<b>Convective drying of regular mint leaves: analysis based on fitting empirical correlations, response surface methodology and neural networks<b>

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...

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Main Authors: Ariany Binda Silva Costa, Fábio Bentes Freire, Maria do Carmo Ferreira, José Teixeira Freire
Format: Article
Language:English
Published: Universidade Estadual de Maringá 2014-04-01
Series:Acta Scientiarum: Technology
Subjects:
Online Access:http://186.233.154.254/ojs/index.php/ActaSciTechnol/article/view/19238
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spelling doaj-d4d5b8a8ecfe4d4f8c57fcfa5f04ea242020-11-25T00:47:49ZengUniversidade Estadual de MaringáActa Scientiarum: Technology1806-25631807-86642014-04-0136227027810.4025/actascitechnol.v36i2.1923810618<b>Convective drying of regular mint leaves: analysis based on fitting empirical correlations, response surface methodology and neural networks<b>Ariany Binda Silva Costa0Fábio Bentes Freire1Maria do Carmo Ferreira2José Teixeira Freire3Universidade Federal de São CarlosUniversidade Federal de São CarlosUniversidade Federal de São CarlosUniversidade Federal de São CarlosIn 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.http://186.233.154.254/ojs/index.php/ActaSciTechnol/article/view/19238Mentha x villosa Hkinetic parametersconvective dryingmoisture content
collection DOAJ
language English
format Article
sources DOAJ
author Ariany Binda Silva Costa
Fábio Bentes Freire
Maria do Carmo Ferreira
José Teixeira Freire
spellingShingle Ariany Binda Silva Costa
Fábio Bentes Freire
Maria do Carmo Ferreira
José Teixeira Freire
<b>Convective drying of regular mint leaves: analysis based on fitting empirical correlations, response surface methodology and neural networks<b>
Acta Scientiarum: Technology
Mentha x villosa H
kinetic parameters
convective drying
moisture content
author_facet Ariany Binda Silva Costa
Fábio Bentes Freire
Maria do Carmo Ferreira
José Teixeira Freire
author_sort Ariany Binda Silva Costa
title <b>Convective drying of regular mint leaves: analysis based on fitting empirical correlations, response surface methodology and neural networks<b>
title_short <b>Convective drying of regular mint leaves: analysis based on fitting empirical correlations, response surface methodology and neural networks<b>
title_full <b>Convective drying of regular mint leaves: analysis based on fitting empirical correlations, response surface methodology and neural networks<b>
title_fullStr <b>Convective drying of regular mint leaves: analysis based on fitting empirical correlations, response surface methodology and neural networks<b>
title_full_unstemmed <b>Convective drying of regular mint leaves: analysis based on fitting empirical correlations, response surface methodology and neural networks<b>
title_sort <b>convective drying of regular mint leaves: analysis based on fitting empirical correlations, response surface methodology and neural networks<b>
publisher Universidade Estadual de Maringá
series Acta Scientiarum: Technology
issn 1806-2563
1807-8664
publishDate 2014-04-01
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.
topic Mentha x villosa H
kinetic parameters
convective drying
moisture content
url http://186.233.154.254/ojs/index.php/ActaSciTechnol/article/view/19238
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