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Modeling and Predicting the Biofilm Formation of Salmonella Virchow with Respect to Temperature and Ph

Overview of attention for article published in Biologia Futura, December 2016
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Title
Modeling and Predicting the Biofilm Formation of Salmonella Virchow with Respect to Temperature and Ph
Published in
Biologia Futura, December 2016
DOI 10.1556/018.67.2016.1.8
Pubmed ID
Authors

M. Nima Ariafar, Sencer Buzrul, Nefise Akçelik

Abstract

Biofilm formation of Salmonella Virchow was monitored with respect to time at three different temperature (20, 25 and 27.5 °C) and pH (5.2, 5.9 and 6.6) values. As the temperature increased at a constant pH level, biofilm formation decreased while as the pH level increased at a constant temperature, biofilm formation increased. Modified Gompertz equation with high adjusted determination coefficient (Radj(2)) and low mean square error (MSE) values produced reasonable fits for the biofilm formation under all conditions. Parameters of the modified Gompertz equation could be described in terms of temperature and pH by use of a second order polynomial function. In general, as temperature increased maximum biofilm quantity, maximum biofilm formation rate and time of acceleration of biofilm formation decreased; whereas, as pH increased; maximum biofilm quantity, maximum biofilm formation rate and time of acceleration of biofilm formation increased. Two temperature (23 and 26 °C) and pH (5.3 and 6.3) values were used up to 24 h to predict the biofilm formation of S. Virchow. Although the predictions did not perfectly match with the data, reasonable estimates were obtained. In principle, modeling and predicting the biofilm formation of different microorganisms on different surfaces under various conditions could be possible.

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The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Postgraduate 3 18%
Student > Bachelor 2 12%
Student > Ph. D. Student 2 12%
Researcher 2 12%
Professor > Associate Professor 2 12%
Other 3 18%
Unknown 3 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 35%
Biochemistry, Genetics and Molecular Biology 2 12%
Veterinary Science and Veterinary Medicine 1 6%
Earth and Planetary Sciences 1 6%
Medicine and Dentistry 1 6%
Other 0 0%
Unknown 6 35%