Articles
Modelling redox potential curves for identification of selected bacterial strains
Article number
1382_21
Pages
163 – 170
Language
English
Abstract
Being time consuming is the main weakness of colony counting method that has led to develop new technologies.
One recent alternative approach is based on the redox potential which defines the oxidative change of complex media, and it is basically related to the consumption of oxygen and nutrients, and the production of reduced molecules in the measured biological system.
This study shows the characterization and discrimination results of the redox potential curves of three bacteria, Escherichia coli, Pseudomonas aeruginosa, and Salmonella enterica serovar Typhimurium.
Evaluated data were acquired using a MicroTester instrument (Microtest Ltd., Budapest, Hungary), which is a multi-channel redox potential measuring device.
All together 40 curves were analyzed.
Curve fitting and classification based on linear discriminant analysis (LDA) were performed using R and RStudio free software.
Three sigmoidal R models were compared with first order statistical parameters to describe the unique shape of the redox potential curves (Gompertz, Rosso, and Logistic). First order statistical parameters achieved 100% accuracy with LDA. Rosso and Logistic models gave comparable results with the correct classification of 95%. Gompertz model was the least accurate model with 92.5% correct classification.
Results confirmed that each studied bacteria has a distinctive redox potential curve shape and their discrimination is possible based on this feature.
One recent alternative approach is based on the redox potential which defines the oxidative change of complex media, and it is basically related to the consumption of oxygen and nutrients, and the production of reduced molecules in the measured biological system.
This study shows the characterization and discrimination results of the redox potential curves of three bacteria, Escherichia coli, Pseudomonas aeruginosa, and Salmonella enterica serovar Typhimurium.
Evaluated data were acquired using a MicroTester instrument (Microtest Ltd., Budapest, Hungary), which is a multi-channel redox potential measuring device.
All together 40 curves were analyzed.
Curve fitting and classification based on linear discriminant analysis (LDA) were performed using R and RStudio free software.
Three sigmoidal R models were compared with first order statistical parameters to describe the unique shape of the redox potential curves (Gompertz, Rosso, and Logistic). First order statistical parameters achieved 100% accuracy with LDA. Rosso and Logistic models gave comparable results with the correct classification of 95%. Gompertz model was the least accurate model with 92.5% correct classification.
Results confirmed that each studied bacteria has a distinctive redox potential curve shape and their discrimination is possible based on this feature.
Authors
E. Yakdhane, D. Tőzsér, K. Szakmár, L. Baranyai, G. Kiskó
Keywords
Escherichia, Pseudomonas, Salmonella, multivariate classification, Rosso model, Gompertz model, Logistic model, nonlinear regression
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