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A digital learning tool based on models and simulators for food engineering (MESTRAL)

Ioana Suciu 1 Amadou Ndiaye 2 Cédric Baudrit 2 Christophe Fernandez 2 Alain Kondjoyan 3 Pierre-Sylvain Mirade 3 Jason Sicard 3 Pascal Tournayre 3 Philippe Bohuon 4 Patrice Buche 5 Francis Courtois 4 Valérie Guillard 5 V. Athes 6 Denis Flick 6 A. Plana-Fattori 6 C. Tréléa 6 Gilles Trystram 6 G. Delaplace 7 S. Curet 8 Dominique Della Valle 9 Laurence Pottier 8 Hubert Chiron 1 Sofiane Guessasma 1 Kamal Kansou 1 Magdalena Kristiawan 1 Guy Della Valle 1, *
* Corresponding author
1 BIA - Unité de recherche sur les Biopolymères, Interactions Assemblages
2 I2M - Institut de Mécanique et d'Ingénierie
3 QuaPA - Qualité des Produits Animaux
4 UMR Qualisud - Démarche intégrée pour l'obtention d'aliments de qualité
5 UMR IATE - Ingénierie des Agro-polymères et Technologies Émergentes
6 SayFood - Paris-Saclay Food and Bioproduct Engineering
7 UMET - Unité Matériaux et Transformations - UMR 8207
8 GEPEA - Laboratoire de génie des procédés - environnement - agroalimentaire
9 ONIRIS - Ecole Nationale Vétérinaire, Agroalimentaire et de l'alimentation Nantes-Atlantique
Abstract : This paper presents a digital learning tool, MESTRAL (“Modélisation Et Simulation des TRansformations ALimentaires”, “Modelling and Simulating Food Processing” in English), that can provide educators with a tool to teach food processing using simulators and a broad range of models derived from research in food science & engineering. It was built using electronic knowledge books (eK-book). The eK-book represents knowledge in the form of concept maps and knowledge sheets, connected via a network of hypertext links. MESTRAL encompasses 15 modules, that cover approximately 150 h of teaching and a broad range of real systems, from a single unit operation (e.g., frying a banana) to a logistic chain (e.g., ham cold chain). Each module conveys information on a food product or a food process, and includes a simulator based on a published scientific model. Altogether, the models address various scale of systems and are based on different theoretical frameworks. For each simulator, the model inputs and outputs are stored in a database. Outputs are visualized through abacuses, which can be used for virtual practice. MESTRAL modules also include training exercises and tests to help students to assess the knowledge they have acquired during consultation of the modules. Finally, MESTRAL has already been successfully tested by different audiences according to various learning forms.
Keywords : Abacus Concept map Electronic knowledge book Food processing Student abacus concept map electronic knowledge book food processing student
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Journal articles
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https://hal.inrae.fr/hal-02980650
Contributor : Dominique Fournier <>
Submitted on : Wednesday, December 16, 2020 - 1:35:45 PM
Last modification on : Wednesday, April 14, 2021 - 3:37:27 AM
Long-term archiving on: : Wednesday, March 17, 2021 - 7:15:38 PM

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INRAE | AGROPARISTECH | INC-CNRS | CIRAD | AGROPOLIS | AFRIQ | UNIV-AVIGNON | UNIV-NANTES | UNIV-MONTPELLIER | UNIV-LILLE | IATE | TDS-MACS | UNAM | INSTITUT-TELECOM | ARTS-ET-METIERS-SCIENCES-ET-TECHNOLOGIES | BA | MONTPELLIER-SUPAGRO | CNRS | I2M-BX | GEPEA | GS-ENGINEERING

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Ioana Suciu, Amadou Ndiaye, Cédric Baudrit, Christophe Fernandez, Alain Kondjoyan, et al.. A digital learning tool based on models and simulators for food engineering (MESTRAL). Journal of Food Engineering, Elsevier, 2021, 293, pp.110375. ⟨10.1016/j.jfoodeng.2020.110375⟩. ⟨hal-02980650⟩

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