Premium
Predictive models for bacterial growth in sea bass ( D icentrarchus labrax ) stored in ice
Author(s) -
Carrascosa Conrado,
Millán Rafael,
Saavedra Pedro,
Jaber José R.,
Montenegro Tania,
Raposo António,
Pérez Esteban,
Sanjuán Esther
Publication year - 2014
Publication title -
international journal of food science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.831
H-Index - 96
eISSN - 1365-2621
pISSN - 0950-5423
DOI - 10.1111/ijfs.12307
Subject(s) - dicentrarchus , sea bass , food spoilage , food science , biology , photobacterium phosphoreum , gill , shewanella putrefaciens , fishery , microorganism , mesophile , bacteria , fish <actinopterygii> , genetics
Summary The purpose of this paper was to estimate microbial growth through predictive modelling as a key element in determining the quantitative microbiological contamination of sea bass stored in ice and cultivated in different seasons of the year. In the present study, two different statistical models were used to analyse changes in microbial growth in whole, ungutted sea bass ( D icentrarchus labrax ) stored in ice. The total counts of aerobic mesophilic and psychrotrophic bacteria, P seudomonas sp., A eromonas sp., S hewanella putrefaciens, E nterobacteriaceae, sulphide‐reducing C lostridium and P hotobacterium phosphoreum were determined in muscle, skin and gills over an 18‐day period using traditional methods and evaluating the seasonal effect. The results showed that specific spoilage bacteria ( SSB ) were dominant in all tissues analysed, but were mainly found in the gills. Predictive modelling showed a seasonal effect among the fish analysed. The application of these models can contribute to the improvement of food safety control by improving knowledge of the microorganisms responsible for the spoilage and deterioration of sea bass.