Publication
Quality Index Method for fish quality control: Understanding the applications, the appointed limits and the upcoming trends
dc.contributor.author | Freitas, Jorge | |
dc.contributor.author | Vaz-Pires, Paulo | |
dc.contributor.author | Câmara, José S. | |
dc.date.accessioned | 2023-06-12T11:10:21Z | |
dc.date.available | 2023-06-12T11:10:21Z | |
dc.date.issued | 2021 | |
dc.description.abstract | Background: The Quality Index Method (QIM) is a widely used approach for fish sensory grading, based on a structured scaling for freshness measurements, providing information concerning the fish freshness status, as a prediction of the remaining shelf-life for specific species or products. However, its tendency to be used in an oversimplified way and other common misapplications could lead to discredit of a methodology with great potential. Scope and approach: Review the principles of QIM methodology, discussing its concept, applications, and un derstand their limits, as a useful strategy to propose improvements, reinforce its predictive power and consequent acceptability. Key findings and conclusions: QIM methodology is based on a compromise between the number of fish samples necessary and the number of attributes, with sensory relevance in fish spoilage, that allows verifying if quality requirements are fulfilled. However, the assumptions inherent to the method, undermine the reliability of the shelf-life predictions. Determination of the variability associated with assessors, product, and correct structure of datasets for statistical analysis, will improve the predictive power of the method. However, it could lead to an increase in the method complexity that would drive it away from the industry’s needs for fast and easily implemented methods. | pt_PT |
dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
dc.identifier.citation | Freitas, J., Vaz-Pires, P., & Câmara, J. S. (2021). Quality Index Method for fish quality control: Understanding the applications, the appointed limits and the upcoming trends. Trends in Food Science & Technology, 111, 333-345. | pt_PT |
dc.identifier.doi | 10.1016/j.tifs.2021.03.011 | pt_PT |
dc.identifier.uri | http://hdl.handle.net/10400.13/5221 | |
dc.language.iso | eng | pt_PT |
dc.peerreviewed | yes | pt_PT |
dc.publisher | Elsevier | pt_PT |
dc.relation | Madeira Chemistry Research Centre | |
dc.relation | Madeira Chemistry Research Centre | |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
dc.subject | Seafood | pt_PT |
dc.subject | Fish sensory analysis | pt_PT |
dc.subject | QIM concept | pt_PT |
dc.subject | Freshness attributes | pt_PT |
dc.subject | . | pt_PT |
dc.subject | Faculdade de Ciências Exatas e da Engenharia | pt_PT |
dc.subject | Centro de Química da Madeira | |
dc.title | Quality Index Method for fish quality control: Understanding the applications, the appointed limits and the upcoming trends | pt_PT |
dc.type | journal article | |
dspace.entity.type | Publication | |
oaire.awardTitle | Madeira Chemistry Research Centre | |
oaire.awardTitle | Madeira Chemistry Research Centre | |
oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00674%2F2020/PT | |
oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F00674%2F2020/PT | |
oaire.citation.endPage | 345 | pt_PT |
oaire.citation.startPage | 333 | pt_PT |
oaire.citation.title | Trends in Food Science & Technology | pt_PT |
oaire.citation.volume | 111 | pt_PT |
oaire.fundingStream | 6817 - DCRRNI ID | |
oaire.fundingStream | 6817 - DCRRNI ID | |
person.familyName | Freitas | |
person.familyName | Vaz-Pires | |
person.familyName | Câmara | |
person.givenName | Jorge | |
person.givenName | Paulo | |
person.givenName | José | |
person.identifier | 347510 | |
person.identifier | G-3003-2013 | |
person.identifier.ciencia-id | E413-C848-1D51 | |
person.identifier.ciencia-id | 2814-F324-2A15 | |
person.identifier.ciencia-id | 481C-08CE-90E5 | |
person.identifier.orcid | 0000-0003-4350-0526 | |
person.identifier.orcid | 0000-0002-9485-7528 | |
person.identifier.orcid | 0000-0003-1965-3151 | |
person.identifier.rid | B-5416-2019 | |
person.identifier.scopus-author-id | 35231724400 | |
person.identifier.scopus-author-id | 10140393000 | |
project.funder.identifier | http://doi.org/10.13039/501100001871 | |
project.funder.identifier | http://doi.org/10.13039/501100001871 | |
project.funder.name | Fundação para a Ciência e a Tecnologia | |
project.funder.name | Fundação para a Ciência e a Tecnologia | |
rcaap.rights | openAccess | pt_PT |
rcaap.type | article | pt_PT |
relation.isAuthorOfPublication | 2872276a-24f1-4e02-ba38-27445de6871a | |
relation.isAuthorOfPublication | 158b1546-4e83-410c-8e0d-f82861766b0e | |
relation.isAuthorOfPublication | e10d78be-e547-4d25-92b5-06a997ed78da | |
relation.isAuthorOfPublication.latestForDiscovery | 158b1546-4e83-410c-8e0d-f82861766b0e | |
relation.isProjectOfPublication | e30e13d9-be9a-4f34-91ea-a1682abce74e | |
relation.isProjectOfPublication | e64ad36a-83b5-467c-bbb3-449ffc0662f2 | |
relation.isProjectOfPublication.latestForDiscovery | e64ad36a-83b5-467c-bbb3-449ffc0662f2 |