The Constrained Median: A Way to Incorporate Side Information in the Assessment of Food Samples

Marc Sader, Raúl Pérez-Fernández, Lotta Kuuliala, Frank Devlieghere and Bernard De Baets
Additional contact information
Marc Sader: KERMIT, Department of Data Analysis and Mathematical Modelling, Ghent University, 9000 Gent, Belgium
Raúl Pérez-Fernández: KERMIT, Department of Data Analysis and Mathematical Modelling, Ghent University, 9000 Gent, Belgium
Lotta Kuuliala: KERMIT, Department of Data Analysis and Mathematical Modelling, Ghent University, 9000 Gent, Belgium
Frank Devlieghere: FMFP—Research Unit Food Microbiology and Food Preservation, Department of Food Technology, Safety and Health, Ghent University, 9000 Ghent, Belgium
Bernard De Baets: KERMIT, Department of Data Analysis and Mathematical Modelling, Ghent University, 9000 Gent, Belgium

Mathematics, 2020, vol. 8, issue 3, 1-18

Abstract: A classical problem in the field of food science concerns the consensus evaluation of food samples. Typically, several panelists are asked to provide scores describing the perceived quality of the samples, and subsequently, the overall (consensus) scores are determined. Unfortunately, gathering a large number of panelists is a challenging and very expensive way of collecting information. Interestingly, side information about the samples is often available. This paper describes a method that exploits such information with the aim of improving the assessment of the quality of multiple samples. The proposed method is illustrated by discussing an experiment on raw Atlantic salmon ( Salmo salar ), where the evolution of the overall score of each salmon sample is studied. The influence of incorporating knowledge of storage days, results of a clustering analysis, and information from additionally performed sensory evaluation tests is discussed. We provide guidelines for incorporating different types of information and discuss their benefits and potential risks.

Keywords: sensory evaluation; scoring; consensus; food quality (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/8/3/406/pdf (application/pdf)
https://www.mdpi.com/2227-7390/8/3/406/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:8:y:2020:i:3:p:406-:d:331713

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().