Modelling growth/no growth interface of Zygosaccharomyces bailii in simulated acid sauces as a function of natamycin, xanthan gum and sodium chloride concentrations
Probabilistic microbial modelling using logistic regression was used to predict the growth/no growth (G/NG) interfaces of Zygosaccharomyces bailii in simulated acid sauces as a function of natamycin, xanthan gum (XG) and sodium chloride concentrations. The growth was assessed colorimetrically by usi...
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Acceso en línea: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_09639969_v116_n_p916_Zalazar http://hdl.handle.net/20.500.12110/paper_09639969_v116_n_p916_Zalazar |
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paper:paper_09639969_v116_n_p916_Zalazar2023-06-08T15:58:17Z Modelling growth/no growth interface of Zygosaccharomyces bailii in simulated acid sauces as a function of natamycin, xanthan gum and sodium chloride concentrations Growth/no growth interface Model acid sauces Natamycin Sodium chloride Xanthan gum Zygosaccharomyces bailii Regression analysis Sodium chloride Antagonistic effects Chloride concentrations Detection reagents Growth interfaces Logistic Regression modeling Logistic regressions Natamycin Zygosaccharomyces bailii Xanthan gum Probabilistic microbial modelling using logistic regression was used to predict the growth/no growth (G/NG) interfaces of Zygosaccharomyces bailii in simulated acid sauces as a function of natamycin, xanthan gum (XG) and sodium chloride concentrations. The growth was assessed colorimetrically by using 2-(4-iodophenyl)-3-(4-nitrophenyl)-5-phenyl-2H-tetrazolium chloride and 2-methoxy-1,4-naphthoquinone as detection reagents. The logistic regression model successfully predicted G/NG probability. The detection reagents used allowed the evaluation of G/NG interfaces in opaque systems with an excellent agreement with the plate count method. Natamycin concentration of 12 mg/L was needed to inhibit Z. bailii growth independently of the presence of XG and/or NaCl. Addition of 3.00 and 6.00% of NaCl exerted an antagonistic effect on natamycin action. Furthermore, addition of 0.25 and 0.50% XG decreased natamycin and/or NaCl action. However, an increased in XG concentration to 1.00% decreased yeast growth. Mentioned results highlighted the importance of the correct selection of stress factors applied to inhibit Z. bailii growth. © 2018 Elsevier Ltd 2019 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_09639969_v116_n_p916_Zalazar http://hdl.handle.net/20.500.12110/paper_09639969_v116_n_p916_Zalazar |
institution |
Universidad de Buenos Aires |
institution_str |
I-28 |
repository_str |
R-134 |
collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
topic |
Growth/no growth interface Model acid sauces Natamycin Sodium chloride Xanthan gum Zygosaccharomyces bailii Regression analysis Sodium chloride Antagonistic effects Chloride concentrations Detection reagents Growth interfaces Logistic Regression modeling Logistic regressions Natamycin Zygosaccharomyces bailii Xanthan gum |
spellingShingle |
Growth/no growth interface Model acid sauces Natamycin Sodium chloride Xanthan gum Zygosaccharomyces bailii Regression analysis Sodium chloride Antagonistic effects Chloride concentrations Detection reagents Growth interfaces Logistic Regression modeling Logistic regressions Natamycin Zygosaccharomyces bailii Xanthan gum Modelling growth/no growth interface of Zygosaccharomyces bailii in simulated acid sauces as a function of natamycin, xanthan gum and sodium chloride concentrations |
topic_facet |
Growth/no growth interface Model acid sauces Natamycin Sodium chloride Xanthan gum Zygosaccharomyces bailii Regression analysis Sodium chloride Antagonistic effects Chloride concentrations Detection reagents Growth interfaces Logistic Regression modeling Logistic regressions Natamycin Zygosaccharomyces bailii Xanthan gum |
description |
Probabilistic microbial modelling using logistic regression was used to predict the growth/no growth (G/NG) interfaces of Zygosaccharomyces bailii in simulated acid sauces as a function of natamycin, xanthan gum (XG) and sodium chloride concentrations. The growth was assessed colorimetrically by using 2-(4-iodophenyl)-3-(4-nitrophenyl)-5-phenyl-2H-tetrazolium chloride and 2-methoxy-1,4-naphthoquinone as detection reagents. The logistic regression model successfully predicted G/NG probability. The detection reagents used allowed the evaluation of G/NG interfaces in opaque systems with an excellent agreement with the plate count method. Natamycin concentration of 12 mg/L was needed to inhibit Z. bailii growth independently of the presence of XG and/or NaCl. Addition of 3.00 and 6.00% of NaCl exerted an antagonistic effect on natamycin action. Furthermore, addition of 0.25 and 0.50% XG decreased natamycin and/or NaCl action. However, an increased in XG concentration to 1.00% decreased yeast growth. Mentioned results highlighted the importance of the correct selection of stress factors applied to inhibit Z. bailii growth. © 2018 Elsevier Ltd |
title |
Modelling growth/no growth interface of Zygosaccharomyces bailii in simulated acid sauces as a function of natamycin, xanthan gum and sodium chloride concentrations |
title_short |
Modelling growth/no growth interface of Zygosaccharomyces bailii in simulated acid sauces as a function of natamycin, xanthan gum and sodium chloride concentrations |
title_full |
Modelling growth/no growth interface of Zygosaccharomyces bailii in simulated acid sauces as a function of natamycin, xanthan gum and sodium chloride concentrations |
title_fullStr |
Modelling growth/no growth interface of Zygosaccharomyces bailii in simulated acid sauces as a function of natamycin, xanthan gum and sodium chloride concentrations |
title_full_unstemmed |
Modelling growth/no growth interface of Zygosaccharomyces bailii in simulated acid sauces as a function of natamycin, xanthan gum and sodium chloride concentrations |
title_sort |
modelling growth/no growth interface of zygosaccharomyces bailii in simulated acid sauces as a function of natamycin, xanthan gum and sodium chloride concentrations |
publishDate |
2019 |
url |
https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_09639969_v116_n_p916_Zalazar http://hdl.handle.net/20.500.12110/paper_09639969_v116_n_p916_Zalazar |
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1768545236971159552 |