Food modelling strategies and approaches for knowledge transfer - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement Accéder directement au contenu
Article Dans Une Revue Trends in Food Science and Technology Année : 2022

Food modelling strategies and approaches for knowledge transfer

Résumé

Background : Scientific software incorporates models that capture fundamental domain knowledge. This software is becoming increasingly more relevant as an instrument for food research. However, scientific software is currently hardly shared among and (re-)used by stakeholders in the food domain, which hampers effective dissemination of knowledge, i.e. knowledge transfer.Scope and approach : This paper reviews selected approaches, best practices, hurdles and limitations regarding knowledge transfer via software and the mathematical models embedded in it to provide points of reference for the food community.Key findings and conclusions : The paper focusses on three aspects. Firstly, the publication of digital objects on the web, which offers valorisation software as a scientific asset. Secondly, building transferrable software as way to share knowledge through collaboration with experts and stakeholders. Thirdly, developing food engineers' modelling skills through the use of food models and software in education and training.
Fichier principal
Vignette du fichier
TIFS_2022_author-version.pdf (1.09 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03542205 , version 1 (13-07-2022)

Licence

Paternité - Pas d'utilisation commerciale - Pas de modification

Identifiants

Citer

Kamal Kansou, Wim Laurier, Maria Charalambides, Guy Della Valle, Ilija Djekic, et al.. Food modelling strategies and approaches for knowledge transfer. Trends in Food Science and Technology, 2022, 120, pp.363-373. ⟨10.1016/j.tifs.2022.01.021⟩. ⟨hal-03542205⟩
69 Consultations
208 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More