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Food modelling strategies and approaches for knowledge transfer

Authors :
Kamal Kansou
Wim Laurier
Maria N. Charalambides
Guy Della-Valle
Ilija Djekic
Aberham Hailu Feyissa
Francesco Marra
Rallou Thomopoulos
Bert Bredeweg
Faculteit Onderwijs en Opvoeding
Source :
Trends in Food Science & Technology, 120, 363-373. Elsevier, Kansou, K, Laurier, W, Charalambides, M N, Della-Valle, G, Djekic, I, Feyissa, A H, Marra, F, Thomopoulos, R & Bredeweg, B 2022, ' Food modelling strategies and approaches for knowledge transfer ', Trends in Food Science and Technology, vol. 120, pp. 363-373 . https://doi.org/10.1016/j.tifs.2022.01.021
Publication Year :
2022
Publisher :
Elsevier BV, 2022.

Abstract

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.

Details

ISSN :
09242244
Volume :
120
Database :
OpenAIRE
Journal :
Trends in Food Science & Technology
Accession number :
edsair.doi.dedup.....ceab714fa6362735549f0ffbe0248cf3
Full Text :
https://doi.org/10.1016/j.tifs.2022.01.021