Artificial Intelligence and Mathematical Modelling of the Drying Kinetics of Pre-treated Whole Apricots

This study involved monitoring and modelling the drying kinetics of whole apricots pre-treated with solutions of sucrose, NaCl, and sodium bisulphite. The drying was performed in a microwave oven at different power levels (200, 400, and 800 W). Two artificial intelligence models were used for the pr...

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Autores principales:	Abla Bousselma, Dalila Abdessemed, Hichem Tahraoui, Abdeltif Amrane
Formato:	article
Lenguaje:	EN HR
Publicado:	Croatian Society of Chemical Engineers 2021
Materias:	apricot drying kinetics microwave models ann anfis Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/2099ea26d62545b5879c1abd89a7a6a2
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spelling	oai:doaj.org-article:2099ea26d62545b5879c1abd89a7a6a22021-11-03T23:22:17ZArtificial Intelligence and Mathematical Modelling of the Drying Kinetics of Pre-treated Whole Apricots10.15255/KUI.2020.0790022-98301334-9090https://doaj.org/article/2099ea26d62545b5879c1abd89a7a6a22021-11-01T00:00:00Zhttp://silverstripe.fkit.hr/kui/assets/Uploads/3-651-667-KUI-11-12-2021.pdfhttps://doaj.org/toc/0022-9830https://doaj.org/toc/1334-9090This study involved monitoring and modelling the drying kinetics of whole apricots pre-treated with solutions of sucrose, NaCl, and sodium bisulphite. The drying was performed in a microwave oven at different power levels (200, 400, and 800 W). Two artificial intelligence models were used for the prediction of drying time (DT) and moisture ratio (MR): artificial neural network (ANN) and an adaptive neuro-fuzzy inference system (ANFIS). On the other hand, the MR prediction was also done with 21 semi-empirical models, one of which we created. The results showed that the drying time decreased with the increase in microwave oven power for the three treatments. The treatment with NaCl was the most suitable for our work. The correlation coefficients of drying time (0.9992) and moisture ratio (0.9997) of ANN were high compared to the ANFIS model, which were 0.9941 and 0.9995, respectively. Among twenty semi-empirical models that were simulated, three models were fitted to our study (Henderson & Papis modified, Henderson & Pabis, and Two Terms). By comparing the three models adapted to our work and the model that we proposed, as well as ANN for MR prediction, it was observed that the model that we created was the most appropriate for describing the drying kinetics of NaCl-treated apricot. This solution opens the prospect of using this potential model to simulate fruit and vegetable drying kinetics in the future.Abla BousselmaDalila AbdessemedHichem TahraouiAbdeltif AmraneCroatian Society of Chemical Engineersarticleapricotdrying kineticsmicrowavemodelsannanfisChemistryQD1-999ENHRKemija u Industriji, Vol 70, Iss 11-12, Pp 651-667 (2021)
institution	DOAJ
collection	DOAJ
language	EN HR
topic	apricot drying kinetics microwave models ann anfis Chemistry QD1-999
spellingShingle	apricot drying kinetics microwave models ann anfis Chemistry QD1-999 Abla Bousselma Dalila Abdessemed Hichem Tahraoui Abdeltif Amrane Artificial Intelligence and Mathematical Modelling of the Drying Kinetics of Pre-treated Whole Apricots
description	This study involved monitoring and modelling the drying kinetics of whole apricots pre-treated with solutions of sucrose, NaCl, and sodium bisulphite. The drying was performed in a microwave oven at different power levels (200, 400, and 800 W). Two artificial intelligence models were used for the prediction of drying time (DT) and moisture ratio (MR): artificial neural network (ANN) and an adaptive neuro-fuzzy inference system (ANFIS). On the other hand, the MR prediction was also done with 21 semi-empirical models, one of which we created. The results showed that the drying time decreased with the increase in microwave oven power for the three treatments. The treatment with NaCl was the most suitable for our work. The correlation coefficients of drying time (0.9992) and moisture ratio (0.9997) of ANN were high compared to the ANFIS model, which were 0.9941 and 0.9995, respectively. Among twenty semi-empirical models that were simulated, three models were fitted to our study (Henderson & Papis modified, Henderson & Pabis, and Two Terms). By comparing the three models adapted to our work and the model that we proposed, as well as ANN for MR prediction, it was observed that the model that we created was the most appropriate for describing the drying kinetics of NaCl-treated apricot. This solution opens the prospect of using this potential model to simulate fruit and vegetable drying kinetics in the future.
format	article
author	Abla Bousselma Dalila Abdessemed Hichem Tahraoui Abdeltif Amrane
author_facet	Abla Bousselma Dalila Abdessemed Hichem Tahraoui Abdeltif Amrane
author_sort	Abla Bousselma
title	Artificial Intelligence and Mathematical Modelling of the Drying Kinetics of Pre-treated Whole Apricots
title_short	Artificial Intelligence and Mathematical Modelling of the Drying Kinetics of Pre-treated Whole Apricots
title_full	Artificial Intelligence and Mathematical Modelling of the Drying Kinetics of Pre-treated Whole Apricots
title_fullStr	Artificial Intelligence and Mathematical Modelling of the Drying Kinetics of Pre-treated Whole Apricots
title_full_unstemmed	Artificial Intelligence and Mathematical Modelling of the Drying Kinetics of Pre-treated Whole Apricots
title_sort	artificial intelligence and mathematical modelling of the drying kinetics of pre-treated whole apricots
publisher	Croatian Society of Chemical Engineers
publishDate	2021
url	https://doaj.org/article/2099ea26d62545b5879c1abd89a7a6a2
work_keys_str_mv	AT ablabousselma artificialintelligenceandmathematicalmodellingofthedryingkineticsofpretreatedwholeapricots AT dalilaabdessemed artificialintelligenceandmathematicalmodellingofthedryingkineticsofpretreatedwholeapricots AT hichemtahraoui artificialintelligenceandmathematicalmodellingofthedryingkineticsofpretreatedwholeapricots AT abdeltifamrane artificialintelligenceandmathematicalmodellingofthedryingkineticsofpretreatedwholeapricots
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Artificial Intelligence and Mathematical Modelling of the Drying Kinetics of Pre-treated Whole Apricots

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