A digital learning tool based on models and simulators for food engineering (MESTRAL). (March 2021)

• Record Type: Journal Article
• Authors: Suciu, I.; Ndiaye, A.; Baudrit, C.; Fernandez, C.; Kondjoyan, A.; Mirade, P.S.; Sicard, J.; Tournayre, P.; Bohuon, P.; Buche, P.; Courtois, F.; Guillard, V.; Athes, V.; Flick, D.; Plana-Fattori, A.; Trelea, C.; Trystram, G.; Delaplace, G.; Curet, S.; Della Valle, D.; Pottier, L.; Chiron, H.; Guessasma, S.; Kansou, K.; Kristiawan, M.; Della Valle, G.
• Is Part Of: Journal of food engineering. Volume 293(2021)
• Publication Date: 2021-03
• Subjects: Abacus -- Concept map -- Electronic knowledge book -- Food processing -- Student; Food industry and trade -- Periodicals; Food -- Analysis -- Periodicals; Aliments -- Industrie et commerce -- Périodiques; Aliments -- Analyse -- Périodiques; Aliments -- Recherche -- Périodiques; 664.005
• DOI: 10.1016/j.jfoodeng.2020.110375
• Languages: English
• ISSNs: 0260-8774

Abstract

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. Highlights: A digital learning tool, Mestral, was built to train people in food processes. Knowledge is presented in an electronic book with concept maps. Mestral covers 15 real (food and process) systems and is based on published models. Each module contains a simulator which represents graphically the model results. Mestral has been tested satisfactorily and opens up prospects for blended learning.