Literature DB >> 18692267

Modelling spoilage of fresh turbot and evaluation of a time-temperature integrator (TTI) label under fluctuating temperature.

Maider Nuin1, Begoña Alfaro, Ziortza Cruz, Nerea Argarate, Susie George, Yvan Le Marc, June Olley, Carmen Pin.   

Abstract

Kinetic models were developed to predict the microbial spoilage and the sensory quality of fresh fish and to evaluate the efficiency of a commercial time-temperature integrator (TTI) label, Fresh Check(R), to monitor shelf life. Farmed turbot (Psetta maxima) samples were packaged in PVC film and stored at 0, 5, 10 and 15 degrees C. Microbial growth and sensory attributes were monitored at regular time intervals. The response of the Fresh Check device was measured at the same temperatures during the storage period. The sensory perception was quantified according to a global sensory indicator obtained by principal component analysis as well as to the Quality Index Method, QIM, as described by Rahman and Olley [Rahman, H.A., Olley, J., 1984. Assessment of sensory techniques for quality assessment of Australian fish. CSIRO Tasmanian Regional Laboratory. Occasional paper n. 8. Available from the Australian Maritime College library. Newnham. Tasmania]. Both methods were found equally valid to monitor the loss of sensory quality. The maximum specific growth rate of spoilage bacteria, the rate of change of the sensory indicators and the rate of change of the colour measurements of the TTI label were modelled as a function of temperature. The temperature had a similar effect on the bacteria, sensory and Fresh Check kinetics. At the time of sensory rejection, the bacterial load was ca. 10(5)-10(6) cfu/g. The end of shelf life indicated by the Fresh Check label was close to the sensory rejection time. The performance of the models was validated under fluctuating temperature conditions by comparing the predicted and measured values for all microbial, sensory and TTI responses. The models have been implemented in a Visual Basic add-in for Excel called "Fish Shelf Life Prediction (FSLP)". This program predicts sensory acceptability and growth of spoilage bacteria in fish and the response of the TTI at constant and fluctuating temperature conditions. The program is freely available at http://www.azti.es/muestracontenido.asp?idcontenido=980&content=15&nodo1=30&nodo2=0.

Entities:  

Mesh:

Year:  2008        PMID: 18692267     DOI: 10.1016/j.ijfoodmicro.2008.04.010

Source DB:  PubMed          Journal:  Int J Food Microbiol        ISSN: 0168-1605            Impact factor:   5.277


  5 in total

1.  Guideline for proper usage of time temperature integrator (TTI) avoiding underestimation of food deterioration in terms of temperature dependency: A case with a microbial TTI and milk.

Authors:  Min Jung Kim; Hye Ri Park; Seung Ju Lee
Journal:  Food Sci Biotechnol       Date:  2016-06-30       Impact factor: 2.391

2.  Thermochromic Polymer Film Sensors for Detection of Incipient Thermal Damage in Carbon Fiber⁻Epoxy Composites.

Authors:  Ryan Toivola; Sei-Hum Jang; Shawn Baker; Alex K-Y Jen; Brian D Flinn
Journal:  Sensors (Basel)       Date:  2018-04-27       Impact factor: 3.576

3.  Preliminary Study on Biosensor-Type Time-Temperature Integrator for Intelligent Food Packaging.

Authors:  A T M Mijanur Rahman; Do Hyeon Kim; Han Dong Jang; Jung Hwa Yang; Seung Ju Lee
Journal:  Sensors (Basel)       Date:  2018-06-15       Impact factor: 3.576

Review 4.  Assessment and Prediction of Fish Freshness Using Mathematical Modelling: A Review.

Authors:  Míriam R García; Jose Antonio Ferez-Rubio; Carlos Vilas
Journal:  Foods       Date:  2022-08-02

5.  Effect of the Combination of Vanillin and Chitosan Coating on the Microbial Diversity and Shelf-Life of Refrigerated Turbot (Scophthalmus maximus) Filets.

Authors:  Tingting Li; Xiaojia Sun; Haitao Chen; Binbin He; Yongchao Mei; Dangfeng Wang; Jianrong Li
Journal:  Front Microbiol       Date:  2020-03-31       Impact factor: 5.640

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.