Literature DB >> 18775580

Mathematical modelling for predicting the growth of Pseudomonas spp. in poultry under variable temperature conditions.

Radovan Gospavic1, Judith Kreyenschmidt, Stefanie Bruckner, Viktor Popov, Nasimul Haque.   

Abstract

A dynamic growth model under variable temperature conditions was implemented and calibrated using raw data for microbial growth of Pseudomonas spp. in poultry under aerobic conditions. The primary model was implemented using measurement data under a set of fixed temperatures. The two primary models used for predicting the growth under constant temperature conditions were: Baranyi and modified Gompertz. For the Baranyi model the maximum specific growth rate and the lag phase at constant environmental conditions are expressed in exact form and it has been shown that in limit case when maximal cells concentration is much higher than the initial concentration the maximum specific growth rate is approximately equal to the specific growth rate. The model parameters are determined in a temperature range of 2-20 degrees C. As a secondary model the square root model was used for maximum specific growth rate in both models. In both models the main assumption, that the initial physiological state of the inoculum is constant and independent of the environmental parameters, is used, and a free parameter was implemented which was determined by minimizing the mean square error (MSE) relative to the measurement data. Two temperature profiles were used for calibration of the models on the initial conditions of the cells.

Mesh:

Year:  2008        PMID: 18775580     DOI: 10.1016/j.ijfoodmicro.2008.07.022

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


  10 in total

1.  Prediction of acid lactic-bacteria growth in turkey ham processed by high hydrostatic pressure.

Authors:  S P Mathias; A Rosenthal; A Gaspar; G M F Aragão; A Slongo-Marcusi
Journal:  Braz J Microbiol       Date:  2013-04-05       Impact factor: 2.476

2.  Predictive modeling of Pseudomonas fluorescens growth under different temperature and pH values.

Authors:  Letícia Dias Dos Anjos Gonçalves; Roberta Hilsdorf Piccoli; Alexandre de Paula Peres; André Vital Saúde
Journal:  Braz J Microbiol       Date:  2017-01-04       Impact factor: 2.476

3.  Use of modified Richards model to predict isothermal and non-isothermal microbial growth.

Authors:  Jhony Tiago Teleken; Alessandro Cazonatto Galvão; Weber da Silva Robazza
Journal:  Braz J Microbiol       Date:  2018-03-07       Impact factor: 2.476

4.  Modeling the Growth and Interaction Between Brochothrix thermosphacta, Pseudomonas spp., and Leuconostoc gelidum in Minced Pork Samples.

Authors:  Emilie Cauchie; Laurent Delhalle; Ghislain Baré; Assia Tahiri; Bernard Taminiau; Nicolas Korsak; Sophie Burteau; Papa Abdoulaye Fall; Frédéric Farnir; Georges Daube
Journal:  Front Microbiol       Date:  2020-04-09       Impact factor: 5.640

5.  Dimensional Analysis Model Predicting the Number of Food Microorganisms.

Authors:  Cuiqin Li; Laping He; Yuedan Hu; Hanyu Liu; Xiao Wang; Li Chen; Xuefeng Zeng
Journal:  Front Microbiol       Date:  2022-02-08       Impact factor: 5.640

6.  Methodology for modeling the microbial contamination of air filters.

Authors:  Yun Haeng Joe; Ki Young Yoon; Jungho Hwang
Journal:  PLoS One       Date:  2014-02-11       Impact factor: 3.240

7.  Modeling the growth of Listeria monocytogenes on the surface of smear- or mold-ripened cheese.

Authors:  M Sol Schvartzman; Ursula Gonzalez-Barron; Francis Butler; Kieran Jordan
Journal:  Front Cell Infect Microbiol       Date:  2014-07-03       Impact factor: 5.293

8.  Growth Modelling of Listeria monocytogenes in Korean Pork Bulgogi Stored at Isothermal Conditions.

Authors:  Na-Kyoung Lee; Sin Hye Ahn; Joo-Yeon Lee; Hyun-Dong Paik
Journal:  Korean J Food Sci Anim Resour       Date:  2015-02-28       Impact factor: 2.622

9.  Dependence of bacterial growth rate on dynamic temperature changes.

Authors:  Abhishek Dey; Venkat Bokka; Shaunak Sen
Journal:  IET Syst Biol       Date:  2020-04       Impact factor: 1.615

10.  Freshness-based real-time shelf-life estimation of packaged chicken meat under dynamic storage conditions.

Authors:  Samuel Mezemir Yimenu; Junemo Koo; Byeong Sam Kim; Jong Hoon Kim; Ji Young Kim
Journal:  Poult Sci       Date:  2019-12-01       Impact factor: 3.352

  10 in total

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