Predictive models for bacterial growth in sea bass (Dicentrarchus labrax) stored in ice. (30th August 2013)

• Record Type: Journal Article
• Authors: Carrascosa, Conrado; Millán, Rafael; Saavedra, Pedro; Jaber, José R.; Montenegro, Tania; Raposo, António; Pérez, Esteban; Sanjuán, Esther
• Is Part Of: International journal of food science & technology. Volume 49:Number 2(2014:Feb.)
• Page Start: 354
• Page End: 363
• Publication Date: 2013-08-30
• Subjects: Food industry and trade -- Periodicals; 664
• DOI: 10.1111/ijfs.12307
• Languages: English
• ISSNs: 0950-5423

Abstract

<abstract abstract-type="main" id="ijfs12307-abs-0001"> <title>Summary</title> <p>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 (<italic>Dicentrarchus labrax</italic>) stored in ice. The total counts of aerobic mesophilic and psychrotrophic bacteria, <italic>Pseudomonas</italic> sp., <italic>Aeromonas</italic> sp., <italic>Shewanella putrefaciens, </italic>Enterobacteriaceae, sulphide‐reducing <italic>Clostridium</italic> and <italic>Photobacterium phosphoreum</italic> 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.</p> </abstract>