Expertise-based decision support for managing food quality in agri-food companies

Patrice Buche 1 Bernard Cuq 1 Jerome Fortin 1 Clément Sipieter 2, 3
3 GRAPHIK - Graphs for Inferences on Knowledge
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : In many agri-food companies, food quality is often managed using expertise gained through experience. Overall quality enhancement may come from sharing collective expertise. In this paper, we describe the design and implementation of a complete methodology allowing an expert knowledge base to be created and used to recommend the technical action to take to maintain food quality. We present its functional specifications, defined in cooperation with several industrial partners and technical centres over the course of several projects carried out in recent years. We propose a systematic methodology for collecting the knowledge on a given food process, from the design of a questionnaire to the synthesis of the information from completed questionnaires using a mind map approach. We then propose an original core ontology for structuring knowledge as possible causal relationships between situations of interest. We describe how mind map files generated by mind map tools are automatically imported into a conceptual graph knowledge base, before being validated and finally automatically processed in a graph-based visual tool. A specific end-user interface has been designed to ensure that end-user experts in agri-food companies can use the tool in a convenient way. Finally, our approach is compared with current research.
Complete list of metadatas

https://hal-lirmm.ccsd.cnrs.fr/lirmm-02162114
Contributor : Clément Sipieter <>
Submitted on : Friday, June 21, 2019 - 2:09:02 PM
Last modification on : Thursday, November 7, 2019 - 5:30:48 PM

Identifiers

Collections

Citation

Patrice Buche, Bernard Cuq, Jerome Fortin, Clément Sipieter. Expertise-based decision support for managing food quality in agri-food companies. Computers and Electronics in Agriculture, Elsevier, 2019, 163, pp.104843. ⟨10.1016/j.compag.2019.05.052⟩. ⟨lirmm-02162114⟩

Share

Metrics

Record views

72