Literature DB >> 27052713

Microbial and sensorial models for head-on and gutted (HOG) Atlantic Salmon (Salmo salar) stored from 0 to 15 °C.

Olivia J Churchill1, Judith Fernandez-Piquer1, Shane M Powell1, Mark L Tamplin2.   

Abstract

Predictive models offer efficient means to manage the quality and safety of highly perishable seafood. Salmon is an increasingly popular seafood, and relies on well managed domestic and international supply chains to minimize growth of spoilage and pathogenic bacteria. While the literature describes predictive models for smoked and modified atmosphere packaged salmon, there are no reported models for spoilage bacteria and Listeria monocytogenes on head-on and gutted (HOG) aerobically-stored Atlantic salmon. Predictive models were developed for microbial and sensorial degradation of HOG Atlantic salmon stored at 0-15 °C until the end of shelf-life. Total Viable Count (TVC) and Pseudomonas spp. had similar growth rates at 0, 5 and 10 °C, but TVC rate was higher at 15 °C. L. monocytogenes growth rate at 0 °C was 0.004 log10 cfu/h, and showed a log-linear increase (R(2) = 0.99) to 0.079 log10 cfu/h at 15 °C. Sensory Quality Index (QI) scores were 2.4, 4.5, and 7.2 times greater at 5, 10 and 15 °C, respectively, compared to 0 °C. QI and TVC rates had a relatively strong relationship at 5 (R(2) = 0.87), 10 (R(2) = 0.80) and 15 °C (R(2) = 0.78), compared to 0 °C (R(2) = 0.50). These models are potential tools to manage the safety and quality of HOG Atlantic salmon in supply chains.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Listeria monocytogenes; Predictive modelling; Pseudomonas spp.; Quality index method; Spoilage

Mesh:

Year:  2016        PMID: 27052713     DOI: 10.1016/j.fm.2016.02.006

Source DB:  PubMed          Journal:  Food Microbiol        ISSN: 0740-0020            Impact factor:   5.516


  1 in total

1.  Study on the spoilage potential of Pseudomonas fluorescens on salmon stored at different temperatures.

Authors:  Jing Xie; Zhen Zhang; Sheng-Ping Yang; Ying Cheng; Yun-Fang Qian
Journal:  J Food Sci Technol       Date:  2017-11-04       Impact factor: 2.701

  1 in total

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