scispace - formally typeset
Open AccessJournal ArticleDOI

Convenient Model To Describe the Combined Effects of Temperature and pH on Microbial Growth.

Reads0
Chats0
TLDR
A new model in which the maximum microbial specific growth rate ((mu)(infmax)) is described as a function of pH and temperature is presented and an analysis of this new model with an Escherichia coli O157:H7 data set showed that there was a good correspondence between observed and calculated (mu)infmax values.
Abstract
A new model in which the maximum microbial specific growth rate ((mu)(infmax)) is described as a function of pH and temperature is presented. The seven parameters of this model are the three cardinal pH parameters (the pH below which no growth occurs, the pH above which no growth occurs, and the pH at which the (mu)(infmax) is optimal), the three cardinal temperature parameters (the temperature below which no growth occurs, the temperature above which no growth occurs, and the temperature at which the (mu)(infmax) is optimal), and the specific growth rate at the optimum temperature and optimum pH. The model is a combination of the cardinal temperature model with inflection and the cardinal pH model (CPM). The CPM was compared with the models of Wijtzes et al. and Zwietering et al. by using previously published data sets. The models were compared on the basis of the usual criteria (simplicity, biological significance and minimum number of parameters, applicability, quality of fit, minimum structural correlations, and ease of initial parameter estimation), and our results justified the choice of the CPM. Our combined model was constructed by using the hypothesis that the temperature and pH effects on the (mu)(infmax) are independent. An analysis of this new model with an Escherichia coli O157:H7 data set showed that there was a good correspondence between observed and calculated (mu)(infmax) values. The potential and convenience of the model are discussed.

read more

Content maybe subject to copyright    Report

Citations
More filters
Journal ArticleDOI

Soil bacterial and fungal communities across a pH gradient in an arable soil.

TL;DR: Soils collected across a long-term liming experiment were used to investigate the direct influence of pH on the abundance and composition of the two major soil microbial taxa, fungi and bacteria, and both the relative abundance and diversity of bacteria were positively related to pH.
Journal ArticleDOI

GInaFiT, a freeware tool to assess non-log-linear microbial survivor curves

TL;DR: GInaFiT (Geeraerd and Van Impe Inactivation Model Fitting Tool) as discussed by the authors is a freeware add-in for Microsoft Excel aiming at bridging the gap between people developing predictive modelling approaches and end-users in the food industry not familiar with or not disposing over advanced non-linear regression analysis tools.

GInaFiT, a freeware tool to assess non-log-linear microbial survivor curves (vol 102, pg 95, 2005)

TL;DR: The GInaFiT (Geeraerd and Van Impe Inactivation Model Fitting Tool), a freeware Add-in for Microsoft Excel aiming at bridging the gap between people developing predictive modelling approaches and end-users in the food industry not familiar with or not disposing over advanced non-linear regression analysis tools, is presented.
Journal ArticleDOI

Geographic distance and pH drive bacterial distribution in alkaline lake sediments across Tibetan Plateau

TL;DR: It is shown that pH is the best predictor of bacterial community structure in alkaline sediments, and that both geographic distance and chemical factors govern bacterial biogeography in lake sediments.
References
More filters
Journal ArticleDOI

Relationship between temperature and growth rate of bacterial cultures.

TL;DR: A linear relationship between in square root of growth rate constant (r) and temperature (T), namely, square root = b (T - T0), where b is the regression coefficient and T0 is a hypothetical temperature which is an intrinsic property of the organism.
Journal ArticleDOI

Model for bacterial culture growth rate throughout the entire biokinetic temperature range.

TL;DR: The "square-root" relationship proposed by Ratkowsky et al. for modeling the growth rate of bacteria below the optimum growth temperature was extended to cover the full biokinetic temperature range and the least-squares estimators of the parameters of the model were almost unbiased and normally distributed.
Journal ArticleDOI

An Unexpected Correlation between Cardinal Temperatures of Microbial Growth Highlighted by a New Model

TL;DR: A very strong and unexpected linear correlation between the cardinal temperatures was observed and the three cardinal temperatures were found to be independent of mu opt.
Journal ArticleDOI

The effect of sodium chloride and temperature on the rate and extent of growth of Clostridium botulinum type A in pasteurized pork slurry

TL;DR: A selective medium was used to enumerate Clostridium botulinum growing in the presence of natural spoilage organisms in a model cured pork slurry and the information obtained provides a framework to investigate the effects of a wider range of additives or variables on the growth responses of Cl.Botulinum.
Related Papers (5)