Computer vision system (CVS): a powerful non-destructive technique for the assessment of red mullet (Mullus barbatus) freshness

Autor: Santina Romani, Francesco Capozzi, Marco Dalla Rosa, Alessandra Ciampa, Pietro Rocculi, Silvia Tappi, Federica Balestra
Přispěvatelé: Tappi, Silvia, Rocculi, Pietro, Ciampa, Alessandra, Romani, Santina, Balestra, Federica, Capozzi, Francesco, Dalla Rosa, Marco
Rok vydání: 2017
Předmět:
Zdroj: European Food Research and Technology. 243:2225-2233
ISSN: 1438-2385
1438-2377
DOI: 10.1007/s00217-017-2924-0
Popis: The evaluation of fish freshness can be performed using chemical, sensory and physical methods. Besides sensory methods, several instrumental techniques have been applied with the objective of replacing sensory assessment. The aim of this study was to set up and test objective physical methods mainly based on computer vision system (CVS) to assess red mullet (Mullus barbatus) freshness evolution during 10 days of storage, at two different storage temperatures (0 and 4 °C). To check the effectiveness of the purposed physical methods, CVS features (loss in the epidermis pigmentation, development of gill mucus and eye concavity index) and firmness have been compared with chemical trimethylamine content and sensory (QIM) attribute scores. As expected, fish degradation was faster at the higher temperature. Instrumental texture evaluation of fish by penetration test enabled to detect distinctive firmness changes due to onset and resolution of rigor mortis, and the successive tenderization phenomenon. Among CVS parameters, the epidermis pigmentation loss, and particularly the eye shape modification (eye concavity index) evidenced a high sensibility for the estimation of fresh red mullet quality loss, as a function of the two different storage conditions, and a good agreement with trimethylamine content and QIM response evolution.
Databáze: OpenAIRE
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