular mint leaves: analysis based on fitting empirical correlations, response surface methodology and neural networks Costa, Ariany Binda Silva Mentha x villosa H kinetic parameters convective drying moisture content Engenharia Química |
title_short |
Convective drying of regular mint leaves: analysis based on fitting empirical correlations, response surface methodology and neural networks |
title_full |
Convective drying of regular mint leaves: analysis based on fitting empirical correlations, response surface methodology and neural networks |
title_fullStr |
Convective drying of regular mint leaves: analysis based on fitting empirical correlations, response surface methodology and neural networks |
title_full_unstemmed |
Convective drying of regular mint leaves: analysis based on fitting empirical correlations, response surface methodology and neural networks |
title_sort |
Convective drying of regular mint leaves: analysis based on fitting empirical correlations, response surface methodology and neural networks |
author |
Costa, Ariany Binda Silva |
author_facet |
Costa, Ariany Binda Silva Freire, Fábio Bentes Ferreira, Maria do Carmo Freire, José Teixeira |
author_role |
author |
author2 |
Freire, Fábio Bentes Ferreira, Maria do Carmo Freire, José Teixeira |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Costa, Ariany Binda Silva Freire, Fábio Bentes Ferreira, Maria do Carmo Freire, José Teixeira |
dc.subject.por.fl_str_mv |
Mentha x villosa H kinetic parameters convective drying moisture content Engenharia Química |
topic |
Mentha x villosa H kinetic parameters convective drying moisture content Engenharia Química |
description |
In the present work, an analysis of drying of peppermint (Menta x villosa H.) leaves has been made using empirical correlations, response surface models and a neural network model. The main goal was to apply different modeling approaches to predict moisture content and drying rates in the drying of leaves, and obtaining an overview on the subject. Experiments were carried out in a convective horizontal flow dryer in which samples were placed parallel to the air stream under operating conditions of air temperatures from 36 to 64°C, air velocities from 1.0 to 2.0 m s-1 and sample loads from 18 to 42 g, corresponding to sample heights of 1.4, 1.7 and 3.5 cm respectively. A complete 33 experimental design was used. Results have shown that the three methodologies employed in this work were complementary in the sense that they simultaneously provided a better understanding of leaves drying. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-04-04 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/19238 10.4025/actascitechnol.v36i2.19238 |
url |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/19238 |
identifier_str_mv |
10.4025/actascitechnol.v36i2.19238 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/19238/12654 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Estadual De Maringá |
publisher.none.fl_str_mv |
Universidade Estadual De Maringá |
dc.source.none.fl_str_mv |
Acta Scientiarum. Technology; Vol 36 No 2 (2014); 270-278 Acta Scientiarum. Technology; v. 36 n. 2 (2014); 270-278 1806-2563 1807-8664 reponame:Acta scientiarum. Technology (Online) instname:Universidade Estadual de Maringá (UEM) instacron:UEM |
instname_str |
Universidade Estadual de Maringá (UEM) |
instacron_str |
UEM |
institution |
UEM |
reponame_str |
Acta scientiarum. Technology (Online) |
collection |
Acta scientiarum. Technology (Online) |
repository.name.fl_str_mv |
Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM) |
repository.mail.fl_str_mv |
||actatech@uem.br |
_version_ |
1799315335344553984 |